Browse Topic: Radar
The detection of free space plays a fundamental role in ensuring the safe and efficient operation of heavy-duty vehicles, particularly in environments where the available area to maneuver is severely constrained, such as construction zones, rest areas, or loading docks. An accurate estimation of free space is essential to prevent collisions, maintaining operational continuity and minimizing vehicle downtime. As observed from the reviewed literature, despite the large number of proposed free-space detection methods, there is no concise and established definition about how free space should be determined, represented, and inferred, nor agreement on the semantic classes to be considered. This heterogeneity complicates systematic comparison and benchmarking across approaches. This paper presents a structured survey and methodological analysis of recent free-space detection and semantic segmentation approaches across automotive LiDAR-, camera-, and radar-based perception systems, as well as multimodal sensor fusion. The review spans classical geometric and occupancy-based techniques together with deep-learning methods, along with datasets commonly used for evaluation. The main contributions are (i) a structured taxonomy and comparative analysis of existing free-space definitions and detection strategies, categorized by their assumptions, representation forms, and sensing modalities; and (ii) a unified and application-independent definition of free space together with the required semantic classes. These contributions aim to provide a consistent conceptual foundation to support future research and to aid the systematic evaluation of upcoming free-space detection systems.
On a clear afternoon over a contested airspace, a drone suddenly appears on radar. Within seconds, more follow, and they're small, fast, and unpredictable. For the U.S. Army's air and missile defense operators, every moment counts. The difference between mission success and mission failure is measured in milliseconds. During that brief window, sensors must connect instantly, embedded systems must process floods of data at the edge, and command links must hold steady even under electronic interference.
This study introduces a novel in-cabin health monitoring system leveraging Ultra-Wideband (UWB) radar technology for real-time, contactless detection of occupants' vital signs within automotive environments. By capturing micro-movements associated with cardiac and respiratory activities, the system enables continuous monitoring without physical contact, addressing the need for unobtrusive vehicle health assessment. The system architecture integrates edge computing capabilities within the vehicle's head unit, facilitating immediate data processing and reducing latency. Processed data is securely transmitted via HTTPS to a cloud-based backend through an API Gateway, which orchestrates data validation and routing to a machine learning pipeline. This pipeline employs supervised classifiers, Support Vector Machine (SVM), K-Nearest Neighbors (KNN), and Random Forest (RF) to analyze features such as temporal heartbeat variability, respiration rate stability, and heart rate. Empirical evaluations demonstrate the system's proficiency in classifying occupant states, including normal, distressed, and unconscious conditions, achieving high prediction accuracy with low false positive rates. Notably, the system attains sub-10-second detection latency and facilitates end-to-end response actions within a 5-minute window. Experimental deployment in a Mercedes vehicle demonstrated high accuracy in occupancy detection (97%), vital sign monitoring (94%), and full ERS (Emergency Response System) activation within five minutes, meeting Euro NCAP 2025+ Child Presence Detection (CPD) requirements. Furthermore, the cloud infrastructure supports the accumulation of health data, contributing to personalized driver profiles and informed decision-making for future interventions. This research underscores the potential of UWB radar technology in augmenting automotive safety through real-time health monitoring, paving the way for smarter and more secure vehicular environments.
Perception radar company Arbe was at IAA Mobility in Munich this year to press the case that customers can and should trust automated vehicles. One reason is the global trend of stricter regulations from the NHTSA, Euro NCAP, and in China, which now require automated vehicles to safely meet demanding use cases that are not covered by current sensors, according to Arbe co-founder and CTO Noam Arkind. Arkind told SAE Media that one such category is detecting vulnerable road users (VRU) in poor weather and lighting conditions. “We know from recent tests that a lot of Chinese cars, for example, failed VRU detections in the dark,” he said. “Camera alone doesn't really have reliable pedestrian detection in a dark situation. Radar is a great sensor. It's very sensitive. It's not dependent on weather conditions or lighting conditions, but it's noisy, it's low resolution, and it's hard to use.”
Hensoldt Taufkirchen, Germany nico.fritz@hensoldt.net
The Vision for Off-road Autonomy (VORA) project used passive, vision-only sensors to generate a dense, robust world model for use in off-road navigation. The research resulted in vision-based algorithms applicable to defense and surveillance autonomy, intelligent agricultural applications, and planetary exploration. Passive perception for world modeling enables stealth operation (since lidars can alert observers) and does not require more expensive or specialized sensors (e.g., radar or lidar). Over the course of this three-phase program, SwRI built components of a vision-only navigation pipeline and tested the result on a vehicle platform in an off-road environment.
