Multistatic Passive Radar System Research Articles

GLRT‐based compressive subspace detectors in single‐frequency multistatic passive radar systems

AbstractThe authors study the problem of compressive target detection in a single‐frequency network (SFN)‐based multistatic passive radar system (MS‐PRS) consisting of multiple illuminators of opportunity (IOs) and one receiver. Firstly, a generalised likelihood ratio test (GLRT)‐based SFN‐based compressive subspace detector (SFN‐CSD) is derived by exploiting the sparsity of the target echoes for the case of known noise variance. When the noise variance is unknown, an SFN‐based unknown‐noise (UN) compressive subspace detector is proposed, referred to as the SFN‐UNCSD. Moreover, closed‐form expressions of the probability of false alarm and detection of the proposed detectors are deriived. It is proved that the SNF‐UNCSD has a constant false alarm rate (CFAR) property. Finally, numerical simulations are conducted to verify the theoretical analysis and illustrate the performance of the proposed detector relative to several benchmark detectors.

SkyWatch: A Passive Multistatic Radar Network for the Measurement of Object Position and Velocity

Quantitative three-dimensional (3D) position and velocity estimates obtained by passive radar will assist the Galileo Project in the detection and classification of aerial objects by providing critical measurements of range, location, and kinematics. These parameters will be combined with those derived from the Project’s suite of electromagnetic sensors and used to separate known aerial objects from those exhibiting anomalous kinematics. SkyWatch, a passive multistatic radar system based on commercial broadcast FM radio transmitters of opportunity, is a network of receivers spaced at geographical scales that enables estimation of the 3D position and velocity time series of objects at altitudes up to 80[Formula: see text]km, horizontal distances up to 150[Formula: see text]km, and at velocities to [Formula: see text][Formula: see text]km/s ([Formula: see text][Formula: see text]Mach). The receivers are designed to collect useful data in a variety of environments varying by terrain, transmitter power, relative transmitter distance, adjacent channel strength, etc. In some cases, the direct signal from the transmitter may be large enough to be used as the reference with which the echoes are correlated. In other cases, the direct signal may be weak or absent, in which case a reference is communicated to the receiver from another network node via the internet for echo correlation. Various techniques are discussed specific to the two modes of operation and a hybrid mode. Delay and Doppler data are sent via internet to a central server where triangulation is used to deduce time series of 3D positions and velocities. A multiple receiver (multistatic) radar experiment is undergoing Phase 1 testing, with several receivers placed at various distances around the Harvard–Smithsonian Center for Astrophysics (CfA), to validate full 3D position and velocity recovery. The experimental multistatic system intermittently records raw data for later processing to aid development. The results of the multistatic experiment will inform the design of a compact, economical receiver intended for deployment in a large-scale, mass-deployed mesh network. Such a network would greatly increase the probability of detecting and recording the movements of aerial objects with anomalous kinematics suggestive of Unidentified Aerial Phenomena (UAP).

Order-Statistic Based Target Detection with Compressive Measurements in Single-Frequency Multistatic Passive Radar

This paper considers the problem of compressive target detection with direct-path interference (DPI) and clutter in a single-frequency network (SFN) based multistatic passive radar system (MS-PRS). Specifically, a measurement matrix is designed to jointly obtain compressive observations and remove the DPI and clutter. We first analyze a compressive subspace detector which assumes the target support is known. When the target supports cannot be accurately obtained, an order-statistic (OS) based detector, referred to as the OSOMP, is proposed by using the orthogonal matching pursuit (OMP) algorithm to estimate the target support, and then projecting the compressive observations into the estimated subspace. Since OMP applies an iterative ranking process to select the components/atoms of the dictionary, the OSOMP test variable is an order statistic, which has a non-convergent distribution. To cope with this problem, a modified test statistic for the OSOMP detector is presented and an analytical expression for the probability of false alarm is obtained. We further discuss the minimum number of iterations required by the OSOMP algorithm to achieve the desired probability of detection and false alarm. Numerical simulations are conducted to verify the theoretical analysis and illustrate the performance of the proposed detector relative to several benchmark detectors.

