Radar detection and tracking of resident space objects in Geosynchronous Earth Orbit (GEO) is challenging due to the loss in sensitivity at the extreme distance of 36,000 km and because of the proliferation of small satellites with decreased radar cross section. One option to increase sensitivity of existing monostatic radar sensors is to employ large aperture radio telescopes configured as bistatic receivers. Moreover, multiple receivers would enable a multi-bistatic configuration with additional performance improvement in terms of both detection and tracking. In this paper we report on long baseline bistatic measurements using the Millstone Hill Radar (MHR) in the USA and the Tracking and Imaging Radar (TIRA) in Germany as transmitters and a number of receivers in Europe: the Sardinia Radio Telescope (SRT) in Italy, the Westerbork Synthesis Radio Telescope (WSRT) in the Netherlands, and multiple antennas of the e-MERLIN array in the United Kingdom. The work presented in this paper has been carried out as part of the Program of Work of the SET-293 Research Task Group (RTG).

Bistatic radars with long baselines are gaining popularity due to the increased interest in Space Domain Awareness, but require significant investment due to the need for large antenna apertures, low noise temperatures, and synchronized clocks. However, radio telescopes can be paired with high-power radars to create long baseline bistatic-multistatic radar networks. This paper describes novel long baseline bistatic measurements using the Millstone Hill Radar (MHR) in the USA and receivers in multiple antennas of the e-MERLIN array in the United Kingdom and the Westerbork Synthesis Radio Telescope (WSRT) in the Netherlands. When provided with basic information about the transmitted waveform, multiple receivers can detect, identify, and track multiple targets. The paper also presents a framework for imaging tumbling targets, demonstrating its effectiveness on real data collected by a novel system concept. This framework integrates coherent integration and Doppler processing techniques to improve signal-to-noise ratio, estimate and correct target motion, and estimate the rotation period and dimensions of tumbling targets, resulting in a clear image of the space object. The presented framework and the proposed system concept have potential to improve bistatic imaging, leading to better characterization of objects in Earth orbits undergoing complex motion, with significant implications for applications such as space domain awareness, space traffic management, and space object characterization.

Accurate motion estimation is a challenging problem for agile radar platforms, even when state-of-the-art inertial navigation sensors (INSs) are used. However, it is an important problem to solve as it can have a large impact on the performance of radar modes, such as synthetic aperture radar (SAR). This study addresses the motion estimation problem of agile radar platforms from the perspective of an omnidirectional radar array. In this study, we perform an analysis on the applicability of an omnidirectional radar array to explicitly estimate the motion of an agile SAR platform and improve imaging quality. Building on existing 1-D SAR motion compensation techniques, we develop a method to estimate the 3-D motion of the radar platform utilizing its height and velocity vector. Using a prototype radar developed at the Netherlands Organisation for Applied Scientific Research, we experimentally verify that using the proposed velocity estimation method alone, we achieve comparable positioning performance to that of a state-of-the-art INS, making it possible to perform INS-free SAR imaging by using arbitrary flight paths. We also show that fusing the radar positioning estimates obtained from the proposed methods with the INS output yields an additional increase in SAR imaging performance, improving the resolvability and detectability of weak targets.

In future military operations, unmanned platforms are anticipated to play a very important role. One of the initiatives of the Royal Netherlands Navy, to prepare for that future, is the development of an organic unmanned aerial vehicle (UAV) capability for maritime operations. This capability should bridge the operational gap between small hand-launched UAVs and large tactical UAVs. Therefore, the focus is on developing operational concepts for intermediate-sized mini-UAVs. These mini-UAVs are envisaged to work together as a unit and carry a variety of payloads, including radar. Within this context, TNO seeks to leverage its compact radar technology for small airborne platforms towards an upgraded compact, multifunctional radar payload for maritime operations.

