Browse Topic: Navigation and guidance systems

Items (1,325)
Find
Aeroseek: Exploring LLM-Enhanced Monte-Carlo Path Planning for UAV Navigation2026-99-061311/6/2026
While Unmanned Aerial Vehicles (UAVs) hold immense potential for transforming the low-altitude economy, developing an agent that combines both intelligence and flexibility remains a significant challenge. To this end, we propose a novel aerial navigation system, Aeroseek, to search for executable paths that coherently transition from cognitive understanding to physical movement, enabling more autonomous and flexible navigation with instruction guidance. Specifically, given a navigation instruction, we follow a fast-andslow thinking procedure inspired by human pilots by breaking down complex decisions into manageable sub-tasks and initiating motion planning immediately upon the completion of each sub-task for realtime movement. By integrating a multi-branch Chain-of-Thought, Aeroseek is capable of combining reasoning with spatial recognition and self-verification to search for robust sub-goals under expected constraints. For sub-goal navigation, we introduce Online Kinodynamic Monte-Carlo Path Planning (OnKi-MCPP), a novel motion planning approach handling both kinodynamic constraints and path search, while ensuring obstacle avoidance for UAVs. Benefiting from the proposed two-tier searching protocol, Aeroseek demonstrates comprehensive capabilities in processing complicated instructions and adapts to dynamic aerial conditions. Extensive experiments demonstrate the advantages of Aeroseek across tasks of varying complexity.
Luo, Guoan, Xu, Tian, Zhou, Jiacong, Wang, Xianyun
Intelligent Unmanned Aerial Vehicle System for Automated Red Pine Cone Harvesting in Dense Forests2026-99-063011/6/2026
This paper describes an intelligent unmanned aerial vehicle (UAV) system that automates red pine cone harvesting in dense forests to mitigate the safety and inefficiency of traditional manual harvesting. The suggested system combines multi-sensor fusion perception, variable-stiffness rigid-flexible composite manipulator, and smart path planning into a single aerial harvesting system. To create a three-dimensional model of the environment and robust cone detection under complicated lighting conditions and extreme canopy occlusion, a heterogeneous sensor suite such as LiDAR, depth cameras, and inertial sensors is used. According to the results of fused perception, collision-free approach paths are created to lead the UAV safely to target cones in limited three-dimensional spaces. One of the significant contributions of this work is the iterative design and optimization of a dedicated harvesting manipulator to be used in aerial forestry operations. A comparative analysis of various structural designs leads to the creation of a rigid flexible composite manipulator with an effective workspace diameter of 1.8 m and adequate stiffness to reduce the effects of the downwash of the UAV rotor. The disturbance-assisted harvesting strategy is adopted by the system, which enables efficient dislodgement of cones without requiring accurate grasping. The proposed technical route is proven to be feasible based on laboratory experiments and initial field tests carried out in real forest settings. It has been experimentally proven that the combined system can effectively perform autonomous harvesting cycles, including target recognition, navigation, and cone dislodgement, thus offering a practical technical paradigm of intelligent and safe forestry harvesting applications.
Shi, Shuaiqi, Du, Yisheng, Li, Xiang, Wang, Weidong
Research on Intelligent Switching and Control Strategy of Air-Sea Amphibious WIG Craft Based on Multi-Sensor Fusion2026-99-061911/6/2026
Aiming at the core problems of abrupt changes in dynamic characteristics and poor smoothness in mode switching during the cross-medium operation of amphibious wing-in-ground (WIG) craft, this paper develops an intelligent switching and control system based on multi-sensor fusion. The system integrates measurement data from the Global Navigation Satellite System (GNSS), Inertial Measurement Unit (IMU), and Light Detection and Ranging (LiDAR) to construct a state observation module for mode switching decision-making. On this basis, a fuzzy switching logic centered on flight altitude and sea state characteristics is proposed, and a hybrid control strategy combining Linear Quadratic Regulator (LQR) and Proportional-Integral-Derivative (PID) is designed to realize the smooth transition between water surface and flight modes. Numerical simulations conducted in Python demonstrate that the proposed control scheme can accurately determine the mode switching timing, stabilize the pitch angle fluctuation within ±3° during the transition process, and effectively enhance the ability of WIG craft to operate autonomously and stably of the WIG craft in complex sea conditions.
Zhang, Qihao, Yan, Yifei, Cao, Fengshuo, Xiong, Yueling, Liu, Qing, Deng, Yanpeng, Wu, Peng
Comparative Analysis of BDS PPP-B2b on Shore-Based and Ship-Borne Platforms2026-99-064211/6/2026
The integration technology of autonomous navigation and positioning provides critical technical support for high-precision positioning in the marine environment. As an indispensable core technology in modern marine navigation, satellite navigation plays a vital role in marine navigation safety and precision operations, such as marine surveying, ship navigation, and offshore engineering. The BDS PPPB2b service is commonly used in the marine high-precision application. However, compared to the landing application, the BDS PPP in the marine environment performs poorly due to the complex environmental factors on the ship-borne platform, such as hull occlusion and sea surface signal reflection. To compare and analyze the positioning performance differences of BDS PPP-B2b between shore-based and ship-borne platforms, an experiment has been conducted by using real data of the BDS receiver on both shore-based and ship-borne platforms. The results have shown that the BDS PPPB2b positioning performance on a ship-borne platform achieves poor satellite visibility and stable positioning performance. The BDS PPPB2b positioning accuracy after convergence can reach centimeter and decimeter levels on shore-based and ship-borne platforms, respectively.
Wang, Xilong, Li, Menghao, Shi, Huiwen, Sun, Min, Lu, Yin
Design Strategy for Cislunar Space Navigation Constellations Based on Navigation and Autonomous Navigation Performance2026-99-062511/6/2026
This paper proposes a bi-objective design strategy for cislunar navigation constellations, simultaneously optimizing navigation performance for target users and the autonomous navigation performance of constellation itself. The design variables include orbital characteristic parameters and inter-satellite phases, while the objectives are defined as the worst-case Geometric/Position Dilution of Precision (GDOP/PDOP) for users and the constellation's aggregated Dynamic and Geometric Dilution of Precision (DAGDOP). To address phase jump issues, the optimization is formulated on a product manifold and solved using the Riemannian steepest descent algorithm via the Pymanopt toolbox. Three constellations are designed by this strategy, which are six-satellite constellation for the Lunar South Pole station, a twenty-satellite constellation for lunar surface and lunar orbit users, and an eight-satellite constellation for a LEO-to-DRO transfer trajectory. Simulation results demonstrate that the optimized designs achieve the required geometric visibility, maintain GDOP/PDOP below specified usable thresholds (e.g., max PDOP of 5.96 for the South Pole, max GDOP of 2.28 for the transfer), and exhibit stable autonomous navigation performance. The study confirms the feasibility of the proposed strategy for designing practical, high-performance navigation constellation deployments across diverse cislunar mission scenarios.
Chan, Meichen, Qiu, Haipeng, Hu, Jiaxin, Yang, Leping, Zhu, Yanwei, Chen, Yujie
A Multimodal Perception Unmanned System Based on GNN and SLAM2026-99-063311/6/2026
The complex environments encountered in emergency rescue scenarios pose severe challenges to the perception and navigation capabilities of unmanned ground systems. This paper designs and implements a ground unmanned rescue system named "SkyEye" based on multimodal perception fusion. The system adopts a four-wheel independent steering and four-wheel drive (4WIS-4WID) omnidirectional ground chassis and integrates a 4D-FMCW LiDAR, structured-light binocular cameras, a high-precision IMU, and Beidou RTK. Through a tightly coupled graph-optimization SLAM framework and GNN-based dynamic obstacle prediction, it achieves robust perception and autonomous navigation in complex rescue scenarios. Experiments show that under clear open-field conditions, the system achieves centimeterlevel positioning accuracy and obstacle recognition accuracy ≥95%. In extreme dense smoke, recognition accuracy remains at 82.6% with stable navigation. The obstacle avoidance response latency is ≤0.5 s in narrow spaces and GNSS-denied tunnels. This paper elaborates the platform kinematic model, multi-sensor spatio-temporal calibration, detailed SLAM implementation, and complete GNN trajectory prediction pipeline, providing a theoretical basis and engineering reference for ground emergency rescue unmanned systems.