Compressive Subspace Detectors Based on Sparse Representation in Multistatic Passive Radar Systems

This paper considers the problem of target detection by using compressive observations in a multistatic passive radar system (MS-PRS) consisting of one non-cooperative illuminator of opportunity, one reference channel, and multiple receivers. We first jointly design the measurement matrix for each receiver to obtain the compressive observations, thus making the echo signals at different receivers corresponding to the same target share the same target support indices (SSIs). Following this, a generalized likelihood ratio test (GLRT) based complex-valued compressive subspace detector (CSD) is provided given the prior of receiver noise variance. To further improve the detection performance, we develop a linear-fusion based CSD (LFCSD) by designing a set of weights at the fusion center. For the scenario of unknown noise variance, we continue to derive two GLRT-based unknown-noise CSDs (UNCSD). Specifically, we consider two cases based on whether the noise variance of each receiver is equal, referred to as the UNCSD1 and UNCSD2, respectively. Besides, we provide closed-form expressions of the probability of false alarm and detection of the proposed detectors. It is shown that the proposed UNCSD1 and UNCSD2 have constant false alarm rate (CFAR) properties. Finally, numerical simulation results show that the proposed detectors outperform the generalized coherence correlation (GCC) detector and the energy detector (ED) in low and moderate signal-to-noise ratio (SNR) regions.

A Centralized Ship Localization Strategy for Passive Multistatic Radar Based on Navigation Satellites

This letter focuses on ship target localization using a multistatic passive radar system based on navigation satellites opportunistic illuminators. In such systems, the typical approach to localize the targets is taking peripheral decisions at each bistatic channel to detect the target followed by bistatic ranges intersection. In contrast, here we consider a centralized approach in order to jointly detect and localize the ship target of interest. The proposed approach entirely operates in a Cartesian plane representing the surveyed maritime area and it is able to combine the signals pertaining the different bistatic links despite the variation of the e.m. response of the targets, typically occurring in the framework under consideration as the target is illuminated by multiple (and possibly widely separated) transmitters viewing angles. Moreover, the hypothesis of point-like targets is here replaced with the more realistic case of extended targets (i.e., occupying more than one resolution cell). The ship localization effectiveness of the method is proved via both synthetic and experimental datasets.

Multistatic Passive Radar Multi-target Tracking Under Target-measurement-illuminator Data Association Uncertainty

Different from the traditional multi-target tracking problem which has the measurements to targets data association uncertainty problem, the multistatic passive radar multi-target tacking system has the additional measurements to illuminators data association uncertainty problem, which means the data association relationship is three dimensional. A novel target-measurement-illuminator Probabilistic Multiple Hypothesis Tracking (PMHT) algorithm is proposed, which introduces a new data association variable to represent the data association relationship. The proposed algorithm is based on the Expectation-Maximization (EM). To handle the nonlinear problem of range-Doppler measurements, the Unscented Kalman Smoother (UKS) is used to get the multi-targets’ estimated states. To increase the data association accuracy, the measurements are set to mixture Gaussian distribution. Simulation results show that for the FKIE passive radar data set, the proposed algorithm can track multi-targets effectively in dense clutter environment.

Cooperative Fusion Based Passive Multistatic Radar Detection.

Passive multistatic radars have gained a lot of interest in recent years as they offer many benefits contrary to conventional radars. Here in this research, our aim is detection of target in a passive multistatic radar system. The system contains a single transmitter and multiple spatially distributed receivers comprised of both the surveillance and reference antennas. The system consists of two main parts: 1. Local receiver, and 2. Fusion center. Each local receiver detects the signal, processes it, and passes the information to the fusion center for final detection. To take the advantage of spatial diversity, we apply major fusion techniques consisting of hard fusion and soft fusion for the case of multistatic passive radars. Hard fusion techniques are analyzed for the case of different local radar detectors. In terms of soft fusion, a blind technique called equal gain soft fusion technique with random matrix theory-based local detector is analytically and theoretically analyzed under null hypothesis along with the calculation of detection threshold. Furthermore, six novel random matrix theory-based soft fusion techniques are proposed. All the techniques are blind in nature and hence do not require any knowledge of transmitted signal or channel information. Simulation results illustrate that proposed fusion techniques increase detection performance to a reasonable extent compared to other blind fusion techniques.

