Coarse-fine joint target parameter estimation method based on AN-RSC in OFDM passive radar

In this paper,we study the accuracy of delay-Doppler parameter estimation of targets in a passive radar using orthogonal frequency division multiplexing(OFDM)signal.A coarse-fine joint estimation method is proposed to achieve better estimation accuracy of target parameters without excessive computational burden.Firstly,the modulation symbol domain(MSD)method is used to roughly estimate the delay and Doppler of targets.Then,to obtain high-precision Doppler estimation,the atomic norm(AN)based on the multiple measurement vectors(MMV)model(MMV-AN)is used to manifest the signal sparsity in the continuous Doppler domain.At the same time,a reference signal compensation(RSC)method is presented to obtain highprecision delay estimation.Simulation results based on the OFDM signal show that the coarse-fine joint estimation method based on AN-RSC can obtain a more accurate estimation of target parameters compared with other algorithms.In addition,the proposed method also possesses computational advantages compared with the joint parameter estimation.

Equalization Reconstruction Algorithm Based on Reference Signal Frequency Domain Block Joint for DTMB-Based Passive Radar

Channel equalization plays a pivotal role within the reconstruction phase of passive radar reference signals.In the context of reconstructing digital terrestrial multimedia broadcasting(DTMB)signals for low-slow-small(LSS)target detection,a novel frequency domain block joint equalization algorithm is presented in this article.From the DTMB signal frame structure and channel multipath transmission characteristics,this article adopts a unconventional approach where the delay and frame structure of each DTMB signal frame are reconfigured to create a circular convolution block,facilitating concurrent fast Fourier transform(FFT)calculations.Following equalization,an inverse fast Fourier transform(IFFT)-based joint output and subsequent data reordering are executed to finalize the equalization process for the DTMB signal.Simulation and measured data confirm that this algorithm outperforms conventional techniques by reducing signal errors rate and enhancing real-time processing.In passive radar LSS detection,it effectively suppresses multipath and noise through frequency domain equalization,reducing false alarms and improving the capabilities of weak target detection.

Ambiguity function analysis and side peaks suppression of Link16 signal based passive radar

Link16 data link is the communication standard of the joint tactical information distribution system(JTIDS)used by the U.S.military and North Atlantic Treaty Organization,which is applied as the opportunistic illuminator for passive radar in this paper.The time-domain expression of the Link16 signal is established,and its ambiguity function expression is derived.The timedelay dimension and Doppler dimension side peaks of which lead to the appearance of the false target during target detection.To solve the problem,the time-delay dimension and Doppler dimension side peaks suppression methods are proposed.For the problem that the conventional mismatched filter(MMF)cannot suppress the time-delay dimension side peaks,a neighborhood MMF(NMMF)is proposed.Experimental results demonstrate the effectiveness of the proposed methods.

A spawning particle filter for defocused moving target detection in GNSS-based passive radar

Global Navigation Satellite System(GNSS)-based passive radar(GBPR)has been widely used in remote sensing applications.However,for moving target detection(MTD),the quadratic phase error(QPE)introduced by the non-cooperative target motion is usually difficult to be compensated,as the low power level of the GBPR echo signal renders the estimation of the Doppler rate less effective.Consequently,the moving target in GBPR image is usually defocused,which aggravates the difficulty of target detection even further.In this paper,a spawning particle filter(SPF)is proposed for defocused MTD.Firstly,the measurement model and the likelihood ratio function(LRF)of the defocused point-like target image are deduced.Then,a spawning particle set is generated for subsequent target detection,with reference to traditional particles in particle filter(PF)as their parent.After that,based on the PF estimator,the SPF algorithm and its sequential Monte Carlo(SMC)implementation are proposed with a novel amplitude estimation method to decrease the target state dimension.Finally,the effectiveness of the proposed SPF is demonstrated by numerical simulations and pre-liminary experimental results,showing that the target range and Doppler can be estimated accurately.

Moving target localization for multistatic passive radar using delay, Doppler and Doppler rate measurements

Time delay and Doppler shift between the echo signal and the reference signal are two most commonly used measurements in target localization for the passive radar. Doppler rate, which can be obtained from the extended cross ambiguity function, offers an opportunity to further enhance the localization accuracy. This paper considers using the measurement Doppler rate in addition to measurements of time delay and Doppler shift to locate a moving target. A closed-form solution is developed to accurately and efficiently estimate the target position and velocity.The proposed solution establishes a pseudolinear set of equations by introducing some additional variables, imposes weighted least squares formulation to yield a rough estimate, and utilizes the function relation among the target location parameters and additional variables to improve the estimation accuracy. Theoretical covariance and Cramer-Rao lower bound(CRLB) are derived and compared, analytically indicating that the proposed solution attains the CRLB. Numerical simulations corroborate this analysis and demonstrate that the proposed solution outperforms existing methods.