Li, Yizhen, Wei, Yuxiao, Wen, Yuanhao, Xun, Xuhang, Wang, Chengjun, Wu, Peng
UAV Positioning and Tracking Measurement Method Based on Laser-Vision Dual-Mode Fusion2026-99-192911/6/2026
Flight positioning accuracy is a key technical indicator of unmanned aerial vehicle (UAV) systems. To quantitatively and accurately evaluate the positioning accuracy of UAV flight trajectories, this paper proposes a theoretical model for motion trajectory measurement and positioning, as well as a systematic solution for tracking measurement, based on a 2D tracking turntable carrying a dual-mode optoelectronic fusion integration system consisting of a laser ranging sensor and a vision camera. It analyzes the main influencing factors of measurement errors and establishes a measurement error model for flight trajectory positioning. Finally, flight trajectory tracking, positioning, and measurement experiments are carried out based on the principle prototype, which verifies the correctness of the method model and the feasibility of the system scheme. This study provides a theoretical basis and technical support for the testing of UAV flight control positioning accuracy indicators.
Qi, Weijie, Qiao, Yongming
Cybersecurity Risks in Safety-Critical Off-Highway Vehicle Controllers and Hardware Security Modules-Backed Mitigation Strategies2026-28-020411/5/2026
Off-highway vehicles (OHV) increasingly rely on electronically controlled, safety-critical systems such as braking, steering, powertrain, and implement control electronic control unit (ECUs). The integration of connectivity, telematics, precision-agriculture features, and semi-autonomous operation has transformed these machines into complex cyber-physical systems. While these capabilities improve productivity and operational efficiency, they also expand the attack surface, creating cybersecurity risks that can directly impact vehicle control, operator safety, and field operations. Off-highway platforms often operate in remote environments, use legacy in-vehicle networks, and have long service lifecycles, further amplifying exposure to cyber threats. Recent research and real-world demonstrations highlight that many attacks on safety-critical controllers exploit fundamental architectural weaknesses rather than advanced exploits. Common scenarios include unauthenticated CAN-based communication enabling message injection, replay, or spoofing of steering and braking commands; compromised telematics or wireless interfaces pivoting into safety-critical networks; unsecure over-the-air update mechanisms permitting unauthorized firmware installation; and misuse of diagnostic or maintenance access paths to invoke privileged ECU functions. Network-level attacks such as denial-of-service and sensor-level manipulation, including GPS or perception spoofing, further threaten the integrity and availability of control functions relied upon by modern agricultural machines. This paper examines these attack scenarios in the context of off-highway safety-critical controllers and discusses how Hardware Security Modules (HSMs) provide a practical trust anchor for mitigating such risks. HSMs onboard hardware-isolated execution, tamper-resistant key storage, and cryptographic enforcement that strengthen ECU security beyond secure boot. HSM-backed mechanisms enable authenticated and integrity-protected software updates, prevent execution of unauthorized firmware, support message authentication and freshness on in-vehicle networks, and harden diagnostic access through secure challenge-response mechanisms. By grounding cybersecurity risks in realistic off-highway use cases and mapping them to deployable HSM-backed controls, the paper illustrates how hardware-anchored security enhances runtime trust, supports safety objectives, and aligns off-highway vehicle architectures with emerging vehicle cybersecurity expectations, including the EU Cyber Resilience Act (CRA). In addition, a PoC implementation based on an automotive-grade embedded controller is presented to demonstrate secure boot, authenticated CAN communication, diagnostic access control, and runtime integrity monitoring, together with a validation methodology that demonstrates their practical effectiveness.
Maheshwaram, Chetan, Dasari, Manoj Sham
An Intelligent Computer Vision Framework for Duplicate Part Detection in Complex CAD Assemblies2026-28-017311/5/2026
Duplicate components in large-scale Digital Mock-Up (DMU) assemblies present a significant challenge to product integrity within Digital Twin environments operating on integrated OEM Product Lifecycle Management (PLM) platforms. These duplicates, often referred to as structural redundancies or doubloons, are characterized by geometrically identical or equivalent components occupying the same spatial location without corresponding justification in the Bill of Materials (BOM). Such inconsistencies arise from increasing assembly complexity, tool integration issues, and limitations of conventional scripting-based validation approaches. Existing duplicate detection methods rely heavily on manual inspection and isolated tool functionalities, making them impractical for large-scale assemblies. While interference analysis tools can detect spatial conflicts, they cannot reliably distinguish between valid engineering overlaps and unintended duplicate conditions. Consequently, a more structured and automated validation strategy is required. This paper presents an automated computer vision-based methodology developed within an OEM Digital Twin environment to address these challenges. The proposed framework combines interference-data extraction, image-based overlap assessment, automated duplicate screening, Active Feedback Learning, and BOM-integrated validation within a unified workflow. The methodology transforms interference-derived information into structured analytical features and uses Red Percentage–based overlap evaluation to identify potential duplicate conditions. The proposed approach enables scalable duplicate detection across complex assemblies while reducing dependence on manual review. Validation on production-scale automotive DMU datasets demonstrated significant reductions in engineering effort and substantial filtering of non-actionable interference records. By integrating computer vision analytics, feedback-driven noise elimination, and product structure validation, the proposed framework improves Digital Twin data integrity and supports efficient engineering workflows in modern OEM PLM environments.
Gnanaprakasam, Hepshibha, Sridhar, Ashok
Trajectory Optimization for Non-Cooperative Target Spacecraft Based on Sequential Convex Programming2026-99-233010/30/2026
Autonomous operations near space targets that do not cooperate present great challenges because position and attitude planning must be linked. A target of this type lacks navigation aids or communication systems, which makes relative motion planning much more difficult. Although methods based on convex optimization work well for problems with three degrees of freedom, like planetary landing, their use in integrated operations with six degrees of freedom is limited by constraints that are not convex. To solve this problem, this paper proposes a new framework for servicing spacecraft using sequential convex programming. The primary contribution is the extension of convex methods to high dimensional trajectory planning while adding a robust trust region constraint based on trajectory deviation. This mechanism reduces the chance of finding no solution during convex approximations. It improves reliability and convergence when solving complex problems. The approach first creates a continuous optimal control problem with an index that balances energy use and the angle of the line of sight. Nonlinear dynamics are simplified using first order Taylor expansions. Constraints for the field of view and collision avoidance are modeled using spherical and ellipsoidal regions. The non convex problem is changed into a sequence of discrete convex subproblems and solved through iterations. Numerical simulations show that the servicing spacecraft can safely approach the target with stable attitude while meeting all physical limits. The method using sequential convex programming with a trust region demonstrates great potential in optimizing computational efficiency alongside strong numerical stability, laying a solid foundation for future real-time autonomous trajectory generation in complex orbital environments.
Wang, Yuzhi, Yao, Zihao, Wang, Qian, Han, Ziwen, Zhang, Chao, Zhang, Yumei, Li, Shunli
A Spacecraft Targeting Method Based on 3D Imaging and Point Cloud Alignment2026-99-230110/30/2026
Spacecraft are now required to possess all-weather, zero-window, and support-independent launch capabilities. Consequently, research on spacecraft targeting must continue to focus on improving convenience and efficiency. In this paper, a spacecraft targeting method based on point cloud alignment is proposed. Firstly, external Triple Self-targeting Inertial Measurement Units are utilized to complete self-targeting. Secondly, the 3D point cloud of the spacecraft is obtained by binocular imaging technology, and an attitude transformation matrix is obtained by aligning the measured point cloud with the standard point cloud. Finally, the installation relationships between the binocular camera and the Triple Self-targeting Inertial Measurement Units, as well as between the guidance system and the spacecraft body, are determined. Combining these installation relationships with the attitude transformation matrix, the targeting results from the Triple Self-targeting Inertial Measurement Units are transferred to the spacecraft guidance system. In the simulation experiment, the maximum standard deviation of the three directions after multiple targetings is 9′9″, which can meet the requirements of spacecraft targeting. The method proposed in this paper fully retains the self-targeting advantages of the Triple Self-targeting Inertial Measurement Units without external support, while making spacecraft targeting more flexible and rapid. If applied to actual equipment, it will effectively enhance the adaptability of spacecraft equipment to environments.