Modern military aircraft represent some of the most complex electronic environments ever engineered. These platforms integrate advanced avionics, radar systems, data links, and communication networks that must function seamlessly in hostile, high-frequency environments. In these mission-critical contexts, electromagnetic interference (EMI) poses a silent but serious threat that can degrade signal integrity, cause crosstalk between systems, or even lead to mission failure. The combination of increasing data rates, higher frequencies, and more complex electromagnetic environments demands shielding solutions that can deliver superior performance while contributing to overall system weight reduction. This challenge has driven innovation toward advanced materials that maintain electrical effectiveness while dramatically reducing mass.
FibreCoat, the German materials startup, has developed a groundbreaking fiber reinforced composite that is capable of making aircraft, tanks and spacecraft invisible to radar surveillance. The company was officially founded in Aachen, Germany, in 2020, however its core founding team first began developing new approaches to the use of materials that make commercial and military vehicles invisible to radar as back as 2014. FibreCoat is known for inventing a novel technology to coat metals and plastics onto fibers, thus combining the properties of the fibers and the coating material, during the fiber-spinning process.
FibreCoat, the German materials startup, has developed a groundbreaking fiber reinforced composite that is capable of making aircraft, tanks and spacecraft invisible to radar surveillance.
The U-Shift IV represents the latest evolution in modular urban mobility solutions, offering significant advancements over its predecessors. This innovative vehicle concept introduces a distinct separation between the drive module, known as the driveboard, and the transport capsules. The driveboard contains all the necessary components for autonomous driving, allowing it to operate independently. This separation not only enables versatile applications - such as easily swapping capsules for passenger or goods transportation - but also significantly improves the utilization of the driveboard. By allowing a single driveboard to be paired with different capsules, operational efficiency is maximized, enabling continuous deployment of driveboards while the individual capsules are in use. The primary focus of U-Shift IV was to obtain a permit for operating at the Federal Garden Show 2023. To achieve this goal, we built the vehicle around the specific requirements for semi-public road operations which includes narrow streets and pedestrians. This involved integrating necessary modifications across multiple domains, including the e/e-architecture, sensor setup, software stack, and even the design of the driveboard and capsule. By utilizing systematic methods to address regulatory and safety challenges, we ensured that the vehicle met the standards required for autonomous driving in semi-public environments. In this paper, we explore the methodologies employed to achieve regulatory compliance, focusing on sensor integration, software- and e/e-architecture. We discuss our multi-modal sensor setup, which combines camera, lidar and radar to archive redundancy and enhanced environmental perception. Additionally, we provide an overview of our software architecture, emphasizing its role in ensuring safe driving functions and enabling autonomous operations.
Airbus Defense London, UK aeron.a.haworth@airbus.com
Low-level flight, defined by high-speed operations near terrain, represents a significant challenge in military rotorcraft missions while providing strategic advantages, such as radar evasion and heightened surprise. Recent conflicts highlight the urgent need for advanced low-level flight capabilities in the design of new rotorcraft. The close proximity to ground obstacles, combined with the complexities of piloting, necessitates precise control and robust handling qualities to prevent accidents. However, existing handling quality standards, such as MIL-DTL-32742, reveal limitations in assessing low-level maneuvers. Given the diverse array of new rotorcraft designs, driven by initiatives like the U.S. Army's Future Vertical Lift and NATO's Next Generation Rotorcraft Capabilities, a customized handling qualities evaluation for each design is impractical. In response, a performance-driven strategy has been implemented, scaling Mission Task Elements to align with aircraft performance capabilities. This approach identifies handling quality gaps across the Operational Flight Envelope, concentrating on the aircraft’s effectiveness in achieving task success under varied conditions. Prior simulator studies validate the effectiveness of this method for assessing different configurations. This paper presents flight test results using DLR's ACT/FHS research helicopter, confirming a set of scalable Mission Task Elements developed at DLR's AVES and NASA's VMS simulators. Pilots utilized a Head-Mounted Display for task cueing, eliminating the need for physical infrastructure. The Mission Task Elements proved suitable for evaluating the low-level handling qualities of the ACT/FHS. Although the provided Head-Mounted Display facilitated Handling Qualities evaluations, it encountered some hardware limitations. The scaling for different airspeeds met pilot expectations, and wind compensation functioned as anticipated, enhancing the independence of flight tests from environmental conditions. These findings lead to recommended updates for task descriptions and course cueing requirements, confirming desired performance tolerances.