Synthetic aperture radar (SAR) processing on agile radar platforms requires a very accurate estimate of position due to the unpredictable trajectory of such platforms. This is even more challenging in GPS-denied scenarios where the bias in inertial sensors cannot be compensated. In this study, we propose a 3D radar-aided positioning method based on SAR autofocusing to achieve subresolution positioning accuracy. The proposed multibeam autofocus algorithm builds on multiple SAR motion compensation techniques to generalize and provide a framework for simultaneous omnidirectional imaging and trajectory estimation and correction while taking advantage of the beamforming capabilities of the antenna array. Our initial simulations and proof of concept show that the performance of the proposed approach is adequate even in low signal-to-noise ratio cases.

Detection of command wires is one of several ways of localizing Improvised Explosive Devices (IEDs). Wires are currently detected with hand-held detectors close to the ground, which is dangerous and very time-consuming. This paper describes a new system and method to detect wires in the field much more efficiently, using a multi-channel wide-angle Synthetic Aperture Radar (SAR) mounted on a drone. The radar system is circular, with a 25 cm diameter, and a weight of less than 1 kg. Experimental results with wire pairs laid out in the field demonstrate the detectability of thin wires at the expected angles.

Continuous navigation is crucial for small drones when flying a pre-planned route or during autonomous flight. In scenarios where a global positioning system (GPS) signal is unavailable, drift in the onboard sensors causes the inertial navigation system (INS) to quickly deviate from the planned route. This paper proposes a radar-aided navigation method for small drones which is able to estimate the horizontal velocity and height of the platform independently from GPS. The method is based on an omnidirectional radar system and takes advantage of multi-look processing to increase estimation precision. Simulations and experiments verify that an omnidirectional radar can be used to successfully estimate the velocity and course of a small drone platform.

This paper investigates the benefits of multichannel processing for inverse synthetic aperture radar (ISAR) imaging. There are potential advantages of multichannel processing in radar systems, for example, improved motion estimation, clutter suppression, extraction of supporting information, such as sea wave direction and speed, and ship wake imaging. The current study focuses on two multichannel techniques, namely the oceanic displaced phase centre antenna (ODPCA) and the minimum variance distortionless response (MVDR) techniques, to suppress (ambiguous) clutter and enhance focused target responses even in the proximity of other target responses. These techniques are validated using experimental multichannel radar data from an airborne measurement campaign in a maritime environment.

In this paper, a wire detection algorithm is proposed for synthetic aperture radar (SAR) images. The algorithm is specifically designed for SAR images generated from an agile, drone-mounted, omnidirectional radar array to be used for the detection of improvised explosive devices (IEDs). A multistage approach consisting of denoising, constant false alarm rate (CFAR) thresholding, feature extraction, and automated detection using the Radon transform, is proposed and applied to a set of SAR images with multiple aspect angles. At each detection step, the look-angles of individual pixels are used to remove false alarms, and improve detection accuracy. The algorithm is tested using measured data and provides an acceptable detection performance on straight wire segments even in the presence of a strong background clutter.

This paper presents a new multifunction radar that was specially designed for mini-UAV platforms. The multi-channel radar is omnidirectional, allowing great flexibility in radar- and flight operations. A demonstrator has been built, weighing 800 grams, and consuming 25 W. Flexible SAR, GMTI and novel sensing modes can be demonstrated with this system.

This contribution addresses the problem of designing a sparse active array antenna for spaceborne SAR applications at Ka-band. The main driver for the design is limiting the recurring manufacturing costs associated to the number of active modules, while preserving main performance and insuring a certain level of industrial feasibility. A sparse configuration based on linear subarrays is presented here, which allows a substantial reduction in the number of control points while maintaining the gain and thus the sensitivity of the benchmark regular array.

The AMBER multichannel FMCW SAR enables novel SAR and GMT modes, such as simultaneous Strip and Spot imaging. To enable such advanced modes in an airborne processor for small aircraft, a high performance and power efficient computing solution is required. Multi-channel SAR processing by means of back projection has been implemented on several GPU platforms, and performance tests have been performed. The results indicate that real-time solutions with state-of-the art GPUs are feasible.

An X-band Digital Array Synthetic Aperture Radar for a Short Range Tactical UAV is presented. The Frequency Modulated Continuous Wave radar principle in combination with digital beam forming over 24 receive channels is used to achieve low power and advanced imaging SAR capabilities on small platform. Novel SAR imaging modes are discussed, and some examples are given. Real-time processing for such a system becomes a challenging task, and a practical example of an approach using GPU processing is presented in this paper.