Wu, Bingjie, Wang, Xiaozi, Zhang, Wei, Li, Mingrun
Target Positioning Method for Unmanned Aerial Vehicle Tracking Based on Beidou2026-99-235310/30/2026
In order to support successful tracking and monitoring tasks in different environments, drones need to quickly and accurately identify targets. This paper studies a drone combat target positioning method, with a focus on the BeiDou satellite navigation system and its performance under different environmental conditions. A complete system has been designed, including flight control system, environmental sensors, data transmission and processing system, aiming to achieve precise positioning and target tracking of unmanned aerial vehicles. This paper uses on-site testing to explain the coverage range and stability positioning accuracy of ranging signals in different environments. Experimental data shows that the BDS system has good positioning error performance for unmanned aerial vehicles, with an average error of 46.52 cm. BDS positioning time is usually short, with a maximum positioning time of 780ms and a minimum positioning time of 224ms. However, the BDS system still needs improvement in terms of dynamic environmental adaptability, multi-target tracking, anti-interference ability, and adaptability to harsh environmental conditions. Future work will focus on algorithm optimization, hardware technology improvement, and data security to enhance system performance.
Tao, Zhiping, Zhang, Chenghao, Hou, Bo, Song, Juan, Yuan, Peng, Liu, Xianyang
Optimization Method for UAV Scheduling Based on Beidou2026-99-235210/30/2026
Currently, UAVs are increasingly used in remote sensing monitoring, logistics and distribution, emergency rescue and recreational aerial photography, etc., which puts higher requirements on wireless networks, i.e., how to allocate limited wireless resources in real-time, efficiently and fairly to ensure that a large number of UAVs can work together in complex environments and maintain high-quality communication services. This paper investigates an optimisation method for UAV scheduling based on the BeiDou satellite navigation system, which improves the accuracy and efficiency of UAV mission execution by utilising the high-precision positioning and time synchronisation services provided by the BeiDou system. The results of the experiment showed that as the number of missions increased from 10 to 50, the average mission completion time increased from 8.3 to 12.5 minutes, the average speed increased from 30 to 34 km/h, the average energy consumption increased from 0.8 to 1.2 kWh, the average distance flown increased from 12 to 22 km, the communication success rate decreased slightly from 99.2 to 98.2%, the resource utilization rate increased from 85.1% to 87.5%. These results show that the method performs well in terms of task completion time, energy consumption, communication success rate and resource utilisation, which provides strong support for the application of UAVs in the fields of logistics and distribution, emergency rescue, and so on.
Ji, Hongbin, Jiang, Kexin, Zhang, Dongxue, Bai, Yanhui, Liu, He, Zhang, Shuangna
PINNs-Based Parameter Estimation for Gradient Descent2026-99-230310/30/2026
To address the joint estimation of state and parameters for fixed-wing aircraft in wind gradient environments, this paper proposes a high-precision identification method based on a physics-informed neural network. By integrating wind gradient models with flight dynamics equations, a multi-objective optimization framework combining data-driven approaches with physical constraints is established. Employing polynomial time embedding and a dual-branch network architecture, coupled with a dynamic training strategy, simultaneous estimation of flight state and wind gradient parameters is achieved. Experimental results demonstrate that this method achieves approximately 7% parameter estimation error while accurately reconstructing unobserved attitude information. Requiring only four-dimensional observation data, this approach provides an effective solution for wind gradient glide navigation in low-cost aircraft.
Wu, Ting, Bai, Zhuoyue, Gao, Xianzhong
Noise Analysis and Circuit Optimization for the Drive Loop of Resonant Accelerometers2026-99-296710/19/2026
Resonant MEMS accelerometers are core inertial devices in precision measurement fields such as inertial navigation, aerospace, and seismic monitoring, characterized by frequency signal output, strong anti-interference capability, and high-precision potential. With the growing demand for sub-microg-level measurement accuracy in high-end industrial and scientific applications, noise suppression and detection sensitivity optimization have become key research topics for resonant accelerometers. This paper conducts a systematic modeling study on resonant accelerometers, analyzes their mechanical structure and acceleration sensing mechanism based on the force-frequency effect of double-ended tuning forks, and establishes corresponding mathematical models. Non-ideal noise models of the mechanical structure and drive loop are constructed separately, and key noise source analysis identifies mechanical thermal noise and 1/f noise of the front-end charge amplifier as the main contributors to system noise. To solve these problems, a dedicated low-noise charge amplifier is designed for the drive loop. Simulation results show that the input-referred noise of the low-noise operational amplifier used in the charge amplifier reaches 18.804 nV/√Hz @ 50 kHz. When applied to the drive loop and verified through tape-out testing, the system achieves a phase noise better than -119.904 dBc/Hz @ 20 Hz offset from the resonant frequency, with a corresponding acceleration noise density of approximately 0.477 μg/√Hz @ 20 Hz.
Cai, Hebin, Li, Zhaohan, Zhang, Qiukun, Liu, Guowen, Zhang, Wenbo, Yin, Liang, Gao, Naikun, Fu, Qiang
Magnetometer Temperature Compensation of Geomagnetic Directional Technology2026-99-295710/19/2026
Accurate compensation of magnetic measurement errors is one of the key factors in ensuring the accuracy of geomagnetic navigation. Magnetic sensors are susceptible to temperature drift during use due to the disturbance of external ambient temperature, which affects the accuracy of magnetic field measurement. To improve the precision of the tri-axis geomagnetic sensor, a suitable thermal error compensation algorithm must be designed to process measured data correctly. Thus, a temperature compensation model and a high-precision geomagnetic directional technology were proposed in this paper. Firstly, a tri-axis geomagnetic sensor temperature compensation model based on particle swarm optimization-least squares support vector machines (PSO-LSSVM) was established. Then the inertial measurement unit (IMU) data is processed with zero drift correction and filtering. Finally, geomagnetic directional experiments were conducted with the gradient descent method. The experimental results show that the proposed temperature error compensation method can effectively alleviate the impact of thermal variations on the detector output and enhance the precision of the geomagnetic orientation system. It is expected to be applied to multiple navigations, aviation, and aerospace fields.
Fan, Chenyu, Guan, Feng, Liang, Zhuo, Zhang, Haifeng
Research on Multi-Source Navigation Information Fusion Based on Adaptive Weighted Least Squares Algorithm Considering Signal Quality and Geometric Distribution2026-99-296010/19/2026
With the extensive application of satellite navigation technology in intelligent transportation and aerospace fields, the fusion of multi-source navigation information has become a key approach to solving the problem of high-precision positioning in complex environments. To address the issues of single weighting and insufficient robustness in traditional weighted least squares (WLS) algorithms for multi-source navigation information fusion in complex environments, this paper proposes an adaptive weighted least squares (AQG-WLS) algorithm based on signal quality and geometric distribution. This algorithm dynamically adjusts the weights of observations by constructing a composite weight model that integrates the carrier-to-noise ratio and the spherical geometric distribution of satellites. On the one hand, it uses the carrier-to-noise ratio to reflect the level of observation noise corresponding to signal strength. On the other hand, it introduces the area of spherical quadrilaterals to quantify the correlation of satellite geometric configuration, thereby avoiding the deterioration of the geometric dilution of precision (GDOP) caused by satellite clustering. Experimental results show that in scenarios with obstructions such as urban canyons, the AQG-WLS algorithm improves positioning accuracy by approximately 23% compared to the traditional WLS algorithm, and demonstrates stronger robustness against multi path effects and gross errors, providing an effective parameter estimation method for multi-source navigation fusion.
Zhu, Shengling
LASERAgent: Toward Highly Automated and Reliable Reproduction of LEO Networking Experiments2026-99-299110/19/2026
It is still difficult to reproduce the low-Earth-orbit (LEO) networking experiments since the experimental settings are scattered and the Large Language Model (LLM) assisted workflow is laborious and needs to be refined by manually crafting the prompt, transferring the code and debugging. Existing retrieval-assisted pipelines still demand substantial human effort for parameter inference and code repair, particularly given the precise alignment required for LEO topology, constellation, and simulator configurations. This paper presents LASERAgent, a highly automated agent system for LEO networking experiment reproduction. Unlike retrieval-assisted pipelines that mainly support evidence retrieval and code generation, LASERAgent organizes the downstream workflow into a bounded pipeline of retrieve - extract - generate - check - execute, integrating structured parameter extraction, template-guided generation, deterministic validation, controlled execution, and limited retry. Preliminary results show that LASERAgent reduces required human interventions by roughly half while improving result consistency over prior retrieval-assisted workflows, and that the validation stage plays an important role in reliable automation.
