Browse Topic: Satellite communications

Items (449)
This paper investigates the tracking of highly maneuverable targets during flight and the corresponding satellite scheduling problem in a space-based observation system. Based on dual-satellite measurements, a nonlinear observation equation was formulated. The J2 perturbation model and the current statistical model were utilized within an Interacting Multiple Model filtering framework to achieve adaptive estimation of the target states of the boost-glide vehicles. Building upon this framework, a greedy satellite scheduling algorithm based on IMM model probabilities is proposed. This method dynamically selects the optimal measurement set within a given prediction window to maximize observation performance. The proposed strategy is compared against rolling-horizon scheduling and fast-slow timescale scheduling approaches. Simulation results demonstrate that the proposed method effectively adjusts model weights in response to target maneuvers, enhancing adaptability during highly maneuverable phases. Meanwhile, it reduces the number of satellite switches while maintaining estimation accuracy, significantly improving scheduling efficiency and tracking continuity.
Deng, SiruiLiu, ChengzheWang, Yandong
In this paper, we focus on satellite production lines and design and implement a digital twin simulation and verification system for them. This is to improve manual documentation efficiency and provide sufficient process controllability in the small satellites’ batch production and assembly testing. We built a layered architecture. This allows the system to dynamically interact with AIT data management systems, structured process systems, and equipment data by fusing multi-source data. We also develop functional modules that combine lightweight 3D model visualization, dynamic simulation engines, and hybrid scheduling optimization algorithms. These modules can perform twin simulation, execute processes, intelligently schedule production, manage work reporting, conduct intelligent analysis, trigger anomaly alarms, and perform system management. We also dynamically simulate complex workflows like satellite transfer and automated assembly. These workflows are then verified using 3D virtual scene modeling and physical engines. We use time-series analysis to improve scheduling accuracy and multidimensional dynamic monitoring and hierarchical response to enhance production stability. In practice, the system can provide visualized control over the full process of satellite production. This greatly improves assembly efficiency and process controllability. It can also be an extensible digital way for aerospace manufacturing. The use of hierarchical architecture design and multimodal data fusion can be further applied in the complex equipment intelligent manufacturing.
Zhao, Fenghua
This paper solves the problem of resource and energy constraints on orbit computing for LEO satellites. By combining MADDPG reinforcement learning and Lyapunov optimization, the paper proposes a computing framework and implements an adaptive task offloading model for space flight using a multi-agent deep actor critic algorithm, MADDPG. The joint optimization mechanism is implemented by multi-agent dynamic task offloading. Through the transformation from the state with long-term constraints into optimization of the status of queue stability, the load scheduling under threshold energy in accordance with the characteristics of energy constraints was realized by introducing Lyapunov virtual queues into the process of policy evaluation of deep reinforcement learning. The experimental results show that the proposed framework enables a lightweight preliminary calculation, balanced energy consumption to reduce resource allocation, and realizes the stable queues through adaptability of tasks under energy balance conditions, which can provide high-efficiency computing assistance and support for space orbit tasks such as monitoring remote sensing of Earth.
Yan, MingZhao, LiangXu, LexiZhou, XiaofeiHawbani, AmmarSun, Yunhe
Aiming at problems such as low efficiency and poor accuracy in fault identification for traditional small satellites, this paper proposes a multi-model fusion method based on machine learning. By constructing a telemetry data preprocessing module based on the Data Generation Adversarial Network, it effectively deals with outliers and fills missing values. Combining single model methods such as polynomial curve fitting, the grey model, and the ARMA model, and introducing the Long Short-Term Memory network and Gated Recurrent Unit to fuse with these models enhance the ability to process complex data features. The prediction results of each model are fused using machine learning methods, and finally, the fused value is taken as the final prediction result. The numerical simulation results show that this prediction method can predict the anomalies of different types of satellite telemetry parameters and has achieved good results.