A lightweight radar system, suitable for use on board small airborne platforms, has been built and tested. The radar system comprises a digital receive array, offering full beam forming flexibility at the cost of high data rates and heavy processing loads. In this paper, the requirements and architecture for multi-channel SAR processing are discussed and processing results from recent airborne campaigns are presented.

In this paper the performance of a combined Constant False Alarm Rate (CFAR) Compressive Sensing (CS) radar detector is investigated. Using the properties of the Complex Approximate Message Passing (CAMP) algorithm, it is demonstrated that the behavior of the CFAR processor can be separated from that of the non-linear l(1)-norm recovery, thus allowing the use of standard radar equations to evaluate detection performance. The CS CFAR processor has been evaluated under different interference scenarios using both the Cell Averaging (CA) and Order Statistic (OS) CFAR detectors. The performance of the CS CFAR processor is also compared to that of an l(1)-norm detector using both simulations and experimental data.

Rockwell Collins France (RCF) radar department is currently developing, in close collaboration with TNO in The Hague, The Netherlands, a Frequency Modulated Continuous Wave (FMCW) radar sensor dedicated to Obstacle Warning function and potentially to air traffic detection. The sensor combines flood light illumination and digital beam forming to accommodate demanding detection and coverage requirements. Performances have been evaluated in flight tests and results prove that such a radar sensor is a good candidate for the Sense Function of Sense & Avoid Systems onboard UAV.

We consider the problem of target detection from a set of Compressive Sensing (CS) radar measurements corrupted by additive white Gaussian noise. We propose two novel architectures and compare their performance by means of Receiver Operating Characteristic (ROC) curves. Using asymptotic arguments and the Complex Approximate Message Passing (CAMP) algorithm, we characterize the statistics of the `1-norm reconstruction error and derive closed form expressions for both the detection and false alarm probabilities of both schemes. Of the two architectures, we demonstrate that the best one consists of a reconstruction stage based on CAMP followed by a detector. This architecture, which outperforms the `1-based detector in the ideal case of known background noise, can also be made fully adaptive by combining it with a conventional Constant False Alarm Rate (CFAR) processor. Using the state evolution framework of CAMP, we also derive Signal to Noise Ratio (SNR) maps that, together with the ROC curves, can be used to design a CS-based CFAR radar detector. Our theoretical findings are confirmed by means of both Monte Carlo simulations and experimental results.

An X-band Digital Array Synthetic Aperture Radar for a Short Range Tactical UAV is presented. This system is demonstrated on a manned helicopter and motor glider. The Frequency Modulated Continuous Wave radar principle in combination with digital beam forming over 24 receive channels is used to meet the stringent payload requirements of Tactical UAVs with respect to Size, Weight, Power and Cost. The paper presents the concept, key parameters (15 cm resolution, 5 km maximum range, 6 kg, 7×30×40 cm3 and 50W dissipation), functional capabilities and experimental results.

A light weight SAR, suitable for use on short range tactical UAV, has been designed and built. The system consists of a fully digital receive array, and a very compact active transmit antenna. The approximate weight of the complete system is 6 kg, with power consumption below 75 W, depending on the required data acquisition volume. This X-band system is designed to provide an image resolution down to 10–15 cm at a maximum range of approximately 5 km. The design is described, and initial ground test results are presented.

In this paper we develop the first Compressive Sensing (CS) adaptive radar detector. We propose three novel architectures and demonstrate how a classical Constant False Alarm Rate (CFAR) detector can be combined with l(1)-norm minimization. Using asymptotic arguments and the Complex Approximate Message Passing (CAMP) algorithm we characterize the statistics of the l(1)-norm reconstruction error and derive closed form expressions for both the detection and false alarm probabilities. We support our theoretical findings with a range of experiments that show that our theoretical conclusions hold even in non-asymptotic setting. We also report on the results from a radar measurement campaign, where we designed ad hoc transmitted waveforms to obtain a set of CS frequency measurements. We compare the performance of our new detection schemes using Receiver Operating Characteristic (ROC) curves.