Tian, Siyu, Wei, Guangyu, He, Xiongwen, Liu, Donghua, Ma, Yue, Zhan, Yuheng, Xia, Lang
Quantifying the Accuracy of Reporting the Onset of Lateral Movement for a Selection of Bicycle Global Positioning System Computers2026-01-507810/1/2026
Bicycle computers and apps record, at minimum, positional data over time, and these data are commonly used in accident reconstruction to understand the behavior of the bicycle and rider prior to an incident in question. These positional data are obtained using the Global Positioning System (GPS), and while their absolute positional accuracy has been the subject of prior research, their accuracy at detecting and reporting particular movements is less studied. To improve the accident reconstruction industry’s understanding of these devices’ performance, this research aims to statistically quantify the temporal and positional accuracy of these devices reporting the onset of a lateral deviation or lane change. Controlled testing was performed and recorded with several commercially available bicycle GPS computers and apps, which were compared to a RaceLogic VBox 3i ADAS with Real-Time Kinematics (RTK) corrections from a RaceLogic Base Station. Three separate test bouts were performed, with each test bout consisting of 30 or 32 repeats of three different lateral deviation maneuvers. The bicycle GPS computers were individually synchronized to the RaceLogic data by offsetting their time to minimize the mean-square positional error across the entire test bout, which enabled calculation of the 50th percentile and 95th percentile absolute positional errors for each device. A custom script was then used to programmatically detect the start of each lateral deviation, and then, confidence intervals were calculated to estimate the probability of each GPS device reporting the start of the lateral deviation with zero lead or lag, with 1 s of lag, or with 0 or 1 s of lag based on the relative timestamps and positional data. All three of the tested bicycle GPS computers had a probability of at least 0.5 of reporting the onset of sharp lateral movements with zero lead or lag based on the time data, while only two of the devices maintained a similarly high probability for the position-based data. The iPhone 17 Pro had a probability greater than 0.6 of detecting the onset of both gradual and sharp lateral movements with 1 s of lag for both the time-based and position-based data. And across all lateral movement types, all devices had a probability of at least 0.6 of reporting the onset of lateral movement with either 0 or 1 s of lag.
Sweet, David Michael, Bretting, Gerald, Wilhelm, Chris, O’Brien, Nathan
Hybridnav: A Hybrid Approach to Zero-Shot Object Detection with Adaptive Exploration for Autonomous Reconnaissance2026-01-75179/22/2026
Autonomous reconnaissance in unknown or contested environments demands robust perception systems capable of identifying diverse objects without prior training data. This paper presents HybridNAV, a hybrid framework that combines multiple foundation models with an adaptive navigation system for zero-shot object detection and autonomous exploration. Unlike monolithic detection models, HybridNAV’s multi-model fusion achieves balanced precision (0.60) and recall (0.58) with a macro F-score of 0.59, representing a 24% improvement over single-model baselines. The adaptive navigation system reduces scan time by 25% and path length by 30% compared to static waypoint approaches, while operating in real-time at 3.2 Hz with sub-100 msec latency on resource-constrained hardware. All processing is performed locally on the robotic platform, eliminating reliance on external communication infrastructure—a critical requirement for operations in communication-denied environments. We evaluate HybridNAV in both simulated indoor scenes and physical robot trials, demonstrating its effectiveness for intelligence gathering in unknown environments.
Indurthi, Hemanth, Martinson, Eric
Development of a UAV Platform for Remote Inspection and Visualization2026-01-75119/22/2026
This paper details the development of an intelligence and inspection platform consisting of an attritable sub-250g UAV, a ground control station, and a visualization interface for users. The UAV architecture combines onboard obstacle detection and avoidance along with simultaneous localization and mapping to have full autonomous navigation inside of complicated GPS-denied environments. The ROS 2-to-Unreal Engine data pipeline allows for sensor fusion, data cleansing, and initial analysis as well as creation of a high-fidelity real-time 3D digital twin. The visualization interface allows users to easily identify critical features and turn data into intelligence to support decision making by soldiers and first responders.
Lee, Yeen K., Bainard, Sean, Shaughnessy, Michael, Bolger, Matt, Koepp, R. Tucker, Salehzadeh, Roya, Mallory, Stephen, Mynderse, James A., Guillen, Pedro, Hernandez, Margarita
Current Situation of Ship Navigation and Research on the Route Reform Scheme in Typical Tributary-Confluence Waters of the Lower Yangtze River2026-99-15729/11/2026
The thalweg at the outlet of the Yuxikou Waterway transitions from right to left, forming a 90-degree bend. It then merges with the Xihua Waterway after passing Xiliang Mountain, creating a main-branch confluence water area. Taking a typical main-branch confluence water area in the lower reaches of the Yangtze River as the research object, this paper reflects the current navigation status and existing problems of ships in the area through the analysis of ship traffic flow. It classifies the risk levels of passing ships, proposes suggestions for route reform and optimization, and uses a model to verify the probability of collision accidents in the area after the implementation of the round-island navigation method, providing a reference for the navigation safety of passing ships.
Liu, Ka, Xu, Yerong
Dimensional Adaptability and Traffic Organization Analysis of Ships in Group Lockage2026-99-15109/11/2026
Aiming at the technology of electric intelligent working boat towing 4 ships in group lockage during the construction period of the Gezhouba Shipping Capacity Expansion Project, this paper, starting from ship dimensions, conducts an adaptability analysis on electric intelligent working boat towing ships in group lockage for all ships passing through Gezhouba No. 1 and No. 2 Ship Locks throughout 2024, based on the two-dimensional packing model, ship lock chamber scheduling model and algorithms, navigation scheduling rules and safety management regulations, the results show that ships unsuitable for being towed in group lockage through Gezhouba No. 1 Ship Lock account for approximately 26% of the total number of ships passing through it, while those unsuitable for being towed in group lockage through Gezhouba No. 2 Ship Lock account for approximately 57% of its total passing ships. Meanwhile, ships passing through the three Gezhouba ship locks on a specific day are selected, and an adaptability analysis on the dimensional suitability of electric intelligent working boat towing these ships in group lockage is carried out under the scenario where these ships only pass through Gezhouba No. 1 and No. 2 Ship Locks. The results show that the number of ships with suitable dimensions for group lockage accounts for the majority of the ships passing through the locks on a selected specific day. On this basis, combined with the operation modes of Gezhouba No. 1 and No. 2 Ship Locks, an analysis is carried out on the traffic organization, potential risks, corresponding countermeasures, and the required quantity of electric intelligent working boats for towing ships in group lockage, targeting the three main collaborative operation modes. The results can provide a basis for the future practical application of electric intelligent working boat towing ships in group lockage during the construction and operation periods of the Gezhouba Shipping Capacity Expansion Project.
Huang, Shaowen, Yang, Xi, Wang, Jian
Safety Analysis of Collision Avoidance for Semi-Autonomous Navigation Ship Based on STPA-CREAM2026-99-15549/11/2026
With the continuous improvement of ship intelligence, more intelligent onboard navigation equipment and intelligent navigation systems are used to assist in improving navigation efficiency. This study takes semi-autonomous navigation ships as research objects and adopts System-Theoretic Process Analysis (STPA) to model the complex interaction relationships of semi-autonomous navigation encounter scenarios and identify and analyze potential risks. To address the deficiency of STPA in human factors analysis capability, the Cognitive Reliability and Error Analysis Method (CREAM) is introduced to analyze human factors in semi-autonomous navigation. Finally, based on the results of the STPA-CREAM analysis, recommendations are provided to improve the safety of semi-autonomous navigation.