Liu, BiyanChen, YeGuo, Qi
To solve a problem that ignition anomaly can’t be detected in time, based on the thermal equilibrium equation, the space heat flow, heater heating, propellant combustion, and thermal radiation to cryogenic space are considered to build an accurate ignition temperature method for the 10 N thruster by using on-orbit true temperature. Further, considering the error of measuring the thermistor, an envelope model for the 10 N thruster ignition temperature is established. Based on the above, a detection method for the 10 N thruster ignition anomaly of on-orbit satellites is proposed. The accuracy of the method is relatively high, and the absolute error is less than 3 degrees Celsius. An anomaly can be quickly detected when the 10N thruster ignition temperature deviates from the normal trend by 3–5 degrees celsius. The method is applied to a DFH-3 satellite, and the maximum difference of 10 N thruster ignition temperature between the theoretical values calculated by the proposed method and the measured values is only 2.72 degrees celsius. It has been proven that the prediction accuracy of the proposed method is high. It plays an important role in discovering the 10N thruster ignition anomaly in time and ensuring the success of satellite orbit or attitude control.
Li, LilingTian, HuadongWei, YuboFei, DiXing, Chao
Noise pollution is a major environmental and health challenge, yet its strong spatial and temporal variability makes comprehensive mapping highly complex. Current approaches under the European Noise Directive (END) provide only partial coverage and often lack temporal dynamics. The NoiseSphere project, funded by the Austrian Research Promotion Agency FFG, develops an AI-based methodology for dynamic, large-scale noise prediction and mapping. A machine learning model is trained on heterogeneous data sources, including semantically enriched open Sentinel-2 satellite imagery, OpenStreetMap road data and existing noise maps. The model is refined through integration of noise emission data and validated using targeted in-situ measurements. A case study in an urban environment (Graz, Austria) demonstrates the model’s applicability. By combining remote sensing, traffic dynamics, and machine learning, NoiseSphere enables predictive noise mapping even in regions not covered by current legislation. This approach provides a scalable tool for evidence-based environmental planning, health risk assessment, and policy support.
Girstmair, Josef
Global Navigation Satellite System (GNSS) receivers are widely being used in aerospace as well as automotive applications primarily for navigation applications. ISRO uses indigenously developed GNSS receivers in its Launch vehicles (LV) mainly for POD (Preliminary Orbit Determination) and for INS aiding in long duration missions. Advanced GNSS receivers are being developed and used in ISRO’s new generation launch vehicles for closed loop guidance (CLG) applications. Being used in CLG, continuous solution availability and robustness of GNSS solutions are of paramount importance. From April 2023 onwards, GNSS receivers on-board ISRO’s LV missions have shown degraded performance in terms of reduction in no. of satellites tracked and in some cases loss of GNSS solution as well. This was seen in multiple missions and was analyzed in detail. It was observed that there is nearly 3-4dB reduction in carrier to noise density (C/No) ratio and corresponding change in RF AGC gain is also observed. The issue is seen when the LV’s ground trace is over a particular terrestrial area (latitude 7degN-10degN longitude 95degE-110degE). A survey on internet indicated presence of GPS interference/jamming signals from nearby region and aircraft pilots have also reported similar observations. This paper addresses the performance degradation observed due to terrestrial jamming in ISRO’s GNSS receiver and analysis of observation w.r.t reduction in carrier to noise ratio and RF AGC gains. Further details on anti-jamming techniques implemented in LV GNSS receivers using trajectory based jamming signal isolation using RF switch is also addressed in this paper. Future developments being pursued towards building resilience towards different threats including jamming and spoofing using dual RF-front end & other software techniques are also discussed in this paper.
A, Mohammed BasimO T, Anand ShankaraV S, BijuV Gopal, BijuV S, VinojK, BalanC, Radhakrishna Pillai
Space vehicle and satellite development programs are driving demand for new small- and medium-sized satellites across commercial and defense imaging, data collection, and other space-based applications.
