一種穩(wěn)健的知識輔助STAP色加載系數優(yōu)化算法

張圣鹋; 何子述; 李軍; 趙翔

doi:10.11999/JEIT151335

一種穩(wěn)健的知識輔助STAP色加載系數優(yōu)化算法

doi: 10.11999/JEIT151335

基金項目:

國家自然科學基金(61371184, 61301262, 61401062)

計量
- 文章訪問數: 1521
- HTML全文瀏覽量: 162
- PDF下載量: 364
- 被引次數: 0
出版歷程
- 收稿日期: 2015-11-26
- 修回日期: 2016-03-08
- 刊出日期: 2016-08-19

A Robust Colored-loading Factor Optimization Approach for KA-STAP

Funds:

The National Natural Science Foundation of China (61371184, 61301262, 61401062)

摘要

摘要: 色加載知識輔助STAP技術中，需根據先驗信息的準確度設置色加載系數。已有的基于色加載矩陣預白化性能評估的色加載系數優(yōu)化算法(Pre-Whitening, PW)無法評估當前待檢測距離單元(CUT)的先驗信息準確度，對于雜波先驗信息準確度不均勻的場景不具有魯棒性。該文在PW法的基礎上提出一種可有效評估CUT單元色加載矩陣性能的穩(wěn)健色加載系數優(yōu)化方法(CUT information involved PW, CPW)。CPW法利用部分參考單元樣本實現對CUT單元色加載矩陣預白化能力的評估，同時解決了PW法優(yōu)化結果非單值性的問題。仿真實驗討論了CPW法在不同參考單元樣本個數以及不同先驗信息準確度條件下的色加載系數優(yōu)化性能。仿真結果驗證了所提方法的有效性及穩(wěn)健性。
- 知識輔助空時自適應處理 /
- 色加載系數 /
- 預白化
Abstract: In colored-loading Knowledge Aided STAP (KA-STAP) techniques, the colored-loading factor should be determined according to the performance of the a priori information. The existing Pre-Whitening (PW) colored-loading factor optimization method can not evaluate the accuracy degree of the a priori information of the Cell Under Test (CUT), which makes it not robust to the situation where a priori information for each range bin is different. In this paper, a colored-loading factor optimization method, CUT information involved PW (CPW), is proposed to improve the performance of PW method. In CPW, partial training samples are utilized to evaluate the pre-whitening ability of the colored-loading matrix of CUT. At the same time, non-uniqueness problem of the optimization result of PW is also solved. Simulations are conducted to discuss the performance of CPW under different sample support conditions and different a priori information performance situations. Simulation results demonstrate the effectiveness and robustness of the proposed CPW approach.
- Knowledge Aided STAP (KA-STAP) /
- Colored-Loading factor (CL) /
- Pre-Whitening (PW)

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參考文獻(22)

GUERCI J R Space-time adaptive processing for radar[R]. Artech House, 2002.

馬澤強, 王希勤, 劉一民, 等. 基于稀疏恢復的空時二維自適應處理技術研究現狀[J]. 雷達學報, 2014, 3(2): 217-228. doi: 10.3724/SP.J.1300.2014.14002.

MA Zeqiang, WANG Xiqin, LIU Yimin, et al. An Overview on Sparse Recovery-based STAP[J]. Journal of Radars, 2014, 3(2): 217-228. doi: 10.3724/SP.J.1300.2014.14002.

WARD J. Space-time adaptive processing for airborne radar.[R] Report of Lincoln Laboratory, Lexington, MA, USA, 1998.

GUERCI J R and BARANOSKI E J. Knowledge-aided adaptive radar at DARPA: an overview[J]. IEEE Signal Processing Magazine, 2006, 23(1): 41-50. doi: 10.1109/ MSP.2006. 1593336.

范西昆, 曲毅. 知識輔助機載雷達雜波抑制方法研究進展[J]. 電子學報, 2012, 40(6): 1199-1206. doi: 10.3969/j.issn.0372- 2112.2012.06.022.

FAN Xikun and QU Yi. An overview of knowledge-aided clutter mitigation methods for airborne radar[J]. Acta Electronica Sinica, 2012, 40(6): 1199-1206. doi: 10.3969/j.issn. 0372-2112.2012.06.022.