Just one year after signing a ground-breaking trilateral agreement, the Deep Space Advanced Radar Capability partnership is completing facilities construction at the first of three sites that will host a global network of advanced ground-based sensors.
Naval Air Systems Command Patuxent, MD navairpao@us.navy.mil
Hensoldt Taufkirchen, Germany nico.fritz@hensoldt.net
Launch, recovery, and deck handling operational performance on smaller ship platforms like Corvettes, Frigates and Destroyers are qualified as the most challenging tasks in the UAS ship-deployment of a VTOL Uncrewed Air System (UAS). One of the main hurdles is the random nature of seaway-created deck motions coupled with ship structure disturbed air wake patterns. The MoD has supported a range of work aimed at bringing Quiescent Period Prediction (QPP) technology to fruition. QPP firstly requires Wave Profiling RADAR to measure the sea wave system out to approximately 2km in the region around a vessel. Secondly these measurements are employed in a wave propagation model to predict the actual wave forces acting on a vessel. Using the wave predictions as inputs to a vessel model makes possible to predict the actual (deterministic as opposed to statistical) motions of a vessel. Wave systems naturally alternate groups of large waves with smaller waves, this property, combined with the predictive ability, allows to identify the quietest (most quiescent) periods in which to conduct wave limited naval operations. Naval mission planners in the Royal Navy, and elsewhere in the World, appreciate the need to maintain rapid, but safe, deck tempo. The fundamental concept is to measure remote sea surface profiles to predict the future wave forces acting upon a vessel. The objective is to expand ship operating deck limits to approximately Sea State 6+. The deck definitions generally empirically measured by using standard rating scales, are replaced by instrumented devices reporting the status of the deck prior to touch-down. In this paper, a thorough discussion describing the QPP deck measuring devices designed to replace piloted cueing is provided. Theory, previous simulation studies and current at-sea testing along with data results, are also discussed. To conclude, the interface of the deck measuring device into the next version of the UK UAS system, is provided. The results of the RADAR trial indicated that the RADAR data was reliable, with the RADAR images matching the physical map. The two-dimensional surface plot showed both the RADAR blocking fence along with an additional target. An additional observation concerning the operation over the deck whilst the ship is experiencing a quiescent ship motion period. The coupled secondary effect documents minimized air wake confusion. This is owing to fewer ship structure excursions into and out of the air flow. To better define deck airflow around the ship the integration of a Doppler LIDAR instrumented federate is proposed. This is meant to predict the future vessel air wake and look for quiescent periods in this paralleling the vessel motion QPP technique.
As infrastructure ages, it becomes more susceptible to failure, which can cause safety and mobility concerns for drivers and pedestrians, and economic woes for taxpayers. A recent study published in “Transportation Research Record” shows that high-resolution synthetic aperture radar (SAR) satellite data can detect infrastructure issues early on, which can help prevent further damage to roads in the same way that annual checkups can help prevent more complex health issues in humans.
The final frontier in digital transformation is the analog edge, where apertures and actuators meet the mission. Buried behind layers of firmware and analog mitigation, open architecture has a new frontier to conquer, and the opportunity starts at the component level, where digital transformation and the miniaturization enabled by Moore's Law is having its biggest impact. Miniature, modular, and intelligent gateways can be embedded into analog components to replace and re-imagine old firmware and analog mitigation circuitry. These new, embedded gateways promise to bring open architecture deeper into the tactical edge and realize a new level of agility throughout the lifecycle of a system, from design through sustainment of hybrid digital and analog systems.
Hensoldt Taufkirchen, Germany lothar.belz@Hensoldt.net
Automotive radar plays a crucial role in object detection and tracking. While a standalone radar possesses ideal characteristics, integrating it within a vehicle introduces challenges. The presence of vehicle body, bumper, chassis, and cables in proximity influences the electromagnetic waves emitted by the radar, thereby impacting its performance. To address these challenges, electromagnetic simulations can guide early-stage design modifications. However, operating at very high frequencies around 77GHz and dealing with the large electrical size of complex structures demand specialized simulation techniques to optimize radar integration scenarios. Thus, the primary challenge lies in achieving an optimal balance between accuracy and computational resources/simulation time. This paper outlines the process of radar vehicle integration from an electromagnetic perspective and demonstrates the derivation of optimal solutions through RF simulation.