The successful launch of the final GPS-III satellite into orbit makes 32 total satellites in the GPS-III constellation, and paves the way for production and launch of GPS-IIIF satellites. Space Systems Command, El Segundo, CA With the successful launch of the 10th Global Positioning System III satellite on April 21 from Cape Canaveral Space Force Base, Space Systems Command is celebrating the start of a new era for the world's premier GPS constellation. “This milestone satellite launch completes GPS Block III,” said Erin Carper, Acting Portfolio Acquisition Executive for Satellite Communications and Positioning, Navigation, and Timing (PNT) at SSC. “Providing critical military and civil signal accuracy 24/7, GPS continues to underpin global military operations for our warfighters.”
As satellites take on more onboard processing - from Earth imaging to autonomy - spacecraft computing designers are pushing for higher performance under tight thermal and radiation constraints. Here's how suppliers are approaching heat removal, radiation mitigation and production-scale space-grade computing for LEO and beyond.
Researchers discover texts, phone calls, military communication, internal corporate networks all easily eavesdropped on using off-the-shelf equipment. University of California San Diego, La Jolla, CA With $800 of off-the-shelf equipment and months' worth of patience, a team of U.S. computer scientists set out to find out how well geostationary satellite communications are encrypted. And what they found was shocking. Close to half of the communications beamed from satellites to the ground that the researchers were able to listen in on were not encrypted. This included sensitive data including cellular text messages, voice calls, as well as sensitive military information, data from internal corporate and bank networks, and the in-flight online activity of airline passengers.
The convergence of highly capable edge AI models and advanced commercial-off-the-shelf (COTS) edge AI accelerators is reshaping how computation is deployed across defense, aerospace, and commercial platforms. Mission-critical decisions increasingly must be made at the edge, onboard vehicles, satellites, and infrastructure nodes, where latency, connectivity, and power availability are constrained.
Precise time synchronization is the backbone of today's connected world, keeping telecom networks, data centers, and financial systems running seamlessly. Without accurate timing, our digital infrastructure would quickly fall out of sync. Septentrio designs and manufactures world recognized Global Navigation Satellite System (GNSS) timing receivers for critical infrastructure and leading industry organizations. The Septentrio mosaic-T timing module delivers nanosecond-level precision for synchronization and is trusted by companies such as Meinberg, VIAVI, and Saab. Built-in AIM+ technology protects against intentional and unintentional GNSS jamming and spoofing, ensuring maximum system uptime even in challenging or hostile conditions.
RF and fiber have long co-existed within modern military and aerospace systems, with each medium dedicated to separate, mission-critical roles. Increasingly, however, system designers are turning to RF-over-fiber (RFoF) architectures to bridge the gap between over-the-air RF interfaces and the long, interference-resistant transport advantages of fiber. When it comes to over-the-air communications uses like tactical radio or satellite communications terminals, radio frequency (RF) is still the dominant signal format. RF is also commonly used at the front end of radar and electronic warfare, supporting search, tracking, fire control radar, missile seekers, jammers and electronic support measures.
NASA's Space Communications and Navigation (SCaN) Program and the Johns Hopkins Applied Physics Laboratory in Laurel, Maryland, have successfully tested wideband technology that allows spacecraft to communicate with both government and commercial networks for the first time. Launched July 23, 2025, aboard a SpaceX Falcon 9 rideshare mission, the Polylingual Experimental Terminal (PExT) is demonstrating multilingual wideband terminal technology. Hosted on a satellite from York Space Systems, PExT enhances a spacecraft's communications subsystem, enabling mission controllers to track and exchange data more efficiently across a broad range of networks and frequencies.
Without reliability and signal integrity, aerospace communications risk severe signal degradation and reduced security, posing risks to both personnel and mission-critical data. These challenges are particularly critical for applications that depend on military aircraft, satellite communications, and unmanned aerial vehicles (UAVs). As global demand for real-time data continues to surge, communication infrastructure requires regular maintenance and upgrades to maintain secure and reliable performance.
The U.S. Space Force (USSF) Space Systems Command (SSC) achieved a major milestone during a demonstration event in August, showcasing the Joint Antenna Marketplace (JAM) and successfully transferring the U.S. Naval Research Laboratory's (NRL) Transmit/Receive Enterprise (TREx) Service from a research and development project into an SSC operational prototype. During the demonstration, the team demonstrated the use of commercial antennas for real-time contacts between a Space Development Agency's (SDA) satellite operations center and their Tranche 0 satellites using JAM which leveraged the newly integrated TREx system.
