An Efficient Moving Target Detection Algorithm Based on Sparsity-Aware Spectrum Estimation

Abstract

In this paper, an efficient direct data domain space-time adaptive processing (STAP) algorithm for moving targets detection is proposed, which is achieved based on the distinct spectrum features of clutter and target signals in the angle-Doppler domain. To reduce the computational complexity, the high-resolution angle-Doppler spectrum is obtained by finding the sparsest coefficients in the angle domain using the reduced-dimension data within each Doppler bin. Moreover, we will then present a knowledge-aided block-size detection algorithm that can discriminate between the moving targets and the clutter based on the extracted spectrum features. The feasibility and effectiveness of the proposed method are validated through both numerical simulations and raw data processing results.

Extended Target Echo Detection Based on KLD and Wigner Matrices

“…Here, consider common LPI radar waveforms: Linear frequency modulation (LFM) and Poly-Phase Shift Keying (PPSK) techniques including Frank, P1, P2, P3, and P4 codes [32]. To verify the efficiency of the proposed method, Figure 3 precisely illustrates the comparison of performance between the proposed method and the three established ones, namely, Jun Chen's method, the normality tests, and the MTD [33,34]. The normality tests are Jarque-Bera test (JB), Lilliefors test (Lillie), and Anderson-Darling test (AD).…”

An Efficient Adaptive Angle-Doppler Compensation Approach for Non-Sidelooking Airborne Radar STAP

“…If we still utilize FFT to obtain the angle spectrum in the spatial domain, the angle-Doppler spectrum will suffer from a series of problems such as main-lobe broadening, and high side-lobe leakage, which consequently leads to a poor estimation of the spatial frequency. Therefore, the RDSR technique [ 11 ] can be used to obtain the high resolution spatial spectrum.…”

“…It is clear that the spatial RDSR image has much better resolution and lower side-lobe level than that of 2D FFT, which will improve the accuracy of estimating the SC location of main-lobe clutter. However, due to the spectrum discontinuity of RDSR in the spatial domain, the spectral center frequency extracting method proposed in reference [ 11 ] is also employed to determine the maximum value of the angle spectrum.…”

“…In order to save computational load, an improved AADC implementation strategy is proposed in this paper. Firstly, a novel clutter spectrum angle-Doppler location estimation method based on reduced-dimension sparse reconstruction [ 11 ] is designed to extract the exact knowledge of the clutter angle-Doppler trajectory centers. Then, the clutter spectral center (SC) can be efficiently compensated over range.…”

Fast ℓ1-regularized space-time adaptive processing using alternating direction method of multipliers

“…Compared with conventional STAP methods, sparsity-based STAP techniques have been shown to provide high resolution and exhibit better performance than conventional STAP algorithms. 16 The alternating direction method of multipliers (ADMM) is a technique used to combine the decomposability of dual ascent with the rapid convergence speed of the method of multipliers. 17,18 This technique is well suited for solving the optimization problems of the l 1 constraint, particularly large-scale problems.…”