Passive radar for GMTI

Passive radar systems operate by exploiting signals of opportunity that are designed for other applications, such as broadcasting, communications, and satellite navigation. Passive radars have recently attracted attention in military applications, mainly because of their covertness, low-cost implementation, and no requirement of signal emissions [1], [2]. Whereas the primary use of passive radars is in the defense sector, these same features make them attractive in commercial applications. Unlike conventional active radar systems, which typically operate in a monostatic mode, passive radar can operate in a multistatic mode (thus called passive multistatic radar, or PMR) by using multiple transmitters. Multiple networked receivers can also be exploited for an expanded PMR network size.

Distributed passive radars confront the high dynamic range challenge by splitting the receiver physically to provide high SNR samples of the transmitter as well as reduced cochannel interference. The receivers are mutually coherent and must therefore exchange voltage level data for computation of the cross-ambiguity function. The data bandwidth required for full- precision (16 bit) data is about 2 Mbps to support for a single channel. This data bandwidth demand can stress the cost and latency of distributed passive radars. Therefore we investigate the effect the sensitivity of a passive radar system using several methods to compress the voltage level samples prior. (4 pages)

The present work illustrates the Fraunhofer FHR contribution to the MAPIS project field trials held in Livorno in June 2017. The MAPIS project, funded by EDA, aims at demonstrating radar imaging capability of passive radar systems in a (military) maritime scenario. In particular, two different Passive Bistatic Radar (PBR) systems, one exploiting Digital Video Broadcasting - Terrestrial (DVB-T) signals, the other one exploiting Digital Video Broadcasting - Satellite (DVB-S) signals have been used to experimentally assess the imaging performance. This paper describes the systems developed by Fraunhofer FHR and used during the trials. In addition, a small overview of the trial itself is provided together with some preliminary results concerning the passive radar imaging.

Utilizing digital beam forming (DBF) on transmit and receive, the multiple-input multiple-output (MIMO) radar can be applied to ground moving target indication (GMTI) and can provide an efficient way to improve the GMTI performance. The operating pattern is very significant for the MIMO radar GMTI. For the traditional GMTI pattern, there is a conflict of the wider swath and narrower clutter bandwidth. The observation area can be broadened with MIMO techniques by scanning. This paper designs an effective pattern with the simultaneous transmission of multi-phase-centre multi-sub-band signals as well as beam scanning in each pulse, which provide an efficient way to settle the conflict. By beam scanning in pulse, the new pattern has wider azimuth swath, shorter revisiting period, larger coherent processing interval (CPI) number and higher SCNR. By MIMO technology, more equivalent phase centres and longer efficient baselines can be formed, so the performance of GMTI can be improved. The principle of space-time-frequency adaptive processing (STFAP) is analysed, simulation results are presented to prove the superiority of MIMO radar in clutter suppression and GMTI. Analysis of the results indicates improved detection performance with the new pattern compared to the conventional approach.

This chapter is concerned with the study of signal processing techniques and operational strategies for passive radar systems mounted onboard moving platforms and aimed at ground moving target indication (GMTI) applications. Specifically, the attention is focused on space-time adaptive processing (STAP) methodologies for systems equipped with multiple channels on receive. The spatial degrees of freedom are adaptively exploited for space-time clutter cancellation and slow-moving target detection and direction of arrival estimation. Specific solutions are devised and integrated into the typical signal processing architecture of passive radar to address the main limitations deriving from the passive bistatic framework.

Passive coherent location (PCL), passive covert radar (PCR), passive bistatic radar (PBR), passive radar, parasitic radar, and hitchhiking radar are all common names for passive radar systems exploiting cooperative, noncooperative transmitters, or transmitters of opportunity, [1, pp. 3]. Recent review of the various names resulted in the compromise PBR, [2, pp. 248]. However, it should be noted that the PCL name is still being used for full systems like Lockheed Martin's - Silent Sentry [3], [4], Thales' - Homeland alerter 100 [5], [6] seen in Figure 1, and Airbus “Passive Radar” [7]–[15]. The PCL systems may be considered as systems of PBR systems. This work focuses on the system perspective of the technology, i.e. PCL, while relying on the technical depths of the PBR technology.

In multistatic passive radar systems, the Cramer–Rao lower bound (CRLB) can be used to select the optimal illuminator of opportunity so that it provides the best estimation accuracy for target parameters. In this Letter, the monostatic and bistatic modified Cramer–Rao lower bound (MCRLB) for the Advanced Television Systems Committee (ATSC) signal, which is the pervasive digital television signal of opportunity for North American passive radar systems, is derived using the relationship between the ambiguity function of a signal and its CRLB. It is shown that the derived bistatic MCRLB for the range and velocity measurements can be used to select the optimal illuminator that exhibits the lowest bounds at each region. Examples are provided in the Columbus, OH area where the Ohio State University passive radar is located.

Multidimensional waveform encoding is a new multiple-input multiple-output (MIMO) technique for remote sensing. The orthogonality is acquired by digital beamforming in elevation. It has a potential to enhance ground moving target indication (GMTI) performance due to the larger along-track virtual array of the radar system. This paper proposed two modes for GMTI based on multidimensional waveform encoding: intrapulse azimuth beam scanning and intrapulse azimuth encoding. Compared to the phased-array GMTI systems, the mode with intrapulse azimuth beam scanning has improved area search rates, and the mode with intrapulse azimuth encoding has improved minimal detectable velocity performance. Theoretical analysis and simulation results demonstrate that the proposed modes have better performance than the phased-array GMTI systems.