The European Space Agency (ESA) has added a micro-vibration test instrument, developed by the National Physical Laboratory (NPL), to its satellite testing facilities. NPL is the United Kingdom’s National Measurement Institute, developing and maintaining the national primary measurement standards. The instrument measures vibrations generated by satellite subsystems, to quantify their effects on images and measurements made from space. This facility is the result of five years of collaboration between NPL and ESA.
Moog Inc. East Aurora, NY kgibas@moog.com
In contemporary society, where Global Navigation Satellite Systems (GNSS) are utilised extensively, their inherent fragility gives rise to potential hazards with respect to the safety of ship navigation. In order to address this issue, the present study focuses on an ASM signal delay measurement system based on software defined radio peripherals. The system comprises two distinct components: a transmitting end and a receiving end. At the transmitting end, a signal generator, a first time-frequency synchronisation device, and a VHF transmitting antenna are employed to transmit ASM signals comprising dual Barker 13 code training sequences. At the receiving end, signals are received via software-defined radio equipment, a second time-frequency synchronisation device, a computing host, and a VHF receiving antenna. Utilising sliding correlation algorithms enables accurate time delay estimation. The present study leverages the high performance and low cost advantages of the universal software-defined radio peripheral USRP, fully utilises the good autocorrelation of ASM signals, effectively improves the accuracy of signal transmission delay measurement, and provides a reliable technical means to ensure the safety of ship navigation. The practical application of this subject is of significant importance, and there are wide prospects for its promotion and application.
Li, HaoSun, XiaowenWang, TianqiZhou, ZeliangWang, Xiaoye
Measuring the volume of harvested material behind the machine can be beneficial for various agricultural operations, such as baling, dropping, material decomposition, cultivation, and seeding. This paper aims to investigate and determine the volume of material for use in various agricultural operations. This proposed methodology can help to predict the amount of residue available in the field, assess field readiness for the next production cycle, measure residue distribution, determine hay readiness for baling, and evaluate the quantity of hay present in the field, among other applications which would benefit the customer. Efficient post-harvest residue management is essential for sustainable agriculture. This paper presents an Automated Offboard System that leverages Remote Sensing, IoT, Image Processing, and Machine Learning/Deep Learning (ML/DL) to measure the volume of harvested material in real-time. The system integrates onboard cameras and satellite imagery to analyze the field and top layers of residue, correlating this data with elevation maps to compute harvested material volume. This innovation supports operations such as baling, residue decomposition time and thereby contributing to land preparation. This technique offers benefits like reduced operational costs, labor independence, and enhanced soil nutrient planning.
Singh, Rana ShaktiStallin, Saravanan
NASA has developed an innovative combination of a Magnetometer, low-powered ElectroMagnets, and Resonant Inductive Coupling (MEMRIC) to create and control relative positioning of nano satellites within a cluster. This is a game-changing approach to enable distributed nanosatellite (nanosat) clusters. The focus is on low-cost propulsion, navigation, and power sharing. Each of these functions can share the same basic technology.
The success of off-road missions for ground vehicles depends heavily on terrain traversability, which in turn requires a thorough understanding of soil characteristics a key component being soil moisture content. When large areas need to be analyzed, satellite imagery is often used, although this approach typically reduces the spatial resolution. This decrease of spatial resolution creates what are known as mixed pixels, when two or more classes or features are in a single pixel’s area, which can lead to noisier data and lower accuracy models. This paper investigates using linear spectral unmixing as a way to help clean / mitigate noisy data to yield better predictive models. Hyperspectral remote sensing from the Hyperion satellite platform and ground truth from the International Soil Moisture Network (ISMN) are used for the dataset. This study found that soil moisture content prediction, comparing the mixed multilayer perceptron (MLP) model with an unmixing approach revealed a 10–30% change in RMSE and MAE across NDVI ranges incremented by 0.1. Hence, this study demonstrates the potential use of spectral unmixing as a methodology to help enhance predictive models for terrain properties when using (lower spatial resolution / more noisy) remotely sensed datasets.