Zhang, Xiaojie
Exploration of the Minimum Safe Transverse Distance for Ships Passing Through the Pier of Huangpu River Tidal Barrier Based on the Boundary Element Method2026-99-15469/11/2026
The Huangpu River tidal barrage is in a navigable reach where the quay wall greatly restrains the flow. Earlier studies focused on ship-structure interaction, but there aren’t many hard numbers on safe passing distance near the barrage pier. The purpose of this paper is to determine the lowest safe lateral gap for large vessels and to provide an engineering means of ascertaining the clear width of the main channel. A 20,000-ton oil tanker is used as the test vessel. Using the boundary element method (BEM), a 3D model is constructed to simulate the interactions between the ship and the pier under varying speeds, draft depths, and lateral offsets. Simulations were conducted for different speed levels, draft depths, and lateral offsets to observe the flow and the ship’s movement. Changes in side forces, yawing moments, and bow angles were recorded over time, and their maximum values were determined. Sensitivity and uncertainty analyses were also performed to evaluate how input variations affect the results and to assess model stability. Based on these results, simple limits were established for the three measures to serve as safety rules. Using these rules, the clear width of the main channel was calculated. The results indicate a minimum safe lateral distance of 14 m and a suggested channel width of 202 m, deviating by only 0.5 m, or approximately 0.25%, from the theoretical value of 202.5 m. These findings can also be applied in practice for pier layout and the determination of speed limits in narrow channels.
Guan, Keping, Yu, Min, Zhan, Qingan
Fault Detection and Isolation Method for BDS/GPS Hybrid Constellation Oriented to Airworthiness Retrofit2026-99-14159/11/2026
This work deals with the topic of integrating a multi-GNSS solution within existing avionics, specifically concentrating on airworthiness approval issues, thereby addressing risks associated with susceptibility in standalone GPS solutions. An older aircraft, still relying on existing GPS solutions, remains susceptible to jamming, spoofing, or single-point failures, which, in turn, pose risks associated with integrity requirements necessary for ADS-B or TAWS operation. An approach for a fault detection and isolation (FDI) scheme applicable to a BDS/GPS hybrid satellite system configuration suitable for airworthiness projects would thus be relevant. A transparent proxy architecture is proposed, which consists of a form-fit GPS/BDS dual-mode antenna replacement and an RF power splitter. This design makes it possible to provide BeiDou Navigation Satellite System (BDS) signals with neither changes in the interfaces nor structural changes being required to existing flight management systems. It includes a signal processing module that combines adaptive quality weighting on carrier-to-noise ratios, satellite elevation angles, and code-minus-carrier differences, as well as a carrier phase smoothing process via the Hatch filter. A multiple-channel approach in a parallel position system is designed, with different channels for GPS-only, BDS-only, as well as hybrid solutions, with weighted least squares estimation incorporating the Huber robust reweighting rule, along with Receiver Autonomous Integrity Monitoring (RAIM) with fault detection and exemption in every channel. A cross-constellation integrity monitoring algorithm is presented for the purpose of identifying constellation-level spoofing attacks that evade conventional single-system RAIM integrity. Simulation results, carried out for four different interference levels, show that the hybrid channel provides a 34% improvement in horizontal positioning accuracy compared with the GPS-only mode of operation. The cross-check method is able to effectively detect GPS spoofing attacks with position divergence exceeding 50m within a detection time of 25 seconds, along with a navigation availability of 99.9% under nominal operating conditions.
Ou, Chongjie, Zhang, Kezhi, Zhu, Haijie
Impact of Transient Driving Characteristics on Bench-to-Road Emission Consistency of Light-Duty Vehicles2026-99-15739/11/2026
The thalweg at the outlet of the Yuxikou Waterway transitions from right to left, forming a 90-degree bend. It then merges with the Xihua Waterway after passing Xiliang Mountain, creating a main-branch confluence water area. Taking a typical main-branch confluence water area in the lower reaches of the Yangtze River as the research object, this paper reflects the current navigation status and existing problems of ships in the area through the analysis of ship traffic flow. It classifies the risk levels of passing ships, proposes suggestions for route reform and optimization, and uses a model to verify the probability of collision accidents in the area after the implementation of the round-island navigation method, providing a reference for the navigation safety of passing ships.
Qiao, Jiajun, Jin, Zhenhua, Huang, Qi, Li, Guohui, Zhang, Xinguo
A Three-Dimensional Safety Domain Method for LNG Vessels in Ports Based on Human Factors and Speed Characteristics2026-99-15239/11/2026
To accurately assess the navigation safety status of LNG vessels in port waters and balance safety control with waterway capacity efficiency, this study constructs a 3D dynamic safety domain model for port LNG vessels, integrating human–ship–environment multi-factors. The model introduces the Weibull function to quantify the impact of drivers’ knowledge, skills, and physiological-psychological states on safety boundaries, combines a ship motion mathematical model to establish a 2D safety domain boundary equation, and incorporates hull subsidence to build a vertical dimension, forming a complete 3D model. Longitudinally, the safety distance is calculated using the car-following braking theory, while laterally, boundaries are determined by controlling the ratio of inter-vessel interference force to navigation resistance. Through static scenario analysis and dynamic simulation verification, results show that the safety domain scale is dominated by ship speed and environmental conditions, and its shape tends to shrink as the driver’s state improves, making it more suitable for actual port scenarios than traditional models. Verified with a specific LNG hub port as a case, the safety distance calculated by the model is significantly reduced compared with current specifications, while the delay impact rate and average delay time on other vessels are decreased. The research results establish a quantifiable framework for dynamic safety assessment, providing maritime administrations and on-board pilots with a scientifically-grounded tool to determine real-time safe navigation boundaries in complex port environments, balancing safety control with operational efficiency.
Wang, Yangang, Jia, Changsheng, Zhu, Jinshan
Research and Analysis of Civil Aircraft Radio Altimeter Malfunction2026-99-12359/4/2026
The radio altimeter is an important navigation instrument on an aircraft, capable of accurately measuring the aircraft's true height above the ground or sea to ensure safe flight. This capability is crucial for ensuring normal flight operations, especially during critical phases such as takeoff, approach, and landing. Polar terrain is complex and continually changing. The vast, endless ice fields, crisscrossing glacier crevasses, towering icebergs, and weather conditions all add significant uncertainty to air travel. In such environments, the aircraft's navigation system is particularly important as a core device to ensure flight safety. This article provides a brief overview of the aircraft radio altimeter system. Using data and observations from production flight tests, it studies the specific challenges posed by radio altimeter failures encountered during these critical validation flights. The study synthesizes these findings and proposes a relatively general troubleshooting approach to address such issues. Furthermore, the effectiveness of this method has been rigorously validated through its application in solving a complex real-world radar altimeter failure case.
Song, Mingming, Mi, Yujie
Numerical Study on Measurement Accuracy of Liquid Level/Capacity Measurement Device and System in a Shipboard Environment2026-99-01227/31/2026
In the marine environment, navigation safety and operational effectiveness depend heavily on the precision of liquid level/capacity measurement equipment and systems. In order to examine their measurement accuracy under complex operational situations, including ship navigation states and water tank sloshing, this study employed computational fluid dynamics (CFD) methodologies. The numerical technique performs a thorough examination of how various operating conditions impact measurement accuracy and integrates the volume of fluid (VOF) model and laminar flow model with appropriately defined boundary conditions and solver settings. The findings indicate that constant-speed navigation has minimal impact on accuracy, horizontal acceleration causes moderate deviations, and accelerated diving greatly reduces precision. The amplitude of water tank sloshing has a positive correlation with measurement error. When sloshing amplitudes are less than 1 m, the integration of the resulting acceleration efficiently lowers deviations while preserving excellent accuracy. In light of these results, we advise adding accelerometers to differential pressure transmitters to improve measurement precision. This investigation provides data-driven references and technical solutions for system design and operational standard formulation in marine measurement systems.
