Doppler-Spread Space Target Detection Based on Overlapping Group Shrinkage and Order Statistics

被引:0
作者
Bu, Linsheng [1 ]
Fu, Tuo [1 ]
Chen, Defeng [1 ]
Cao, Huawei [1 ]
Zhang, Shuo [1 ]
Han, Jialiang [1 ]
机构
[1] Beijing Inst Technol, Sch Informat & Elect, Beijing 100081, Peoples R China
关键词
Doppler-spread target detection; line spectra; overlapping group shrinkage; order statistics; COHERENT INTEGRATION ALGORITHM; ADAPTIVE DETECTION; RANGE;
D O I
10.3390/rs16183413
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The Doppler-spread problem is commonly encountered in space target observation scenarios using ground-based radar when prolonged coherent integration techniques are utilized. Even when the translational motion is accurately compensated, the phase resulting from changes in the target observation attitude (TOA) still leads to extension of the target's echo energy across multiple Doppler cells. In particular, as the TOA change undergoes multiple cycles within a coherent processing interval (CPI), the Doppler spectrum spreads into equidistant sparse line spectra, posing a substantial challenge for target detection. Aiming to address such problems, we propose a generalized likelihood ratio test based on overlapping group shrinkage denoising and order statistics (OGSos-GLRT) in this study. First, the Doppler domain signal is denoised according to its equidistant sparse characteristics, allowing for the recovery of Doppler cells where line spectra may be situated. Then, several of the largest Doppler cells are integrated into the GLRT for detection. An analytical expression for the false alarm probability of the proposed detector is also derived. Additionally, a modified OGSos-GLRT method is proposed to make decisions based on an increasing estimated number of line spectra (ENLS), thus increasing the robustness of OGSos-GLRT when the ENLS mismatches the actual value. Finally, Monte Carlo simulations confirm the effectiveness of the proposed detector, even at low signal-to-noise ratios (SNRs).
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页数:23
相关论文
共 40 条
  • [1] JEM MODELING AND MEASUREMENT FOR RADAR TARGET IDENTIFICATION
    BELL, MR
    GRUBBS, RA
    [J]. IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, 1993, 29 (01) : 73 - 87
  • [2] Group-Sparse Signal Denoising: Non-Convex Regularization, Convex Optimization
    Chen, Po-Yu
    Selesnick, Ivan W.
    [J]. IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2014, 62 (13) : 3464 - 3478
  • [3] Translation-invariant shrinkage/thresholding of group sparse signals
    Chen, Po-Yu
    Selesnick, Ivan W.
    [J]. SIGNAL PROCESSING, 2014, 94 : 476 - 489
  • [4] Adaptive Double Threshold Detection Method for Range-Spread Targets
    Chen, Xinliang
    Gai, Jiyu
    Liang, Zhennan
    Liu, Quanhua
    Long, Teng
    [J]. IEEE SIGNAL PROCESSING LETTERS, 2022, 29 : 254 - 258
  • [5] [戴奉周 Dai Feng-zhou], 2009, [电子与信息学报, Journal of Electronics & Information Technology], V31, P2488
  • [6] David H. A., 2004, Order statistics
  • [8] Spatially distributed target detection in non-Gaussian clutter
    Gerlach, K
    [J]. IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, 1999, 35 (03) : 926 - 934
  • [9] [顾新锋 Gu Xinfeng], 2012, [电子与信息学报, Journal of Electronics & Information Technology], V34, P1318
  • [10] Sparsity-based algorithm for detecting faults in rotating machines
    He, Wangpeng
    Ding, Yin
    Zi, Yanyang
    Selesnick, Ivan W.
    [J]. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2016, 72-73 : 46 - 64