Ewing, JordanJayakumar, ParamsothyKasaragod, AnushOommen, Thomas
Solar cells account for approximately six percent of the electricity used on Earth; however, in space, they play a significantly larger role, with nearly all satellites relying on advanced solar cells for their power. That’s why Georgia Tech researchers will soon be sending 18 photovoltaic cells to the International Space Station (ISS) for a study of how space conditions affect the devices’ operation over time.
SuperSharp University of Cambridge, United Kingdom
In a groundbreaking achievement, the 101st Combat Aviation Brigade, 101st Airborne Division (Air Assault) earlier this year became the first unit to successfully use the Mobile User Objective System (MUOS) function of the Army/Navy Portable Radio Communications (AN/PRC) 158 and 162 radios for conventional rotary wing operations. The trailblazing accomplishment occurred as the brigade continued its mission of providing support to ground forces, April 9, 2025. The MUOS function, of the AN/PRC-158 and 162 radios, operates by transmitting ultra-high frequency radio waves through a constellation of satellites to create a steady communications network. MUOS is a component of a bigger Integrated Tactical Network (ITN).
Advanced motion control technologies are essential to modern aerospace design, supporting a wide range of safety-critical and comfort-driven applications. In aerospace, motion control components such as gas springs, actuators, and dampers are integral to nearly every commercial aircraft, rocket, satellite, and space vehicle. These critical elements support flight safety and transport functions, from the dependable deployment of landing gear and cargo doors to the smooth, ergonomic operation of seating for pilots and passengers.
Despite all the technological evolution in navigation, waters just off coastal shores around the globe have remained a black box. That is, until researchers from The University of Texas at Austin and Oregon State University developed a new technology that uses satellites in space to map out these tricky areas.
As NASA’s Artemis missions build out infrastructure on and around the Moon in the coming years, CubeSats and other small satellites will likely play an important role in a communications network that will enable not only conversation with mission control but also navigation, direct scientific observations, and more, all enabled by an internet-like “LunaNet.” These little satellites are cheap to launch and can form constellations for relaying signals reliably. But their small size makes it hard for them to carry antennas large enough to communicate across vast distances.
In October 2024, Kongsberg NanoAvionics discovered damage to their MP42 satellite, and used the discovery as an opportunity to raise awareness on the need to reduce space debris generated by satellites. Kongsberg NanoAvionics, Vilnius, Lithuania Our MP42 satellite, which launched into low Earth orbit (LEO) two and a half years ago aboard the SpaceX Transporter-4 mission, recently took an unexpected hit from a small piece of space debris or micrometeoroid. The impact created a 6 mm hole, roughly the size of a chickpea, in one of its solar panels. Despite this damage, the satellite continued performing its mission without interruption, and we only discovered the impact thanks to an image taken by its onboard selfie camera in October of 2024. It is challenging to pinpoint exactly when the impact occurred because MP42's last selfie was taken a year and a half ago, in April of 2023.
The global satellite communications (SATCOM) sector is undergoing profound transformation. Fueled by the rapid growth of low Earth-orbit (LEO) constellations, increased government investment, and heightened demand for secure, high-throughput connectivity, the market is projected to expand from $66.75 billion in 2025 to $103.78 billion by 20291, 2. This momentum reflects a broader realignment of priorities across commercial and defense markets: a shift from reliance on legacy geostationary systems toward agile, resilient networks capable of supporting next-generation missions and applications.
With 2D cameras and space robotics algorithms, astronautics engineers at Stanford have created a navigation system able to manage multiple satellites using visual data only. They recently tested it in space for the first time. Stanford University, Stanford, CA Someday, instead of large, expensive individual space satellites, teams of smaller satellites - known by scientists as a “swarm” - will work in collaboration, enabling greater accuracy, agility, and autonomy. Among the scientists working to make these teams a reality are researchers at Stanford University's Space Rendezvous Lab, who recently completed the first-ever in-orbit test of a prototype system able to navigate a swarm of satellites using only visual information shared through a wireless network. “It's a milestone paper and the culmination of 11 years of effort by my lab, which was founded with this goal of surpassing the current state of the art and practice in distributed autonomy in space,” said Simone D'Amico, associate professor of aeronautics and astronautics and senior author of the study. “Starling is the first demonstration ever made of an autonomous swarm of satellites.”