A NOVEL ALGORITHM FOR SIDE PEAKS SUPPRESSION OF AMBIGUITY FUNCTION FOR PASSIVE RADAR BASED ON CHINESE DTTB SIGNAL

The ambiguity function of Chinese standard Digital Television Terrestrial Broadcasting (DTTB) signals for passive radar contains one main peak and many side peaks. The side peaks may cause the false alarms. The relative positions and the reasons for the side peaks are analyzed and a new algorithm for side peaks suppression is proposed in this paper. The algorithm, in consideration of the characteristics of the structure of the frame, can eliminate the side peaks completely in the valid Doppler observation interval by setting the reference signals to zero at equal intervals. Both the simulative and experimental results show that this algorithm can improve the performance of target detection of the passive radar based on DTTB signal.

Data fusion of target characteristic in multistatic passive radar

Radar cross section(RCS)is an important attribute of radar targets and has been widely used in automatic target recognition(ATR).In a passive radar,only the RCS multiplied by a coefficient is available due to the unknown transmitting parameters.For different transmitter-receiver(bistatic)pairs,the coefficients are different.Thus,the recovered RCS in different transmitter-receiver(bistatic)pairs cannot be fused for further use.In this paper,we propose a quantity named quasi-echo-power(QEP)as well as a method for eliminating differences of this quantity among different transmitter-receiver(bistatic)pairs.The QEP is defined as the target echo power after being compensated for distance and pattern propagation factor.The proposed method estimates the station difference coefficients(SDCs)of transmitter-receiver(bistatic)pairs relative to the reference transmitter-receiver(bistatic)pair first.Then,it compensates the QEP and gets the compensated QEP.The compensated QEP possesses a linear relationship with the target RCS.Statistical analyses on the simulated and real-life QEP data show that the proposed method can effectively estimate the SDC between different stations,and the compensated QEP from different receiving stations has the same distribution characteristics for the same target.

Observability and estimability of passive radar with unknown illuminator states using different observations

Most existing studies about passive radar systems are based on the already known illuminator of opportunity(IO)states.However,in practice,the receiver generally has little knowledge about the IO states.Little research has studied this problem.This paper analyzes the observability and estimability for passive radar systems with unknown IO states under three typical scenarios.Besides,the directions of high and low estimability with respect to various states are given.Moreover,two types of observations are taken into account.The effects of different observations on both observability and estimability are well analyzed.For the observability test,linear and nonlinear methods are considered,which proves that both tests are applicable to the system.Numerical simulations confirm the correctness of the theoretical analysis.

RESEARCH ON PERFORMANCE INFLUENCE OF DIRECT-PATH SIGNAL FOR DVB-S BASED PASSIVE RADAR

Passive radar detects moving targets by Cross Ambiguity Function (CAF), which is based on the cross correlation process of the direct-path signal in reference channel and echo signal in receive channel. Thus, the performance of direct-path signal is important to system performance for this type of radar. While the Signal to Noise Ratio (SNR) of direct-path signal is low, it will deteriorate the detection performance. In this paper, how SNR of direct-path signal induces degradation on the SNR of CAF, and how the integration gain affects by integration time are analyzed, both with theoretical analysis and numerical simulation, which are valuable for the R&D of passive radar.

Experimental Research of Dual-Polarization Passive Radar Based on DTTB Signal

The passive radar is a hot research topic. A multi-channel wideband passive radar experimental system is designed and the digital television terrestrial broadcasting (DTTB) signal is chosen to carry out the target detection experiment of civil aviation aircraft. The polarization and spatial filtering methods are used to solve the strong direct path interference suppression problems brought by the receiving system location;combined with the characteristics of DTTB signal, the block length selection interval in the block batch processing method for range-Doppler images calculation is given;the clutter suppression performance is compared through the experimental data receiving from different bistatic polarization channels, the conclusion is different from the monostatic radar and it can guide the passive radar experiment.

