Clutter suppression is a challenging problem for passive bistatic radar systems, given the complexity of actual clutter scenarios (stationary, time-varying and fractional-order clutter). Such complex clutter induces intense sidelobes in the entire range-Doppler plane and thus degrades target-detection performance, especially for low-observable targets. In this paper, a novel method, denominated as the batch version of the extensive cancellation algorithm (ECA) in the frequency domain (ECA-FB), is presented for the first time, to suppress stationary clutter and its sidelobes. Specifically, in this method, the received signal is first divided into short batches in the frequency domain to coarsen the range resolution, and then the clutter is removed over each batch via ECA. Further, to suppress the time-varying clutter, a Doppler-shifted version of ECA-FB (ECA-FBD) is proposed. Compared with the popular ECA and ECA-B methods, the proposed ECA-FB and ECA-FBD obtained superior complex clutter suppression and slow-moving target detection performance with lower computational complexity. A series of simulation and experimental results are provided to demonstrate the validity of the proposed methods.

Owing to the continuous random and nonperiodic characteristics of the passive signal, the random range sidelobe coupling (RRSC) effects of the strong clutter (i.e., the direct path signal and the strong multipath signal) will exacerbate the performance of space-time adaptive processing (STAP) algorithm in airborne passive radar (APR). This article analyzes the influence of RRSC caused by strong clutter on detection range cell of interest and illustrates that strong clutter should be suppressed before applying the STAP algorithm. A cascaded least square (CLS) algorithm based on the directional dependence of clutter Doppler frequency is proposed for side-looking APR, where the first least square (LS) algorithm is performed to achieve the amplitude estimation of the Doppler-shift echo signal, and the channel amplitude and phase error correction factor can be obtained by the estimated amplitude information of the direct patch signal and the APR geometric configuration. The second LS is employed to further estimate the amplitude information of the strong clutter, and the resulting weight vector can be utilized for clutter cancelation. To make the CLS algorithm more practical, a batch version of the CLS (CLS-B) algorithm is proposed in this article. The advantage of the method is that it cannot only cancel clutter along the clutter ridge but also effectively prevent the suppression of targets falling in the clutter Doppler band. In addition, the proposed CLS algorithm performs well in the presence of the channel amplitude and phase error. A series of simulations are conducted to test the proposed algorithms.

For time-varying clutter suppression in passive bistatic radar (PBR) systems, some existing clutter suppression algorithms, belonging to the time-domain filter (TDF) or the frequency-domain filter (FDF), will suffer from performance degradation in the presence of fractional-order range clutter or fractional-order Doppler clutter, respectively. Additionally, some FDF-based clutter cancellation algorithms with subband operation will produce undesired periodic peaks in range domain, which is analyzed for the first time in this paper. To overcome the above limitations, an advanced extensive cancellation algorithm based on overlapping subband (ECA-OS) is developed. Initially, the clutter subspace with Doppler frequency is constructed in time-domain with the reference signal, where the clutter cancellation order in range domain is constrained to one-dimension. Subsequently, the echo signal and constructed clutter subspace are transformed to frequency-domain, followed by subband operation. Finally, in conjunction with least squares criterion, the weight coefficients of time-varying clutter are estimated with overlapping subband, and the clutter cancellation is implemented in each subband. Attributed to the above operations, both the fractional-order Doppler clutter and fractional-order range clutter are suppressed by the proposed ECA-OS with low computational complexity. In addition, by overlapping subband operation to introduce an additional degree of freedom (DOF), the proposed algorithm can avoid the generation of periodic peaks in range domain. The effectiveness of proposed ECA-OS is verified by theoretical derivations, simulations and measured data.

This article firstly analyzes the influence of utilizing the space-time adaptive processing (STAP) approaches in airborne passive radar (APR) systems on the dimension of the clutter subspace, and the signal-plus-noise ratio loss of the target, and illustrates that it is necessary to propose clutter cancellation algorithms suitable for APR systems. Combined with the property of APR systems, the multistage least squares algorithm based on subband operation (MLS-S) and the multistage least squares algorithm based on subband operation in temporal domain (MLS-ST) are proposed for the Doppler-shift clutter cancellation. The first method, in the case of the clutter with integer Doppler-shift bins, proves to be a simple solution. The second approach, at the expense of an additional stage, is suitable for more situations. Due to the use of Doppler-angle-dependence and subband operation to coarsen the range resolution, the proposed methods not only suppress effectively clutter along the clutter ridge, but also cancel the fractional-order-range clutter. In addition, the computational complexity of the proposed algorithms is low, and the clutter cancellation operations can be performed in parallel, which provide the possibility of real-time clutter suppression for APR systems. The feasibility of the proposed approaches is verified by diverse simulated scenarios.

To address the multi-frame coherent integration problem of weak target, including range migration (RM) and Doppler frequency migration (DFM) within the integration, a multi-frame integration method based on the short-time Radon Lv’s Distribution (STRLVD) is proposed in this paper. The proposed STRLVD algorithm can be classified into the following three primary steps. Initially, the Generalized Keystone (GKT) technique is employed to eliminate the coupling effect of acceleration and slow-time in each frame. Subsequently, the STRLVD method is performed to eliminate RM and DFM occurred within frame, which accomplishes energy integration and target peaks transfer in the centroid frequency-chirp rate (CFCR) domain. Finally, the Radon transform information is harnessed to facilitate inter-frame integration. Compared with the existing methods, the proposed algorithm attains remarkable target detection performance with lower computational complexity. A series of simulations and experimental data verify the effectiveness of the proposed algorithm.

The performance of the traditional Space-Time Adaptive Processing (STAP) methods will deteriorate in the presence of both mainlobe deceptive jammers and clutter. In order to mitigate the clutter and deceptive jammers simultaneously, a Three-Dimensional Atomic Norm Minimization (3D-ANM) STAP method based on subspace projection is proposed with an Element Pulse Coding-Multiple-Input Multiple-Output (EPC-MIMO) radar. At the modeling stage, by coding both the transmit elements and slow-time pulses, the echoes corresponding to different range ambiguity regions can be discriminated via equivalent spatial beampattern directions. In this regard, the target, mainlobe deceptive jammers, and range-ambiguous clutter can be distinguished in transmit-receive- Doppler domain by exploiting the distribution differences. Subsequently, the STAP method is utilized to mitigate clutter and deceptive jammers jointly. In specific, the subspace projection technique is adopted to ensure the comprehensiveness of subsequent covariance matrices estimation. Moreover, two 3D-ANM problems are formulated to recover the jammer-plus-range-ambiguous clutter covariance and range-unambiguous clutter covariance matrices, respectively. Particularly, in order to reduce the computational complexity, the constructed 3D-ANM problems are solved via Alternating Direction Method of Multipliers (ADMM). In addition, theoretical derivations and proofs on the properties of the developed methods are given. A series of simulations verify the efficacy of the proposed 3D-ANM STAP algorithm in mitigating deceptive jammers and clutter simultaneously.