Adaptive Clutter Cancellation Techniques for Passive Radars

In radar systems, the ambiguity function of the applied illuminator signal essentially determines the detection capabilities. Zero Doppler interference (ZDI) or close targets returns can mask weak target reflections from higher distances. This is particularly the case for passive radars where the illuminator signal is not under the control of the radar designer. In recent times, great efforts have been carried out to research and develop efficiently working filter algorithms. These adaptive algorithms aim to cancel the undesired interference components in order to enhance the useful dynamic range. A number of different algorithms are operating in the space and also in the time domain. Spatial algorithms apply beamforming techniques, while temporal algorithms utilize the available reference signal to suppress the interferences. The main goal of this chapter is to present and compare the available spatial and temporal adaptive interference cancellation techniques in terms of filtering efficiency and computation cost on real-life data

Acceleration of parasitic multistatic radar system using GPGPU

This dissertation details the implementation of PMR [Parasitic Multistatic Radar] signal processing chain in the GPGPU [General Purpose Graphic Processing Units] platform. The primary objective of the project is to accelerate the signal processing chain without compromising the algorithm efficiency and to prove that GPGPUs are a promising platform for parasitic radar signal processing

Doppler-only target tracking for a multistatic radar exploiting FM band illuminators of opportunity

Includes bibliographical referencesCommensal Radar (CR), defined as a subclass of Passive Radar (PR), is a receive only radar that exploits non-cooperative illuminators of opportunity for target detection, location and subsequent tracking. The objective of this thesis is to evaluate the feasibility of using a Frequency Modulation (FM) Broadcast band CR system as a cost effective solution for Air Traffic Control (ATC). An inherent complication by exploiting FM is the low range resolution due to the low bandwidth of FM radio signals. However, due to typical long integration times associated with CR, the frequency domain resolution is typically very good. As a result, measurements of the target's Doppler shift are highly accurate and could potentially make FM illuminators a viable source for ATC purposes. Accordingly, this thesis aims to obtain a comprehensive understanding of using high resolution Doppler measurements to accurately track the position of a target. This objective have been addressed b by performing a comprehensive mathematical analysis for a Doppler only tracking CR system. The analysis is verified with a tracking simulation, in which the Recursive Gauss Newton Filter (RGNF) is used and lastly, a field experiment was conducted to produce tracking results based on real measurement data. Results demonstrated that Doppler only target tracking from real measurement data is possible, even when the initial target state vector is initialised from real measurement data. A good degree of correlation is achieved between the theoretical, simulated and measured results, hence verifying the theoretical findings of this thesis. Ensuring that the observation matrix is properly conditioned in Doppler only tracking applications is important, as failure to do so results in tracking instability. Factors that influence the conditioning of the observation matrix are; the number of receivers used (assuming the basic observation criteria is met) and the placement of the receivers, keeping in mind the possibility of Doppler correlation in the measurements. The possibility of improving an ill-conditioned observation matrix is also demonstrated. In general, tracking filters, for example the RGNF, typically employ time history information and therefore, a direct comparison to the Cramer Rao Lower Bound (CRLB) is unrealistic and accordingly a new theoretical lower bound, called the Cumulative CRLB was derived that does account for time history measurements. Although the best results for this thesis are achieved by using long integration periods (4 s), the effect of Doppler walk was not compensated for and is an aspect that requires further investigation to potentially further improve on the results obtained in this thesis. As a final conclusion for this thesis; the Doppler only target tracking delivered some encouraging results, however a qualification test in the form of an extensive trial period is next required to motivate Doppler only tracking for ATC purposes

Space time adaptive processing in multichannel passive radar

Nowdays, passive bistatic radar (PBR) systems have become a subject of intensive research, owing essentially to its unique features, such as low probability of interception, small size and low cost. Passive radar is a concept where illuminators of opportunity are used. In a bistatic passive radar the main challenges are: estimating the reference signal which is required for detection, mitigating the direct signal, multipath and clutter echoes on the surveillance channel and finally achieving a sufficient SINR to detect targets. This thesis is concerned with the definition and application of adaptive signal processing techniques to a multichannel passive radar receiver. Adaptive signal processing techniques are well known for active pulse radars. A PBR system operates in a continuous mode, therefore the received signal is not avalaible in the classical array elements-slow time-range domain such as in active pulse radar. A major component of this research focuses on demonstrating the applicability of traditional adaptive algorithms, developed in the active radar contest, with passive radar. Firstly a new detailed formulation of the sub optimum “batches algorithm”, used to evaluate the cross correlation function, is proposed. Then innovative 1D temporal adaptive processing techniques are defined extending the matched filter concept to an adaptive matched filter formulation. Afterwards a new spatial adaptive technique, based on the application of the adaptive digital beamforming after the matched filter, is investigated. Finally both 1D spatial and temporal adaptive techniques are extended to 2D space-time adaptive processing techniques. Specifically we demonstrate the applicability of STAP processing to a passive bistatic radar and we show how the classical STAP algorithms, developed for active radar systems, can be applied to a PBR system. The new defined passive radar signal processing architectures are compared with the standard approaches and the effectiveness of the proposed techniques is demonstrated considering both simulated and real data