方明, 劉宏偉, 戴奉周, 等. 基于環(huán)境動態(tài)感知的空時自適應處理[J]. 電子與信息學報, 2015, 37(8): 1786-1792. doi: 10.11999/JEIT141505.

FANG Ming, LIU Hongwei, DAI Fengzhou, et al. Space-time adaptive processing via dynamic environment sensing[J]. Journal of Electronics Information Technology, 2015, 37(8): 1786-1792. doi: 10.11999/JEIT141505.

WANG Pu, LI Hongbin, WANG Zhe, et al. Knowledge-aided parametric adaptive matched filter with automatic combining for covariance estimation[J]. IEEE Transactions on Signal Processing, 2014, 62(18): 4713-4722. doi: 10.1109/ ICASSP.2014.6854769.

郭佳佳, 廖桂生, 楊志偉, 等. 利用廣義內積值迭代加權的空時協(xié)方差矩陣估計方法[J]. 電子與信息學報, 2014, 36(2): 422-427. doi: 10.3724/SP.J.1146.2013.00426.

GUO Jiajia, LIAO Guisheng, YANG Zhiwei, et al. Iterative weighted covariance matrix estimation method for STAP based on generalized inner products[J]. Journal of Electronics Information Technology, 2014, 36(2): 422-427. doi: 10.3724 /SP.J.1146.2013.00426.

吳億鋒, 王彤, 吳建新, 等. 基于道路信息的知識輔助空時自適應處理[J]. 電子與信息學報, 2015, 37(3): 613-618. doi: 10.11999/JEIT140626.

WU Yifeng, WANG Tong, WU Jianxin, et al. A knowledge aided space time adaptive processing based on road network data[J]. Journal of Electronics Information Technology, 2015, 37(3): 613-618. doi: 10.11999/JEIT140626.

WU Yifeng, WANG Tong, WU Jianxin, et al. Robust training samples selection algorithm based on spectral similarity for spacetime adaptive processing in heterogeneous interference environments[J]. IET Radar, Sonar Navigation, 2015, 9(7): 778-782. doi: 10.1049/iet-rsn.2014.0285.

BERGIN J S, TEIXEIRA C M, TECHAU P M, et al. STAP with knowledge-aided data pre-whitening[C]. Proceedings of the IEEE Radar Conference, Philadelphia, PA, USA, 2004: 289-294. doi: 10.1109/NRC.2004.1316437.

BERGIN J S, TEIXEIRA C M, TECHAU P M, et al. Improved clutter mitigation performance using knowledge-aided space-time adaptive processing[J]. IEEE Transactions on Aerospace and Electronic Systems, 2006, 42(3): 997-1009. doi: 10.1109/ TAES.2006.248194.

MELVIN W L and SHOWMAN G A. An approach to knowledge- aided covariance estimation[J]. IEEE Transactions on Aerospace and Electronic Systems, 2006, 42(3): 1021-1042. doi: 10.1109/TAES.2006.248216.

STOICA P, LI Jian, ZHU Xumin, et al. On using a priori knowledge in space-time adaptive processing[J]. IEEE Transactions on Signal Processing, 2008, 56(6): 2598-2602. doi: 10.1109/TSP.2007.914347.

TANG Bo, ZHANG Yu, TANG Jun, et al. Close form maximum likelihood covariance matrix estimation under a knowledge-aided constraint[J]. IET Radar, Sonar Navigation, 2013, 7(8): 904-913. doi: 10.1049/iet-rsn.2012. 0309.

ZHU Xumin, LI Jian, Petre Stoica, et al. Knowledge-aided space-time adaptive processing[J]. IEEE Transactions on Aerospace and Electronic Systems, 2011, 47(2): 1325-1336. doi: 10.1109/ACSSC.2007.4487551.

ZHU Shengqi, LIAO Guisheng, XU Jingwei, et al. Robust space-time adaptive processing with colored loading using iterative optimization[J]. Digital Signal Processing, 2014, 35: 14-20. doi: 10.1016/j.dsp.2014.08.009.

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