Target Localization Based on Bistatic T/R Pair Selection in GNSS-Based Multistatic Radar System

To cope with the increasingly complex electromagnetic environment, multistatic radar systems, especially the passive multistatic radar, are becoming a trend of future radar development due to their advantages in anti-electronic jam, anti-destruction properties, and no electromagnetic pollution. However, one problem with this multi-source network is that it brings a huge amount of information and leads to considerable computational load. Aiming at the problem, this paper introduces the idea of selecting external illuminators in the multistatic passive radar system. Its essence is to optimize the configuration of multistatic T/R pairs. Based on this, this paper respectively proposes two multi-source optimization algorithms from the perspective of resolution unit and resolution capability, the Covariance Matrix Fusion Method and Convex Hull Optimization Method, and then uses a Global Navigation Satellite System (GNSS) as an external illuminator to verify the algorithms. The experimental results show that the two optimization methods significantly improve the accuracy of multistatic positioning, and obtain a more reasonable use of system resources. To evaluate the algorithm performance under large number of transmitting/receiving stations, further simulation was conducted, in which a combination of the two algorithms were applied and the combined algorithm has shown its effectiveness in minimize the computational load and retain the target localization precision at the same time.

Maritime Target Localization From Bistatic Range Measurements in Space-Based Passive Radar

In this article, localization of a maritime target using a passive multistatic radar system, consisting of a single receiver and a number of satellites as its transmitters, is investigated. The set of communication satellites and also the global navigation satellite system (GNSS), including GPS, Glonass, and Galileo, are employed as illuminators of opportunity. In the receiver, the reflected signals from the target along with the direct signal from the satellites are employed to extract a set of bistatic range measurements. Leveraging these measurements and the satellite’s position information, a novel localization method considering zero height of maritime target and appropriate combination of the measurement signals is presented. The proposed method is efficient for localization of maritime targets in cases with arbitrary bistatic range accuracy. The results of numerical simulations confirm the efficiency of the proposed method and its superior performance in comparison with the state-of-the-art methods.

LTE‐based multistatic passive radar system for UAV detection

Using the frequency-division duplex long-term evolution (LTE)-based multistatic passive radar system for unmanned aerial vehicle (UAV) detection is considered. The typical outdoor terrestrial LTE eNodeBs and the broadband direct air-to-ground communications network eNodeBs are used to cover the UAVs at the low altitude and at the medium-high altitude, respectively. The bistatic range measurements are obtained from multiple eNodeBs, and the hyperbolic positioning technique is used for target localisation. Since the existing LTE downlink signals are more suitable for the transmission of the communication data rather than target detection, a new LTE downlink signal feature termed as target localisation reference signals (TLRS) is designed exclusively for the passive radar application using the Costas frequency coding and the P4 phase coding. Compared with the existing LTE downlink signal features, the TLRS have better waveform properties and could potentially provide much higher target detection accuracy. Meanwhile, the TLRS occupy only 0.266% LTE downlink time–frequency resources within a time frame of 1 s when the bandwidth is 10 MHz and have no negative impact on the normal LTE downlink data transmission.

Weak target echo detection based on low rank signal in multi-static passive radar

This paper considers weak target echo detection in multi-static passive radar system. A new detector adopting a test statistic based on the cross correlation of the principal left singular vectors of the reference and surveillance signal-plus-noise matrices is devised. Due to the exploitation of the low-rank structure of transmitted signal, it offers better performance than traditional detector. Simulation results verify the effectiveness of the proposed detection method.