Physicists at the Naval Research Laboratory are collaborating with several universities throughout the U.S. to develop a small satellite that will detect the emission of short gamma-ray bursts. U.S. Naval Research Laboratory, Washington D.C. The U.S. Naval Research Laboratory (NRL), in partnership with NASA's Marshall Space Flight Center (MSFC), has developed StarBurst, a small satellite (SmallSat) instrument for NASA's StarBurst Multimessenger Pioneer mission, which will detect the emission of short gamma-ray bursts (GRBs), a key electromagnetic (EM) signature that will contribute to the understanding of neutron star (NS) mergers. NRL transferred the instrument to NASA on March 4 for the next phase, environmental testing. From there, the instrument will be integrated onto the spacecraft bus, followed by launch into Low Earth Orbit in 2027. StarBurst will be installed as a secondary payload via the Evolved Expendable Launch Vehicle Secondary Payload Adapter Grande interface with a mission duration of one year, with the option of extension.
The Department of Defense (DoD) is developing technology for satellites to communicate via lasers. Laser communications could transmit data faster and more securely than traditional radio frequency communications. DoD has made progress in developing this technology, but it has also faced delays and other issues-and hasn't fully demonstrated that it works in space. Despite these challenges, DoD plans to continue to develop and launch hundreds of satellites worth billions of dollars that require the use of laser communications.
The U.S. Naval Research Laboratory (NRL), in partnership with NASA’s Marshall Space Flight Center (MSFC), has developed StarBurst, a small satellite (SmallSat) instrument for NASA’s StarBurst Multimessenger Pioneer mission, which will detect the emission of short gamma-ray bursts (GRBs), a key electromagnetic (EM) signature that will contribute to the understanding of neutron star (NS) mergers.
Our MP42 satellite, which launched into low Earth orbit (LEO) two and a half years ago aboard the SpaceX Transporter-4 mission, recently took an unexpected hit from a small piece of space debris or micrometeoroid. The impact created a 6 mm hole, roughly the size of a chickpea, in one of its solar panels.
Airbus Defense London, UK aeron.a.haworth@airbus.com
NearSpace Launch Inc. (NSL), a privately held and fully U.S.-owned aerospace company, is actively redefining the boundaries of responsive spaceflight through its development and deployment of the Train Rapid on Orbit Payload (TROOP) and ThinSat platforms. Over the past decade, NSL has launched more than 100 small satellites and over 900 flight systems and subsystems into orbit. NSL's satellites have been part of launches operated by Astra, Atlas, Delta, Firefly Aerospace, Northrop Grumman, Virgin Galactic and SpaceX among others. Headquartered in Upland, Indiana, NSL is currently the largest small satellite manufacturer in the midwestern region of the U.S., uniquely positioned to address urgent national needs for rapid space access and technology testing.
Someday, instead of large, expensive individual space satellites, teams of smaller satellites – known by scientists as a “swarm” – will work in collaboration, enabling greater accuracy, agility, and autonomy. Among the scientists working to make these teams a reality are researchers at Stanford University’s Space Rendezvous Lab, who recently completed the first-ever in-orbit test of a prototype system able to navigate a swarm of satellites using only visual information shared through a wireless network.