Shang, Jin, Qin, Ziming, Wang, Yingwei, Wu, Chao, Zhao, Fenggang, Chen, Liang, Xia, Wei, Yan, Jin, Chen, Min, Chen, Guoao
Attention and Intrinsic Curiosity-Enhanced Deep Reinforcement Learning for Path Planning in Dynamic Environments2026-01-50567/31/2026
Efficient and reliable path planning remains a core challenge for autonomous vehicles operating in dynamic and crowded environments. Although Deep Reinforcement Learning (DRL) has shown considerable potential in autonomous decision-making, it still faces challenges such as insufficient feature extraction, sparse rewards, and low obstacle avoidance efficiency in complex scenarios. To address these issues, this paper proposes an end-to-end path planning framework, PPO-ICM-Attn. Built upon the Proximal Policy Optimization (PPO) algorithm, the framework incorporates a dual-channel attention convolutional neural network module (Attention-CNN) to enhance spatial and semantic understanding of dynamic obstacles, and introduces an Intrinsic Curiosity Module (ICM) to promote active exploration in sparse-reward settings. Furthermore, a reactive avoidance reward function based on velocity-obstacle theory is designed and embedded to achieve real-time proactive collision avoidance in highly dynamic environments. Experiments are conducted in a semi-structured dynamic crowd scenario constructed on the GAZEBO simulation platform. The results demonstrate that PPO-ICM-Attn achieves significant improvements in key metrics such as path success rate, travel time, and path efficiency compared to baseline methods like A*+DWA and standard DRL. Although the gap remains in path efficiency compared to A*+DWA, the proposed method exhibits superior robustness and navigation performance overall, validating its effectiveness in complex dynamic environments.
Shen, Shiquan, Liu, Jiahao, Chen, Zheng, Li, Zongdian, Zhao, Yuting, Wu, Minggong, Zhao, Jie, Qin, Zongquan, Wang, Yanfeng
Durability Study of Electronic-grade Glass Fibers in Salt-Alkali Environments2026-99-02197/31/2026
Electronic substrates and copper-clad laminates are widely used in modern life, particularly in electronic products such as coastal communication base stations and ship communication and navigation system. In these environments, salt particles carried by sea fog can adhere to the surface of the substrates along with moisture, leading to salt-alkali corrosion of the products. As a core material in electronic components, electronic-grade glass fiber urgently requires investigation into its durability under salt-alkali conditions. Therefore, this study focuses on a specific type of electronic-grade glass fiber and explores its corrosion behavior in three different environments: 2 mol/L NaOH, 1 mol/L cement solution, and 3.5 % NaCl. Soaking durations of 6, 12, 24 hours and 3, 7, and 14days were selected as key parameters. The mechanical properties and surface morphology of the fibers before and after corrosion were observed and analyzed. Experimental results indicate that the glass fiber exhibits higher durability in saline solutions than in alkaline environments. This study provides theoretical support for evaluating the long-term performance of Electronic grade glass fibers in practical applications. It also contributes to the optimization of raw materials and manufacturing processes, enhancing the performance of such fibers in salt-alkali conditions, and offers valuable reference for future research on glass fiber-reinforced composites.
Pu, Qixin, Sun, Siqi, Fang, Qiang, Dong, Shuo, Li, Peng, Wang, Yu, Zhang, Mengxuan, Zhang, Yubo, Yang, Wenfeng, Guo, Peng
Simulation and Experimental Evaluation of a Vehicle–Road Cooperative Positioning Method in Global Navigation Satellite Systems (GNSS)-Denied Environments12-09-04-00297/29/2026
In complex urban environments, vehicle positioning based on Global Navigation Satellite Systems (GNSS) is prone to failure or accuracy degradation due to signal blockage and multipath effects. To address this issue, this article proposes a vehicle–road cooperative positioning method based on factor graph optimization for GNSS-denied environments and evaluates its performance through both simulation and real-vehicle experiments. In the proposed approach, road codes deployed on the road surface serve as absolute position references on the road surface, and high-precision vehicle position estimates are obtained in real time by fusing roadside positioning information with onboard sensor measurements using factor graph optimization. Furthermore, to reduce the experimental cost and development cycle of the vehicle–road cooperative positioning method, a performance simulation platform is developed based on the CARLA simulator, RoadRunner, and the CARLA-ROS (Robot Operating System) bridge for real-time communication between simulation and positioning modules. The platform supports road code generation and deployment, customized scenario construction, and positioning performance simulation, and a multi-objective optimization approach is employed to obtain an optimal deployment scheme for road code spacing. Finally, the effectiveness of the proposed vehicle–road cooperative positioning method is validated through both simulation and real-vehicle experiments. Real-vehicle experiments show that the proposed method reduces the average RMSE (Root Mean Square Error) by 26.6% compared with the ESKF (Error State Kalman Filter) baseline, achieving an RMSE of 0.25 m and a maximum error of 0.95 m at a vehicle speed of 60 km/h and a 10 m code spacing, thereby confirming decimeter-level continuous accuracy in GNSS-denied environments.
Shen, Chuanfu, Zhao, Zhiguo, Yan, Danshu, Ling, Yubin
Research on a Rocket Projectile Impact Point Prediction Model Based on Improved Proportional Navigation Guidance Law2026-99-16027/24/2026
Rocket projectiles are a type of ammunition that get their power from rocket engines. Long-range guided rockets, in particular, hold great significance as they seem to mark the way forward in modern warfare. These guided projectiles take full advantage of the considerable range that long-range rockets offer and, at the same time, manage to achieve improved accuracy. This paper delves into a model that is used for predicting the impact point of rocket projectiles, with the application of the proportional navigation guidance law. It also undertakes an analysis of both the strengths and the weaknesses of this model. Through the formulation of equations related to the dynamics of the center of mass and some other supplementary equations, a rather comprehensive trajectory equation was worked out. When this trajectory was simulated, it brought about the creation of a firing table, which is of help in predicting the initial trajectory inclination angle.
Tao, Wenwen, Wang, Ru, Zhang, Liang, Pi, Runge
2025 International Conference on Aircraft Control and Navigation Technology2026-99-18007/17/2026
TOC
Tobolski, Sue
Flight Test Methodology for Verification of Precipitation Static Protection in Civil Aircraft Radio Navigation Systems2026-99-18097/17/2026
The verification of Precipitation static (P-static) protection for the radio navigation system of civil aircraft is a critical test item for airworthiness certification. However, determining the presence of P-Static on the aircraft fuselage and assessing whether its discharge interferes with the radio navigation system remains challenging, with testing methods still under exploration. By analyzing airworthiness certification test provisions, the necessity of conducting flight tests for P-static protection verification of the radio navigation system was clarified. Based on existing conditions for civil aircraft flight tests, a comprehensive flight test method was proposed to verify the P-satic protection capability of the radio navigation system. This method includes determining external meteorological conditions, measuring electrostatic parameters, and designing aircraft maneuvers and states. The test plan was validated on a test aircraft. Discharge current data measured on a discharger indicates that during the flight of a civil aircraft through cirrus clouds, negative charge accumulated on the aircraft's surface, leading to electrostatic discharge. The maximum peak discharge current recorded was 330 μA. P-satic radiation field data were obtained near the Automatic Direction Finder (ADF) antenna; the radiation energy is primarily concentrated within the 200 MHz range, with some energy distribution still observed between 200 MHz and 500 MHz. Within the 200 MHz range, the signal amplitude exceeds the background noise, and stable peaks appear at multiple frequency points, with the maximum amplitude reaching up to 50 dBm.confirming the presence of a P-Static environment. This achieved the objective of evaluating the functional performance of the radio navigation system in an electrostatic environment, providing technical support for P-Static protection verification flight tests and offering a reference for the practical application of electrostatic protection design.
Han, Chunyong, Wang, Fusheng
Study on Resistance and Surface Pressure Characteristics of UUVs Navigating in the Pycnocline2026-99-18077/17/2026
As a critical component of unmanned naval warfare, Unmanned Underwater Vehicles (UUVs) have garnered significant attention from major military powers. When navigating through pycnoclines—a widespread vertical density stratification in marine environments—UUVs generate volume effect internal waves that influence hydrodynamic resistance. Therefore, investigating the hydrodynamic characteristics of UUVs in pycnoclines is essential. Despite substantial research progress, most studies focus on internal wave patterns and their impacts on submerged vehicles, with limited exploration of UUV resistance and surface pressure distribution. This work establishes a numerical method according to the Reynolds-Averaged Navier-Stokes (RANS) equations, employing the Realizable k-ε turbulence model and the Volume of Fluid (VOF) method to capture fluid density interfaces, thereby analyzing the hydrodynamic characteristics of UUVs in pycnoclines. Furthermore, a numerical method was constructed, and the convergence regarding the grid and time-steps were verified. Additionally, numerical experiments under varying navigation speeds and depths are conducted to investigate the total resistance, frictional resistance, wave-making resistance coefficients, and spatial variation of surface pressure. Based on the results, the total resistance of a UUV is positively correlated with its navigation speed. When navigating in the upper seawater layers, the total resistance also exhibits a positive correlation with navigation depth. However, when operating in the lower seawater layers, the total resistance initially increases and then decreases with increasing depth, reaching its peak level at a navigation depth of 13 m. Both increasing navigation speed and approaching the density interface can enhance the sensitivity of total resistance to navigation depth. The alteration in total resistance stems primarily from changes in wave-making resistance while showing a weaker correlation with frictional resistance. The UUV’s speed positively correlates with pressure at locations with abrupt curvature changes on its surface, but it has a negligible influence on pressure distribution in smooth surface regions. Besides, navigation depth positively correlates with surface pressure magnitude yet exerts a limited impact on pressure distribution patterns. The findings contribute to a more complete picture of the hydrodynamic properties of UUVs navigating through pycnoclines, offering valuable references for optimizing UUV design and operational strategies.