DOA estimation based on multi-frequency joint sparse Bayesian learning for passive radar

This paper considers multi-frequency passive radar and develops a multi-frequency joint direction of arrival(DOA)estimation algorithm to improve estimation accuracy and resolution.The developed algorithm exploits the sparsity of targets in the spatial domain.Specifically,we first extract the required frequency channel data and acquire the snapshot data through a series of preprocessing such as clutter suppression,coherent integration,beamforming,and constant false alarm rate(CFAR)detection.Then,based on the framework of sparse Bayesian learning,the target’s DOA is estimated by jointly extracting the multi-frequency data via evidence maximization.Simulation results show that the developed algorithm has better estimation accuracy and resolution than other existing multi-frequency DOA estimation algorithms,especially under the scenarios of low signalto-noise ratio(SNR)and small snapshots.Furthermore,the effectiveness is verified by the field experimental data of a multi-frequency FM-based passive radar.

Detection of UAV Target Based on Continuous Radon Transform and Matched Filtering Process for Passive Bistatic Radar

Long-time integration technique is an effective way of improving target detection performance for unmanned aerial vehicle(UAV)in the passive bistatic radar(PBR),while range migration(RM)and Doppler frequency migration(DFM)may have a major effect due to the target maneuverability.This paper proposed an innovative long-time coherent integration approach,regarded as Continuous Radon-matched filtering process(CRMFP),for low-observable UAV target in passive bistatic radar.It not only mitigates the RM by collaborative research in range and velocity dimensions but also compensates the DFM and ensures the coherent integration through the matched filtering process(MFP).Numerical and real-life data following detailed analysis verify that the proposed method can overcome the Doppler mismatch influence and acquire comparable detection performance.

High-accuracy target tracking for multistatic passive radar based on a deep feedforward neural network

In radar systems,target tracking errors are mainly from motion models and nonlinear measurements.When we evaluate a tracking algorithm,its tracking accuracy is the main criterion.To improve the tracking accuracy,in this paper we formulate the tracking problem into a regression model from measurements to target states.A tracking algorithm based on a modified deep feedforward neural network(MDFNN)is then proposed.In MDFNN,a filter layer is introduced to describe the temporal sequence relationship of the input measurement sequence,and the optimal measurement sequence size is analyzed.Simulations and field experimental data of the passive radar show that the accuracy of the proposed algorithm is better than those of extended Kalman filter(EKF),unscented Kalman filter(UKF),and recurrent neural network(RNN)based tracking methods under the considered scenarios.

An extended processing scheme for coherent integration and parameter estimation based on matched filtering in passive radar

In passive radars, coherent integration is an essential method to achieve processing gain for target detection. The cross ambiguity function(CAF) and the method based on matched filtering are the most common approaches. The method based on matched filtering is an approximation to CAF and the procedure is:(1) divide the signal into snapshots;(2) perform matched filtering on each snapshot;(3) perform fast Fourier transform(FFT) across the snapshots. The matched filtering method is computationally affordable and can offer savings of an order of 1000 times in execution speed over that of CAF. However, matched filtering suffers from severe energy loss for high speed targets. In this paper we concentrate mainly on the matched filtering method and we use keystone transform to rectify range migration. Several factors affecting the performance of coherent integration are discussed based on the matched filtering method and keystone transform. Modified methods are introduced to improve the performance by analyzing the impacts of mismatching, precision of the keystone transform, and discretization. The modified discrete chirp Fourier transform(MDCFT) is adopted to rectify the Doppler expansion in a multi-target scenario. A novel velocity estimation method is proposed, and an extended processing scheme presented. Simulations show that the proposed algorithms improve the performance of matched filtering for high speed targets.

Joint compressed sensing imaging and phase adjustment via an iterative method for multistatic passive radar

The resolution of the multistatic passive radar imaging system(MPRIS)is poor due to the narrow bandwidth of the signal transmitted by illuminators of opportunity.Moreover,the inaccuracies caused by the inaccurate tracking system or the error position measurement of illuminators or receivers can deteriorate the quality of an image.To improve the performance of an MPRIS,an imaging method based on the tomographic imaging principle is presented.Then the compressed sensing technique is extended to the MPRIS to realize high-resolution imaging.Furthermore,a phase correction technique is developed for compensating for phase errors in an MPRIS.Phase errors can be estimated by iteratively solving an equation that is derived by minimizing the mean recovery error of the reconstructed image based on the principle of fixed-point iteration technique.The technique is nonparametric and can be used to estimate phase errors of any form.The effectiveness and convergence of the technique are confirmed by numerical simulations.