Phased array radar technology has been gaining popularity since its initial introduction in the 1960s and is now being used in a variety of applications, from military and defense to civilian sectors and even space exploration. This cutting-edge technology has revolutionized radar systems by offering unparalleled flexibility, precision, and speed. At the heart of phased array radar lies a sophisticated antenna system composed of numerous individual elements, each capable of independently emitting and receiving radio waves. Unlike traditional radar systems that rely on mechanically rotating antennas, phased array radars electronically steer their beams, enabling rapid and precise target acquisition. This breakthrough is made possible by meticulously controlling the phase of radio waves emitted from each antenna element.
Researchers at the University of California, Davis, have developed a proof-of-concept sensor that may usher in a new era for millimeter wave radars. They call its design a “mission impossible” made possible.
Southwest Research Institute has developed off-road autonomous driving tools with a focus on stealth for the military and agility for space and agriculture clients. The vision-based system pairs stereo cameras with novel algorithms, eliminating the need for LiDAR and active sensors.
Radio frequency (RF) and microwave signals are integral carriers of information for technology that enriches our everyday life – cellular communication, automotive radar sensors, and GPS navigation, among others. At the heart of each system is a single-frequency RF or microwave source, the stability and spectral purity of which is critical. While these sources are designed to generate a signal at a precise frequency, in practice the exact frequency is blurred by phase noise, arising from component imperfections and environmental sensitivity, that compromises ultimate system-level performance.
Launch, recovery, and deck handling operational performance on smaller ship platforms like Corvettes, Frigates and Destroyers are qualified as the most challenging tasks in the UAS ship-deployment of a VTOL Uncrewed Air System (UAS). One of the main hurdles is the random nature of seaway-created deck motions coupled with ship structure disturbed air wake patterns. The MoD has supported a range of work aimed at bringing Quiescent Period Prediction (QPP) technology to fruition. QPP firstly requires Wave Profiling RADAR to measure the sea wave system out to approximately 2km in the region around a vessel. Secondly these measurements are employed in a wave propagation model to predict the actual wave forces acting on a vessel. Using the wave predictions as inputs to a vessel model makes possible to predict the actual (deterministic as opposed to statistical) motions of a vessel. Wave systems naturally alternate groups of large waves with smaller waves, this property, combined with the predictive ability, allows to identify the quietest (most quiescent) periods in which to conduct wave limited naval operations. Naval mission planners in the Royal Navy, and elsewhere in the World, appreciate the need to maintain rapid, but safe, deck tempo. The fundamental concept is to measure remote sea surface profiles to predict the future wave forces acting upon a vessel. The objective is to expand ship operating deck limits to approximately Sea State 6+. The deck definitions generally empirically measured by using standard rating scales, are replaced by instrumented devices reporting the status of the deck prior to touch-down. In this paper, a thorough discussion describing the QPP deck measuring devices designed to replace piloted cueing is provided. Theory, previous simulation studies and current at-sea testing along with data results, are also discussed. To conclude, the interface of the deck measuring device into the next version of the UK UAS system, is provided. The results of the RADAR trial indicated that the RADAR data was reliable, with the RADAR images matching the physical map. The two-dimensional surface plot showed both the RADAR blocking fence along with an additional target. An additional observation concerning the operation over the deck whilst the ship is experiencing a quiescent ship motion period. The coupled secondary effect documents minimized air wake confusion. This is owing to fewer ship structure excursions into and out of the air flow. To better define deck airflow around the ship the integration of a Doppler LIDAR instrumented federate is proposed. This is meant to predict the future vessel air wake and look for quiescent periods in this paralleling the vessel motion QPP technique.
This study introduces three new proposed Mission Task Elements (MTEs) - "Big Air", "Giant Slalom", and "Super Combined" - aimed at evaluating handling qualities during low-level and high-speed flight profiles. These MTEs are designed to reflect operational task elements critical in military engagements, particularly where rotorcraft capabilities in evading radar detection and maneuvering at high speeds are paramount. Utilizing piloted simulations with four generic rotorcraft configurations under various flight control laws, the MTEs' effectiveness in exposing aircraft characteristics and handling deficiencies is systematically assessed. The evaluation, conducted with a diverse group of pilots, underscores the MTEs' relevance to real-world scenarios and their robustness in handling qualities assessment across different rotorcraft designs. The study reveals that while some configurations exhibit consistent Level 1 Handling Qualities Ratings (HQRs), others show varied performance, particularly when integrating additional means of velocity control, such as pusher propellers or velocity hold modes. Findings suggest modifications to current evaluation frameworks to better accommodate the dynamic operational requirements of future vertical lift platforms.
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