Zhang, Yin, Xue, Leilei, Guo, Liqiang, Fu, Xiao, Zhang, Xiaofang, Liu, Zhihao, Han, Guoxin
Few-Shot Semantic Segmentation Method for Crater Detection on Small Bodies2026-99-18527/17/2026
Craters are the primary landmarks used for visual navigation in missions exploring small celestial bodies. However, obtaining high-quality, annotated crater data is often challenging due to limited imaging conditions and strict mission constraints. Conventional semantic segmentation models struggle with limited data and are challenging to train effectively. To overcome this limitation, this study introduces a few-shot segmentation approach for crater detection on small celestial bodies. Our method includes a prototype representation module that constructs class-level prototypes to quickly associate crater regions with their semantic features. This paper also designs an iterative learning module that gradually improves the segmentation output, helping the model better capture detailed edges and structures. Tests on a simulated few-shot dataset demonstrate that our method provides reliable and accurate crater segmentation, achieving a mean intersection-over-union (mIoU) of 88.7, outperforming traditional fully supervised methods.
Li, Shuai, Zhu, Shengying
Research on Deep Learning Navigation Algorithms for Helicopter Airborne Navigation2026-99-18647/17/2026
It is very hard to position helicopters in complex environments, and this severely limits their ability to navigate on their own. This paper proposes a navigation algorithm that uses a combination of different sensors and deep learning. It uses a special type of deep learning called ResNet50 and a special type of machine learning called LSTM. This algorithm extracts features of the environment and uses a Kalman filter to estimate the state of the system. The system is made more robust by merging information from multiple levels. The algorithm’s ability to maintain stable navigation in the face of faulty sensors is noteworthy, as is its use of an adaptive inference strategy that dynamically adjusts computational load. This strategy strikes a balance between performance and resource consumption. Experiments show that the plan works well in places where GPS is not available. This makes it much better for the helicopter to fly by itself, and it can be used in places like the army, for looking at places from the sky, and for helping people in danger.
Yang, Ming
Multi-Frame Centroid Extraction Method for Optical Navigation During the Approach Phase of Small Body2026-99-18517/17/2026
Autonomous optical navigation is one of the important navigation methods for the small bodies approach phase. To improve optical navigation performance during the approach phase to a small body, this paper presents a method for extracting the target centroid from sequential optical images. The process begins with fitting a minimum enclosing ellipse to the detected contours in each frame to obtain an initial estimate of the centroid. Building upon this, edge corner points across adjacent images are matched using normalized cross-correlation, and their displacement is tracked using optical flow techniques. The observed pixel trajectories are analyzed, and a predictive model of pixel motion is formulated based on the geometric relationship between the detector and the small body. By combining the directly extracted centroids with the predicted motion of key pixels, a fusion strategy is developed to improve the reliability of the centroid estimation. Finally, numerical simulation results demonstrate that the method significantly improves the accuracy of centroid extraction, thereby enhancing the overall performance of optical navigation during approach operations.
Liu, Jing, Zhu, Shengying
Research on Clustering Data-Driven Intelligent Perception Algorithm for Micro Mobile Robots2026-99-18437/17/2026
To address the challenges faced by micro flapping-wing flying robots in visual navigation—specifically, the large volume of visual information and the difficulty in transforming it into usable intelligent visual data—this paper proposes a clustering-based data-driven approach for directional and image perception. The aim is to enable intelligent visual navigation for flapping-wing robots. The proposed method performs clustering analysis on gyroscope data from the flapping-wing robot to extract directional features. Simultaneously, it applies clustering techniques to visual images captured by the robot to identify intelligent features such as edges. This approach enables the robot to acquire multiple optimized perceptual data types, thereby enhancing the behavior control system. Through the use of clustering analysis, the method not only improves the effectiveness of visual navigation but also extracts features related to visual targets and environmental information, providing technical support for visual target tracking. The experimental platform consists of a flapping-wing robot equipped with an onboard camera, and the proposed clustering-driven visual image perception approach has been experimentally validated. Experimental results demonstrate the high feasibility and effectiveness of the method in practical applications. The main contributions of this study lie in two aspects: (1) a clustering-driven visual image perception method for flapping-wing robots, and (2) a clustering-based approach for identifying posture and behavioral patterns of flapping-wing flying robots.
Li, Zixuan, Ding, Wei, Zhang, Feng, Song, Min, Liu, Zhaoming, Miao, Lei, Liu, Haotian, Bai, Ning, Tian, Shen, Cui, Long, Wang, Hongwei
A Map-free Geomagnetic Navigation Method Based on the World Geomagnetic Model Position Estimation with a Fully Connected Neural Network2026-99-18557/17/2026
In map-free geomagnetic navigation conditions, the traditional matching algorithms will be ineffective, and the regular position searching optimization algorithms still face the problems of low navigation accuracy and inefficiency. How to further improve the accuracy and efficiency of the algorithm has become the key to the application of this method in maple’s geomagnetic navigation conditions. Based on the above background, this paper proposes an evolutionary gradient search navigation algorithm optimized via position estimation (PE-EGA). The world geomagnetic model (WMM) is used to establish the nonlinear correlation relationship between geographic position and geomagnetic features, and the inverse mapping of the geomagnetic model is fitted by a fully connected neural network to get the rough estimation of the geographic position of the vehicle, with a root mean square error (RMSE) of 0.0121 in position estimation. Finally, the information of the rough estimation is used to assist the decision-making of the navigational azimuth angle involved in the EGA algorithm. The simulation results show that the offset distance of the improved algorithm is only 27.09 m, and the path ratio reaches 1.0178 with an error ratio of 0.38%. Comparative study using measured geomagnetic data of Boao town with model data shows that the final offset distance is only 51.63 m, path ratio 1.0036, and error ratio 0.73%, which significantly improves the accuracy and timeliness of navigation compared to the original EGA algorithm. This article provides an innovative and practical solution strategy for map-free geomagnetic navigation.
Xie, Wenbin, Liu, Hongjie, Zheng, Ruifan, Ren, Xintian, Yan, Bing, Qiu, Wei, Chen, Zhuo
The Terminal Guidance Method Improved Based on BP Neural Network2026-99-18227/17/2026
Terminal guidance is critical for ensuring strike precision in the final phase of flight. However, traditional methods, such as proportional navigation and optimal guidance laws, face significant challenges regarding real-time performance and adaptability to dynamic targets. To address these issues, neural networks offer a promising solution by enabling adaptive adjustments to guidance parameters, thereby improving performance under various constraints.