Passive radar systems are proposed as ground traffic control and monitoring tools in modern urban areas. These radars use communication networks transmitters available in the area of interest, instead of dedicated ones. The absence of a transmitter reduces dramatically the cost of development, deployment and maintenance, making feasible passive radar sensor networks for covering modern cities complex scenarios. They do not generate electromagnetic compatibility problems, and, more important, they are not associated with health issues. The illuminator selection is one of the most important tasks. The transmitted waveform, the transmitted power, the availability or the coverage areas are critical elements that are out of the control of the radar designer. The IDEPAR demonstrator is used in an urban environment to prove the traffic monitoring capabilities of passive radars exploiting Direct Video Broascasting -Terrestrial transmitters.

This paper examines the feasibility of 4G (LTE)-based passive radar for detecting ground moving targets. Specifically, the focus of this paper is to describe the proposed LTE-based passive radar system and to conduct an experiment using a real LTE eNB transmitter as an illumination source. Seven scenarios were carried out to investigate the detection performance of the proposed system on moving targets. Each scenario had different types of ground targets moving with a variety of speeds and directions. The experimental results showed that the LTE-based passive radar system has the capability to detect typical ground targets/objects like cars, motorbikes and humans moving with different speeds, trajectories and ranges. The positive results opened up a new frontier for passive radar systems to be used in many potential applications, including border protection, microwave fences, monitor of buildings and others.

Non-contact breathing monitoring systems are very attractive for a range of e-Healthcare applications. This paper proposes a passive radar based system for measuring human breathing rate. A novel signal processing method is introduced to extract breathing rate based on micro Doppler derived from cross ambiguity function (CAF). The passive radar system is built within a software defined radio (SDR) platform. The proposed system uses opportunistically energy harvesting transmitter as an illumination signal. Passive detection is compared and verified using the ground truth from clinical chest belt respiration detector. Two experiments have been conducted to show the feasibility of passive detection system in the line of sight and also through-wall conditions. We conclude that a low frequency narrow band signal with non-contact passive detection can offer a realistic alternative to UWB based radars for future e-Healthcare passive sensing applications.

In our earlier study, an energy-efficient passive UAV radar imaging system was formulated, which comprehensively analyzed the system performance. In this article, based on the evaluator set, a mission planning framework for the underlying energy-efficient passive UAV radar imaging system is proposed to achieve optimized mission performance for a given remote sensing task. First, the mission planning problem is defined in the context of the proposed synthetic aperture radar (SAR) system and a general framework is outlined, including mission specification, illuminator selection, and path planning. It is found that the performance of the system is highly dependent upon the flight path adopted by the UAV platform in a 3-D terrain environment, which offers the potential of optimizing the mission performance by adjusting the UAV path. Then, the path planning problem is modeled as a single-objective optimization problem with multiple constraints. Path planning can be divided into two substages based on different mission orientations and low mutual correlation. Based on this property, a path planning method, called substage division collaborative search (Sub-DiCoS), is proposed. The problem is divided into two subproblems with the corresponding decision space and subpopulation, which significantly relax the constraints for each subproblem and facilitates the search for feasible solutions. Then, differential evolution and the whole-stage best guidance technique are devised to cooperatively lead the subpopulations to search for the best solution. Finally, simulations are presented to demonstrate the effectiveness of the proposed Sub-DiCoS method. The result of the mission planning method can be used to guide the UAV platform to safely travel through a 3-D rough terrain in an energy-efficient manner and achieve optimized SAR imaging and communication performance during the flight.

Multiple-input multiple-output synthetic aperture radar (MIMO SAR) system has drawn considerable attention for its wider detected swath without decreasing PRF compared to the traditional multichannel synthetic aperture radar (MC-SAR) system. For MIMO SAR system, how to extract the matched signal or suppress the unmatched interferences is the foremost task. Using the OFDM chirp signals as the transmitted signals, the robust principal component analysis (RPCA) based method can be employed for ground moving target indication (GMTI) with no need for separating the matched signal and unmatched interferences. The simulation demonstrates the effectiveness of RPCA based method for GMTI in MIMO SAR system.

A common problem in ground moving target indication (GMTI) radar is detecting a target with even a large radar cross section (RCS) when its line-of-sight velocity falls below the minimum detectable velocity (MDV) for that radar system. In a cooperative scenario, a target may employ a tagging device, which can shift or spread its Doppler signature to become more detectable. In this paper we develop a bound on the minimum modulatable RCS of a passive (non-amplifying) device needed to be detectable as a function of radar and mode parameters, and compute this bound for specific GMTI and SAR radar modes.

With the rapid development of lightweight unmanned aerial vehicles (UAVs), the combination of UAVs and ground moving target indication (GMTI) radar systems has received great interest. In GMTI, moving target relocation is an essential requirement, because the positions of the moving targets are usually displaced. For a multichannel radar system, the position of moving targets can be accurately obtained by estimating their interferometric phase. However, the high position accuracy requirements of antennas and the computational resource requirements of algorithms limit the applications of relocation algorithms in UAV-borne GMTI radar systems. In addition, the clutter’s interferometric phase can be severely affected by the undesired phase error in the site. To overcome these issues, we propose an improved knowledge-based (KB) algorithm. In the algorithm, moving targets can be relocated by comparing their interferometric phase with the clutter’s phase. As for the undesired phase error, the algorithm first employs a random sample consensus (RANSAC) algorithm to iteratively filter the outliers. Compared with other classic relocation algorithms, the proposed algorithm shows better relocation accuracy and can be applied in real-time applications. The performance of the proposed improved KB algorithm was evaluated using both simulated and real experimental data.