Experimental research of drone monitoring using multi‐static passive radar

The rapid development of the drone poses potential dangers and challenges for air traffic safety. The reliable monitoring of the drones has attracted much attention around the world in recent years. This study investigates the feasibility and practicability of the multi-static passive radar (MPR) system for the drone monitoring. The authors conduct a series of drone-monitoring experiments using a digital-television-based MPR system developed in Wuhan University. The typical experimental results of the drone detection and tracking are discussed in this study in detail. The agreement is achieved between the experimental results and the ground truth from the global position system of the drones. It demonstrates advantages and prospects of the drone monitoring by the MPR system.

Joint Detection and Localization of Vessels at Sea With a GNSS-Based Multistatic Radar

This paper addresses the exploitation of global navigation satellite systems as opportunistic sources for the joint detection and localization of vessels at sea in a passive multistatic radar system. A single receiver mounted on a proper platform (e.g., a moored buoy) can collect the signals emitted by multiple navigation satellites and reflected from ship targets of interest. This paper puts forward a single-stage approach to jointly detect and localize the ship targets by making use of long integration times (tens of seconds) and properly exploiting the spatial diversity offered by such a configuration. A proper strategy is defined to form a long-time and multistatic range and Doppler (RD) map, where the total target power can be reinforced with respect to, in turn, the case in which the RD map is obtained over a short dwell and the case in which a single transmitter is employed. The exploitation of both the long integration time and the multiple transmitters can greatly enhance the performance of the system, allowing counteracting the low-power budget provided by the considered sources representing the main bottleneck of this technology. Moreover, the proposed single-stage approach can reach superior detection performance than a conventional two-stage process where peripheral decisions are taken at each bistatic link and subsequently the localization is achieved by multilateration methods. Theoretical and simulated performance analysis is proposed and also validated by means of experimental results considering Galileo transmitters and different types of targets of opportunity in different scenarios. Obtained results prove the effectiveness of the proposed method to provide detection and localization of ship targets of interest.

Refining Inaccurate Transmitter and Receiver Positions Using Calibration Targets for Target Localization in Multi-Static Passive Radar.

Transmitter and receiver position errors have been known to significantly deteriorate target localization accuracy in a multi-static passive radar (MPR) system. This paper explores the use of calibration targets, whose positions are known to the MPR system, to counter the loss in target localization accuracy arising from transmitter/receiver position errors. This paper firstly evaluates the Cramér–Rao lower bound (CRLB) for bistatic range (BR)-based target localization with calibration targets, which analytically indicates the potential of calibration targets in enhancing localization accuracy. After that, this paper proposes a novel closed-form solution, which includes two steps: calibration step and localization step. Firstly, the calibration step is devoted to refine the inaccurate transmitter and receiver locations using the BR measurements from the calibration targets, and then in the calibration step, the target localization can be accurately achieved by using the refined transmitter/receiver positions and the BR measurements from the unknown target. Theoretical analysis and simulation results indicate that the proposed method can attain the CRLB at moderate measurement noise level, and exhibits the superiority of localization accuracy over existing algorithms.

Target localisation from bistatic range measurements in multistatic passive radar using MDS

The target localisation in a multistatic passive radar system using bistatic range measurements from multiple transmitter–receiver pairs is considered. A novel closed-form solution employing multidimensional scaling (MDS) analysis technique is proposed, which is based on the optimisation of a cost function related to the scalar product matrix in the classical MDS framework. The proposed solution is robust to large measurement noise. Simulation results demonstrate the proposed solution achieves a significant performance improvement over existing spherical interpolation, spherical intersection and two-step weighted least squares methods, and attains the Cramer–Rao lower bound at a relatively higher measurement noise level before the threshold effect occurs.

Cramér–Rao lower bound for ATSC signal‐based passive radar systems

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.