Ma, Hengwei, Wang, Yongfeng, Wen, Hong, Liu, Di, Wei, Yuanhang, Dong, Longhao, Luo, Ying
Aircraft Optoelectronic Payload Transfer Alignment and Dynamic Error Compensation Algorithm Research2026-99-18497/17/2026
This paper proposes a multi-source dynamic error compensation algorithm for the transfer alignment of airborne optoelectronic payloads. This method addresses performance limitations of micro-inertial navigation systems (micro-INS) in complex dynamic environments, specifically those arising from accumulated device noise and the inability to perform static alignment due to installation errors. The algorithm’s core is the Extended Kalman Filter (EKF) technology. By constructing a “velocity + attitude” matching model between the UAV’s master inertial navigation system (MINS) and the optoelectronic payload’s slave inertial navigation system (SINS), it leverages high-precision MINS navigation information to correct SINS errors. Utilizing a 21-dimensional state space equation and measurement equation, the algorithm achieves real-time estimation and compensation of various errors, including attitude misalignment angles, sensor biases, installation errors, and flexure deformation. Simulation results demonstrate significant alignment accuracy improvement. Post-lever arm effect compensation, velocity errors are stably controlled within 0.01 m/s. Concurrently, flexure deformation angle compensation substantially reduces misalignment angle fluctuations across all directions, enhancing system stability and maintaining low misalignment angles. These findings validate the proposed error compensation strategy’s effectiveness.
Zhang, Lu, Li, Mao, Wang, Shiyong, Lei, Chao
Analysis of Quadrotor UAV Position Accuracy Based on EKF Multi-Sensor Data Fusion2026-99-18597/17/2026
When quadrotor unmanned aerial vehicles (UAVs) operate in urban low-altitude airspace, especially within complex environments, their sensor perception signals are highly susceptible to blockages, deviations, and the inclusion of high-frequency noise. These factors, in turn, induce nonlinear variations in the UAVs’ flight mechanical properties, giving rise to abnormal flight stability issues such as attitude jitter, altitude fluctuations, and trajectory deviations. To address these challenges, this paper puts forward a method aimed at enhancing the positional accuracy of quadrotor UAVs, which is based on Extended Kalman Filter (EKF) multi-sensor fusion. In conjunction with the redundant configuration of sensors, a proportional-integral controller is specifically designed to allow optical flow sensors to compensate for the speed data generated by inertial sensors. Building on the EKF method, a comprehensive data fusion model is established, encompassing both position and speed states. Leveraging the MATLAB platform, trajectory flight simulations are conducted, utilizing multi-sensor data fused via EKF, with the sensor suite including GPS, IMU, Optical Flow sensors, and Barometers. The simulation results demonstrate that this proposed method can effectively mitigate the adverse impacts of environmental interference and sensor noise on the positional accuracy of quadrotors. By continuously correcting position information and accurately estimating position states, it significantly improves the UAVs’ flight position accuracy. This research outcome lays a robust and theoretically sound foundation for in-depth investigations on critical issues related to general aviation applications, such as the safe and efficient autonomous flight, adaptive and reliable intelligent navigation, and ultra-precise and mission-critical operations of quadrotor UAVs, thereby significantly contributing to the sustained and innovative advancement of the field.
Cui, Nan, Liu, Wenzhi, Liu, Hanqi, Wang, Jingrui, Wang, Zhizhong, Zhi, Haonan
Asteroid Landing Navigation Based on Invariant Extended Kalman Filter2026-99-18567/17/2026
Optical navigation serves as a critical modality for autonomous guidance during small celestial body landing missions. To address the inherent strong nonlinearities in both the lander’s dynamic model and optical observation model, this paper investigates an invariant extended Kalman filter algorithm based on Lie group structures. First, we establish the state model and optical observation model on the special Euclidean group. Subsequently, a linearized right-invariant error dynamics equation is derived using invariance theory, along with the formulation of state prediction models. Furthermore, the feature vector observation model is modified into a right-invariant observation form, enabling state correction through exponential mapping of innovation vectors. Numerical simulations using asteroid Eros 433 demonstrate that the proposed invariant extended Kalman filter (InEKF) outperforms the conventional extended Kalman filter (EKF) in both estimation accuracy and convergence speed. Notably, the algorithm eliminates the need for online Jacobian matrix computations, satisfying the stringent navigation requirements for autonomous landing operations. The results validate the effectiveness of Lie group-based filtering in handling the nonlinear geometry of pose estimation for irregular celestial bodies.
Liu, Zhengdong, ZHU, Shengying
Path Planning Algorithm for Self-Driving Cars Based on High-Precision Maps and Improved A*2026-99-05887/10/2026
To address the limitations of the traditional A* algorithm in lane-level navigation, we propose an autonomous vehicle path planning algorithm based on high-precision maps and an improved A* algorithm to ensure effective application in complex traffic environments. We construct a hierarchical high-precision map based on the Lanelet2 framework to achieve structured modeling of complex road environments. To address the adaptability issues of the A* algorithm in lane-level navigation, we propose optimization schemes, including heuristic function improvements, path segment division, and target point validity verification, to ensure that vehicles can autonomously change lanes on multi-lane roads. By combining dynamic programming (DP) and quadratic programming (QP), we ensure the safety and smoothness of the path. Simulation results demonstrate that the optimized algorithm enables smooth stopping and starting at traffic lights in structured road environments and autonomous lane changes on multi-lane roads. Compared to using DP alone, QP provides smoother and safer driving paths and exhibits superior obstacle avoidance performance in speed planning. This method effectively ensures the rationality of path planning in complex road environments while strictly adhering to traffic rules, thereby enhancing the safety and reliability of path planning.
Wang, Siyu, Zhou, Rong, Shi, Tian, Xu, Zhen, Zhao, Zhiguo
Temperature Influence Analysis and Compensation Method of Hemisphere Resonator Gyroscope2026-99-05147/10/2026
Hemisphere resonant gyroscope (HRG) is a new type of vibration gyroscope with high precision, high reliability, and long lifespan. Improving the temperature stability of a hemispherical resonant gyroscope (HRG) has profound implications for navigation and guidance systems as well as airborne sensor technology. By optimizing temperature compensation algorithms or improving material thermal properties, the angular velocity measurement error caused by temperature drift can be significantly reduced, thereby improving the long-term positioning reliability of navigation systems in extreme temperature fluctuation scenarios. This article starts with the structure of the hemispherical resonant gyroscope, studies the temperature characteristics of the hemispherical resonator through formula theory, verifies and analyzes the temperature characteristics of the hemispherical resonant gyroscope through experiments, and designs a temperature compensation scheme. Through experimental data analysis, the root mean square error of hemispherical gyroscope drift was reduced from 1.451066 ° /h to 0.383937 ° /h after temperature compensation. This compensation scheme can effectively improve the output accuracy of the hemispherical resonant gyroscope and reduce the output drift under the condition of gyroscope temperature changes.
Wang, Jiachen, Chen, Pu, Yao, Zhiqiang, Zhang, Yi, Bai, Fan
Simulation Analysis of Pontoon Structure Based on Tunnel Bank Evacuation Channel2026-99-05417/10/2026
To meet the requirements for efficient evacuation during tunnel navigation, the pontoon of the tunnel bank wall evacuation channel in a large-scale navigation building is taken as the research object. The water body and water wave are simulated using the coupled Euler-Lagrangian method and the push-plate wave method, respectively. The water boundary is processed using the viscoelastic artificial boundary method, and a simulation analysis model of the pontoon under the combined action of water waves and load is established. The results show that the average relative vertical displacement of the pontoon is basically the same under the condition of water wave and no water waves, but the fluctuation range of the pontoon is larger under the condition of water waves. When there are water waves and different loads, the maximum Mises stress distribution of the pontoon is essentially the same, and both are less than 80 MPa, meeting the strength requirements and demonstrating the rationality of the pontoon design.
Tang, Weibi, Qin, Pan, Li, Ran, Tao, Ran, Hu, Zhifang
Ship Tunnel Navigation Evacuation Simulation and Evacuation Capability Evaluation2026-99-05727/10/2026
In order to solve the ship emergencies that may occur in the process of tunnel navigation, the tunnel pontoon-type bank wall evacuation channel proposed in a large navigation building is taken as the research object. Based on Pathfinder evacuation software, a numerical model of pedestrian evacuation for 500 passenger ships in emergency situations such as fire in the navigation tunnel is established, and the evacuation simulation analysis and evacuation ability evaluation are completed. The analysis shows that the emergency evacuation time of personnel is at least about 21 minutes, and the bottleneck of emergency evacuation equipment for personnel in the navigation tunnel is at the entrance of the pontoon escape. The results provide guidance and suggestions for the design optimization of the evacuation channel of the tunnel bank wall in the later period.
Tao, Ran, Li, Ran, Tang, Weibi, Hu, Zhifang, Qin, Pan
Items per page:
1 – 50 of 1325