Multi-rank Range-spread Target Detection Method for Space/Time Symmetric Array Radar under Non-Gaussian Clutter Background

被引:0
|
作者
Gao Y. [1 ]
Pan L. [1 ]
Li Y. [1 ]
Zuo L. [1 ]
机构
[1] School of Electronic Engineering, Xidian University, Xi’an
基金
中国博士后科学基金; 中国国家自然科学基金;
关键词
Adaptive detection; Multi-rank subspace; Non-Gaussian; Persymmetry; Range-spread target;
D O I
10.12000/JR22013
中图分类号
学科分类号
摘要
This study proposes a multi-rank range-spread target detection method for multi-channel array radar under a non-Gaussian clutter background. The method aims to detect the target from real clutter using the multi-channel array radar. First, a multi-rank range-spread target model was formulated using a subspace matrix with a rank greater than one and the coordinate vectors of corresponding range bins. Then, by exploiting the persymmetric structure information of the clutter covariance matrix under the detection scenario, wherein the radar receiver units were central symmetric in space or time, a small sample estimation strategy for the parameters to be solved through the unitary transformation was constructed. Further, a non-Gaussian clutter background multi-rank range-spread target detection method was designed based on the generalized likelihood ratio, Rao, and Wald tests. Finally, a theoretical derivation proved that the proposed detection method has the constant false alarm rate property. The experimental results based on both the simulated and measured data showed that the proposed detection method can ensure the constant false alarm rate property of the clutter covariance matrix. Additionally, compared with the existing detection methods, the proposed detection method improves the target detection performance under small sample support. Besides, the proposed detection method effectively improves the robustness of target detection under the condition of steering vector mismatch. © 2022 Institute of Electronics Chinese Academy of Sciences. All rights reserved.
引用
收藏
页码:765 / 777
页数:12
相关论文
共 40 条
  • [1] HAN Jinwang, ZHANG Zijing, LIU Jun, Et al., Adaptive Bayesian detection for MIMO radar in Gaussian clutter[J], Journal of Radars, 8, 4, pp. 501-509, (2019)
  • [2] WANG Yongliang, LIU Weijian, XIE Wenchong, Et al., Research progress of space-time adaptive detection for airborne radar[J], Journal of Radars, 3, 2, pp. 201-207, (2014)
  • [3] DE MAIO A., Rao test for adaptive detection in Gaussian interference with unknown covariance matrix[J], IEEE Transactions on Signal Processing, 55, 7, pp. 3577-3584, (2007)
  • [4] PASCAL F, CHITOUR Y, OVARLEZ J P, Et al., Covariance structure maximum-likelihood estimates in compound Gaussian noise: Existence and algorithm analysis[J], IEEE Transactions on Signal Processing, 56, 1, pp. 34-48, (2008)
  • [5] XU Shuwen, SHI Xingyu, SHUI Penglang, An adaptive detector with mismatched signals rejection in compound Gaussian clutter[J], Journal of Radars, 8, 3, pp. 326-334, (2019)
  • [6] GRECO M, GINI F, RANGASWAMY M., Statistical analysis of measured polarimetric clutter data at different range resolutions[J], IEE Proceedings - Radar, Sonar and Navigation, 153, 6, pp. 473-481, (2006)
  • [7] SANGSTON K J, GINI F, GRECO M S., Coherent radar target detection in heavy-tailed compound-Gaussian clutter[J], IEEE Transactions on Aerospace and Electronic Systems, 48, 1, pp. 64-77, (2012)
  • [8] HE You, JIAN Tao, SU Feng, Et al., Adaptive detection application of covariance matrix estimator for correlated non-Gaussian clutter[J], IEEE Transactions on Aerospace and Electronic Systems, 46, 4, pp. 2108-2117, (2010)
  • [9] CONTE E, LOPS M, RICCI G., Asymptotically optimum radar detection in compound-Gaussian clutter[J], IEEE Transactions on Aerospace and Electronic Systems, 31, 2, pp. 617-625, (1995)
  • [10] STINCO P, GRECO M, GINI F., Adaptive detection in compound-Gaussian clutter with inverse-gamma texture, 2011 IEEE CIE International Conference on Radar, (2011)