A scalable real-time processing chain for radar exploiting illuminators of opportunity

Includes bibliographical references.This thesis details the design of a processing chain and system software for a commensal radar system, that is, a radar that makes use of illuminators of opportunity to provide the transmitted waveform. The stages of data acquisition from receiver back-end, direct path interference and clutter suppression, range/Doppler processing and target detection are described and targeted to general purpose commercial off-the-shelf computing hardware. A detailed low level design of such a processing chain for commensal radar which includes both processing stages and processing stage interactions has, to date, not been presented in the Literature. Furthermore, a novel deployment configuration for a networked multi-site FM broadcast band commensal radar system is presented in which the reference and surveillance channels are record at separate locations

Method for Real-Time Signal Selection for Passive Coherent Location Systems

Passive coherent location (PCL) systems use signals of opportunity to perform traditional radar detection, targeting, and tracking functions. Traditionally these signals include FM radio, digital TV, GSM, and GPS because of their availability in most urban environments. A benefit of having an abundance of signals is the ability to choose which of those best meet the desired system intentions. For example, one may want to choose a digital TV signal over an FM radio signal due to its range resolution characteristics. This work presents a novel algorithm for characterizing commercial signals for use in a PCL system. By analyzing each signal\u27s ambiguity function in terms of amplitude, transmitter geometry, range and Doppler resolution, and sidelobe levels, a comparative evaluation can be made to decide which signals are best suited for an intended radar function. In addition, this research shows that multiple signals can be combined in the detection process to increase the probability of detection over that of a single signal. Finally, this research investigates the geometric considerations for PCL systems in terms of bistatic radar geometry. The results show zones of linear and non-linear relationships between time delay, range, and Doppler frequency

Passive detection of moving aerial target based on multiple collaborative GPS satellites

Passive localization is an important part of intelligent surveillance in security and emergency applications. Nowadays, Global Navigation Satellite Systems (GNSSs) have been widely deployed. As a result, the satellite signal receiver may receive multiple GPS signals simultaneously, incurring echo signal detection failure. Therefore, in this paper, a passive method leveraging signals from multiple GPS satellites is proposed for moving aerial target detection. In passive detection, the first challenge is the interference caused by multiple GPS signals transmitted upon the same spectrum resources. To address this issue, successive interference cancellation (SIC) is utilized to separate and reconstruct multiple GPS signals on the reference channel. Moreover, on the monitoring channel, direct wave and multi-path interference are eliminated by extensive cancellation algorithm (ECA). After interference from multiple GPS signals is suppressed, the cycle cross ambiguity function (CCAF) of the signal on the monitoring channel is calculated and coordinate transformation method is adopted to map multiple groups of different time delay-Doppler spectrum into the distance−velocity spectrum. The detection statistics are calculated by the superposition of multiple groups of distance-velocity spectrum. Finally, the echo signal is detected based on a properly defined adaptive detection threshold. Simulation results demonstrate the effectiveness of our proposed method. They show that the detection probability of our proposed method can reach 99%, when the echo signal signal-to-noise ratio (SNR) is only −64 dB. Moreover, our proposed method can achieve 5 dB improvement over the detection method using a single GPS satellite

Adaptive Radio Frequency Interference Mitigation for Passive Bistatic Radar Using OFDM Waveform

High frequency passive bistatic radar (HFPBR) is a novel and promising technique in development. DRM broadcast exploiting orthogonal frequency division multiplexing (OFDM) technique supplies a good choice for the illuminator of HFPBR. HFPBR works in crowded short wave band. It faces severe radio frequency interference (RFI) problem. In this paper, a theoretical analysis of the range-domain correlation of RFI in OFDM-based HF radar is presented. A RFI mitigation method in the range domain is introduced. After the direct-path wave rejection, the interference subspace is constructed using the echo signals at the reserved range bins. Then RFI in the effective range bins is mitigated by the subspace projection, using the correlation among different range bins. The introduced algorithm is easy to perform in practice and the RFI mitigation performance is evaluated using the experimental data of DRM-based HFPBR

Data association using game theory for multi-target tracking in passive bistatic radar

We investigate a game theoretic data association technique for multi-target tracking (MTT) with varying number of targets in a real passive bi-static radar (PBR) environment. The radar measurements were obtained through a PBR developed using National Instrument (NI) Universal Software Radio Peripheral (USRP). We considered the problem of associating target state-estimates-to-tracks for varying number of targets. We use the sequential Monte Carlo probability hypothesis density (SMC-PHD) filter to perform the multi-target tracking in order to obtain the target state estimates and model the interaction between target tracks as a game. Experimental results using this real radar data demonstrate effectiveness of the game theoretic data association for multiple target tracking