LTE-based passive multistatic radar for high-speed railway network surveillance: design and preliminary results

AbstractWith the aim of performing perimeter surveillance of high-speed railway networks, this paper presents the design of a passive multistatic radar system based on the use of Long-Term Evolution (LTE) downlink signals as the illumination of opportunity. Taking into account the specifications and standard of the LTE system, the ambiguity function of measured downlink signals is analyzed in terms of range and Doppler resolution, ambiguities, and sidelobe level. The deployment of the proposed passive radar is flexible and scalable, and it is based on multichannel software defined radio receivers that obtain the reference and surveillance signals by means of digital beamforming. The signal processing and data fusion are based, respectively, on the delay-Doppler cross-correlation with the reconstructed reference signals and a two-stage tracking at sensor and central level. Finally, the performance of the proposed system is estimated in terms of its maximum detection range and simulation results of the detection of moving targets are presented, demonstrating its technical feasibility for the short-range detection of pedestrians, vehicles, and small drones.

Calibrating the Transmitter and Receiver Location Errors for Moving Target Localization in Multistatic Passive Radar

The presence of transmitter and receiver location uncertainties has been known to remarkably deteriorate the target localization accuracy in multi-static passive radar (MPR) system. This paper explores the use of calibration targets, the positions and velocities of which are known to the MPR system, to counter the loss in target localization accuracy arising from the transmitter/receiver location uncertainties. We firstly evaluate the Cramer-Rao lower bound (CRLB) for bistatic range (BR) and bistatic range rate (BRR)-based target localization in the presence of calibration targets, which analytically indicates the potential of calibration targets in enhancing localization accuracy. After that, a novel closed-form solution is proposed for target localization using the BR and BRR measurements from the unknown target as well as the additional BR and BRR measurements from the calibration targets. The proposed solution includes two processing steps, referred to as calibration step and localization step respectively. The calibration step is devoted to refine the inaccurate transmitter and receiver locations using the BR and BRR measurements from the calibration targets, and then the localization step is devoted to determine the target position and velocity based on the refined transmitter/receiver locations and the BR/BRR measurements from the unknown target. The accuracy of proposed solution is shown analytically to accomplish the CRLB under sufficiently small BR/BRR measurement noises and transmitter/receiver location errors. Simulation results verify the effectiveness and superiority of the proposed solution over existing algorithms.

DA-PMHT for Multistatic Passive Radar Multitarget Tracking in Dense Clutter Environment

Multistatic passive radar exploits illuminators of opportunity such as radio or television stations for tracking airborne targets. This paper focuses on broadcast signals in a single frequency network modulated according to the digital audio/video broadcasting (DAB/DVB) standards. The main challenge is that one has to solve the measurement-to-illuminator association ambiguity in addition to the conventional measurement-to-target association ambiguity, which increases data association complexity greatly. In this paper, to solve the additional measurement-to-illuminator data association ambiguity, a novel deterministic annealing probabilistic multi-hypothesis tracker based on the extended Kalman filter is proposed. The proposed algorithm works directly in the original three-dimensional Cartesian space, and can efficiently handle a large number of association hypotheses among the targets, measurements, and illuminators in a natural way, also it is computationally attractive. As the angular measurement is not available or often of extremely poor quality, this paper assumes measurements of bistatic range and range rate and does not process bearing information. The simulation results show that the proposed algorithm works reasonably well in dense clutter environment for multistatic passive radar system.

An Approximate Maximum Likelihood Algorithm for Target Localization in Multistatic Passive Radar

This paper addresses the problem of target localization using Bistatic range (BR) measurements in a distributed multistatic passive radar system. The rangebased positioning technique employs multiple transmitterreceiver pairs, which provide separate BR measurements. Based on the Maximum likelihood (ML) function, an efficient algebraic Approximate maximum likelihood (AML) algorithm for single target localization is proposed. The closed-form AML solution has neither initial condition requirements nor convergence difficulty. Simulations are included to compare its performance to that of the CramerRao lower bound (CRLB) and the Two-step Weighted least squares (TS-WLS) algorithm. The proposed method is shown to be able to achieve the CRLB accuracy under Gaussian measurement noise. It is more robust to noise than the TS-WLS method, and presents relative insensitivity to target-sensor geometry.