Rotorcraft continue to experience higher fatal accident rates compared to fixed-wing aircraft, primarily due to low altitude flight operations and reduced situational awareness in complex environments. A critical factor is the limited availability of accurate, up-to-date information on helipads and surrounding obstacles - such as trees, poles, and buildings - that pose significant risks during takeoff and landing. Existing resources, including the Federal Aviation Administration's heliport registry, are often outdated and incomplete, particularly for private or state-operated sites, and fail to report nearby obstacles. This lack of up-to-date data is largely due to privacy restrictions at certain locations and the high cost associated with comprehensive obstacle surveys. To address this challenge, we develop a deep learning (DL) framework that automatically detects helipads and nearby obstacles from high-resolution satellite imagery. Our approach combines Mask R-CNN for precise pixel-level helipad segmentation with Grounding DINO, a zero-shot vision-language model that identifies obstacles using flexible text prompts (e.g., "Pole", "Tree") without task-specific training. This text-guided, scalable detection method adapts to diverse and evolving operational settings. We validate our framework across helipads in the United States, and demonstrate strong performance in both helipad localization and obstacle detection. In addition, we build a web-based application that automates image processing, updates incorrect heliport coordinates, and provides obstacle reports. This work aims to enhance aviation safety, modernize infrastructure records, and deliver scalable tools to the aviation and machine learning communities.
Khelifi, AmineCarannante, GiuseppinaBouaynaya, NidhalJohnson, Charles
Muelaner, Jody EmlynMoran, MatthewPhillips, Paul
Recent advances are reducing the cost of space launch, high specific power solar cells, and the production of satellite systems. Modular architectures with no moving parts and distributed power systems would minimize assembly and maintenance costs. Together, this may enable space-based solar power to provide decarbonized dispatchable power at a lower cost than equivalent technologies such as nuclear power stations. Space-based Solar Power for Instantaneously Dispatchable Renewable Power on Earth discusses the advances in emerging technologies, like thin film solar cells, reusable launch vehicles, and mass-produced modular satellite systems that would make economic space power feasible. Click here to access the full SAE EDGETM Research Report portfolio.
Muelaner, Jody Emlyn
This study investigates the application of integrated positioning based on SINS (Strapdown Inertial Navigation System) and GNSS (Global Navigation Satellite System) for highway vehicle navigation. While GNSS offers high-precision outdoor positioning, it is susceptible to signal obstructions, whereas SINS enables autonomous positioning without external signals but accumulates drift errors over time. To enhance positioning accuracy, this study employs three nonlinear filters—Extended Kalman Filter (EKF), Unscented Kalman Filter (UKF), and Cubature Kalman Filter (CKF)—for multi-source data fusion. Experimental results demonstrate that EKF, UKF, and CKF achieve faster convergence, higher stability, and smoother error curves when handling nonlinear problems. Through simulation experiments and field measurements, the strengths of each algorithm are validated across different metrics and directions. Considering sensor limitations and implementation complexity, EKF outperforms other algorithms in scenarios with limited sensors. The findings of this study provide a foundation for improving vehicle navigation accuracy in complex environments.
Zhang, HongbinWen, ChengjuLiu, ZheLin, Chen
There are dead-end roads in the road network, and many of them have the function of indicating specific target clues, which is of great significance in the fields of military, urban construction, and disaster relief and rescue. However, many of the important cut-offs are in mountainous or wilderness areas, and surveying them is difficult and costly. The research objective of this project is to extract the breakpoints in the road network using high-resolution Google satellite imagery, so as to provide clues and indications for the subsequent relevant work. Firstly, the image is corrected and pre-processed to highlight road edge information.Then the phase grouping method is improved by setting a double-angle threshold, filtering the edge operator to reduce the calculation error of the gradient angle, and the road network is extracted by the improved phase grouping method. And finally screens out the dead-end road points with the eight-neighbourhood method, and marks them on the experimental image, so as to realize the identification and positioning of the dead-end roads.The algorithm has a certain degree of universality, after replacing the experimental area and image, it can still locate the dead-end road breakpoints accurately, and the universal accuracy rate reaches more than 80%, and after adjusting the threshold value for a specific area, the extraction accuracy rate can reach more than 90%. This project realizes the technology of identifying and locating the dead-end road based on the phase grouping method, which can intelligently and automatically identify and locate the dead-end roads on the remote sensing image, and the improvement of the phase grouping method significantly improves the extraction precision of the road network and the extraction precision of the broken point, which is of practical value.
Liu, RuohanHaoping, QiJingjie, KangYanyan, WuFeifei, Li
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