Range-Angle Dependent Beampattern Synthesis Method for OFDM-Based Passive Radar

Frequency diverse array(FDA)radar applies a tiny frequency offset across its adjacent transmitting array elements to generate a range-angle-dependent beampattern.The increased degrees-of-freedom(DOFs)in range domain can help improve the performance of radar in target detection,localization,and clutter suppression.Passive radar utilizes uncontrollable external signal as illuminator,which makes it difficult to apply traditional frequency diverse process method.However,the third-party illuminator such as Orthogonal Frequency Division Multiplexing(OFDM)signal usually consists of several closely spaced modulated carriers,and it has been widely selected as the illuminator for passive radar in recent years.Considering the orthogonality between even separated subcarriers,we propose a new frequency diverse process method by extracting and processing each subcarrier of received data independently and attempt to provide a range-angle dependent beampattern for OFDM passive radar.Numerical results and real data analyses verify the superiority of frequency diversity process on the received data of OFDM passive radar.

Target detection method in passive bistatic radar

Owing to the advantages in detecting the low altitude and stealth target,passive bistatic radar(PBR)has received much attention in surveillance purposes.Due to the uncontrollable characteristic of the transmitted signal,a high level range or Doppler sidelobes may exist in the ambiguity function which will degrade the target detection performance.Mismatched filtering is a common method to deal with the ambiguity sidelobe problem.However,when mismatched filtering is applied,sidelobes cannot be eliminated completely.The residual sidelobes will cause false-alarm when the constant false alarm ratio(CFAR)is applied.To deal with this problem,a new target detection method based on preprocessing is proposed.In this new method,the ambiguity range and Doppler sidelobes are recognized and eliminated by the preprocessing method according to the prior information.CFAR is also employed to obtain the information of the target echo.Simulation results and results on real data illustrate the effectiveness of the proposed method.

A Novel Clutter Suppression Algorithm for Low-Slow-Small Targets Detecting Based on Sparse Adaptive Filtering

Passive detection of low-slow-small(LSS)targets is easily interfered by direct signal and multipath clutter,and the traditional clutter suppression method has the contradiction between step size and convergence rate.In this paper,a frequency domain clutter suppression algorithm based on sparse adaptive filtering is proposed.The pulse compression operation between the error signal and the input reference signal is added to the cost function as a sparsity constraint,and the criterion for filter weight updating is improved to obtain a purer echo signal.At the same time,the step size and penalty factor are brought into the adaptive iteration process,and the input data is used to drive the adaptive changes of parameters such as step size.The proposed algorithm has a small amount of calculation,which improves the robustness to parameters such as step size,reduces the weight error of the filter and has a good clutter suppression performance.

Robust mismatched filtering algorithm for passive bistatic radar using worst-case performance optimization

Passive bistatic radar detects targets by exploiting available local broadcasters and communication transmissions as illuminators, which are not designed for radar. The signal usually contains a time-varying structure, which may result in high-level range ambiguity sidelobes. Because the mismatched filter is effective in suppressing sidelobes, it can be used in a passive bistatic radar. However, due to the low signal-to-noise ratio in the reference signal, the sidelobe suppression performance seriously degrades in a passive bistatic radar system. To solve this problem, a novel mismatched filtering algorithm is developed using worst-case performance optimization. In this algorithm, the influence of the low energy level in the reference signal is taken into consideration, and a new cost function is built based on worst-case performance optimization. With this optimization, the mismatched filter weights can be obtained by minimizing the total energy of the ambiguity range sidelobes. Quantitative evaluations and simulation results demonstrate that the proposed algorithm can realize sidelobe suppression when there is a low-energy reference signal. Its effectiveness is proved using real data.

Doppler ambiguity analysis and suppression for LTE-based passive bistatic radars

In this study,we provide a detailed analysis of the frequency division duplex long term evolution downlink(FDD LTE DL)signal for passive bistatic radars that use the signal as an illuminator of opportunity.In particular,we analyze the crossambiguity function and illustrate its undesired deterministic peaks in the Doppler dimension due to the specific structure of the FDD LTE DL signal.A new adaptive mismatched filtering method is proposed for pre-processing the original reference signal to suppress these undesired deterministic peaks in the range-Doppler processing.The effectiveness of our proposed method is demonstrated via simulations following robustness analysis,showing that all undesired peaks are suppressed below-40 dB,with only 1.7 dB reduction in the main peak.