The Weak Target Detection Method Based on the Subspace Bearing Stability

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  • 1. College of Computer Science and Technology, Zhoukou Normal University, Zhoukou 466000, Henan, China; 2. Institute of Visualization Technology, Northwest University, Xi’an 710069, China; 3. Institute of Acoustics, Chinese Academy of Science, Beijing 100190, China; 4. Appsoft Technology Co., Ltd., Beijing 100190, China

Abstract

In unknown underwater target detection and bearing estimation, the weak targets are covered by strong targets, which cannot be detected and estimated at the same time. A weak target detection method based on the subspace bearing stability is proposed to solve the problem. Firstly, this method makes eigen decomposition for covariance matrix of array element receiving data. Then, it utilizes the characteristic that the beam-forming bearing estimation values of targets subspace are stable and close to the true values, and the beam-forming bearing estimation values of background noise subspace are randomly distributed in [0°,180°]. Lastly, the method statistically weights the normalized spatial spectra of each subspace by the bearing variance, so it can further restrain the spatial spectrum disturbances of background noise subspace, and can decrease the spatial spectrum difference between strong targets and weak targets subspace. The theoretical analysis, numerical simulation and experimental results show that, at the same frequency band and the same beam, compared with sub-band conventional beam-forming (SBCBF) detection method, our method can well enhance the spatial spectrum amplitude of weak target subspace, and decrease the spatial spectrum difference between strong targets and weak targets subspace, and detect strong targets and weak targets at the same time.

Cite this article

SUN Ting1,2,GENG Guohua2,ZHENG Enming3,WANG Ping4 . The Weak Target Detection Method Based on the Subspace Bearing Stability[J]. Journal of Shanghai Jiaotong University, 2018 , 52(4) : 480 -487 . DOI: 10.16183/j.cnki.jsjtu.2018.04.014

References

[1]李文兴, 毛晓军, 孙亚秀. 一种新的波束形成零陷展宽算法[J]. 电子与信息学报, 2014, 36(12): 2882-2888. LI Wenxing, MAO Xiaojun, SUN Yaxiu. A new algorithm for null broadening beamforming[J]. Journal of Electronics and Information Technology, 2014, 36(12): 2882-2888. [2]黄聪, 张殿伦, 孙大军, 等. 基于相位校正的零点约束直达波抑制方法[J]. 哈尔滨工程大学学报, 2014, 35(10): 1224-1230. HUANG Cong, ZHANG Dianlun, SUN Dajun, et al. Direct path interference suppression based on zero constraint condition with phase correction[J]. Journal of Harbin Engineering University, 2014, 35(10): 1224-1230. [3]李鹏飞, 刘喆, 陶业荣, 等.主瓣约束下的零陷加深波束形成算法[J]. 探测与控制学报, 2014, 36(4): 44-46. LI Pengfei, LIU Zhe, TAO Yerong, et al. Beamforming algorithm with null beeping under main lobe constraint[J]. Iournal of Detection & Control, 2014, 36(4): 44-46. [4]葛士斌, 陈新华, 孙长瑜.具有良好宽容性的逆波束形成干扰抑制算法研究[J]. 电子与信息学报, 2015, 37(2): 380-385. GE Shibin, CHEN Xinhua, SUN Changyu. Jamming jam method based on covariance matrix[J]. Journal of Electronics and Information Technology, 2015, 37(2): 380-385. [5]葛士斌, 余华兵, 陈新华, 等. 基于协方差矩阵的干扰阻塞算法[J]. 科技导报, 2015, 33(19): 78-83. GE Shibin, YU Huabing, CHEN Xinhua, et al. Jamming jam method based on covariance matrix[J]. Science & Technology Review, 2015, 33(19): 78-83. [6]韩东, 张海勇, 黄海宁, 等. 基于远近场声传播特性的拖线阵声纳平台辐射噪声空域矩阵滤波技术[J].电子学报, 2014, 42(3): 432-438. HAN Dong, ZHANG Haiyong, HUANG Haining, et al. Towed line array sonar platform radiated noise spatial matrix filter based on far-field and near-field sound propagation characteristics[J]. Acta Eleconica Sinica, 2014, 42(3): 432-438. [7]韩东, 李建, 康春玉, 等. 拖曳线列阵声吶平台噪声的空域矩阵滤波抑制技术[J]. 声学学报, 2014, 39(1): 27-34. HAN Dong, LI Jian, KANG Chunyu, et al. Towed line array sonar platform noise suppression based on spatial matrix filtering technique[J]. Acta Acustica, 2014, 39(1): 27-34. [8]方庆园, 韩勇, 金铭, 等. 基于噪声子空间特征值重构的 DOA 估计算法[J].电子与信息学报, 2014, 36(12): 2876-2881. FANG Qingyuan, HAN Yong, JIN Ming. et al. DOA estimation based on eigenvalue reconstruction of noise subspace[J]. Journal of Electronics and Information Technology, 2014, 36(12): 2876-2881. [9]张静, 廖桂生, 张洁. 强信号背景下基于噪声子空间扩充的弱信号 DOA 估计方法[J]. 系统工程与电子技术, 2009, 31(6): 1279-1283. ZHANG Jing, LIAO Guisheng, ZHANG Jie. DOA estimation based on extended noise subspace in the presence of strong signals[J]. Systems Engineering and Electronics, 2009, 31(6): 1279-1283. [10]金燕利, 章伟裕, 陈艳丽. 一种基于特征分析的强干扰抑制方法[J]. 声学技术, 2014, 33(5): 469-472. JIN Yanli, ZHANG Weiyu, CHEN Yanli. A method of suppressing strong interference based on eigen-analysis[J]. Technical Acoustics, 2014, 33(5): 469-472. [11]OLFAT A, NADER-ESFAHARI S. A new signal subspace processing for DOA estimation[J]. Signal Processing, 2004, 84(4): 721-728. [12]RANGARAO K V, VENKATANARASIMHAN S. Gold-MUSIC: A variation on MUSIC to accurately determine peaks of the spectrum[J]. IEEE Trans Antenna & Propagation, 2013, 61(4): 2263-2268. [13]杨志伟, 贺顺, 廖桂生, 等. 子空间重构的一类自适应波束形成算法[J]. 电子与信息学报, 2012, 34(5): 1115-1119. YANG Zhiwei, HE Shun, LIAO Guisheng, et al. Adaptive beamforming algorithm with subspace reconstructing[J]. Journal of Electronics and Infor-mation Technology, 2012, 34(5): 1115-1119. [14]GU Y J, LESHEM A. Robust adaptive beamforming based on interference covariance matrix reconstruction and steering vector estimation[J]. IEEE Transactions on Signal Processing, 2012, 60(7): 3881-3885. [15]CHAE C B, HWANG I, JR R W H, et al. Interference aware-coordinated beamforming in a multi-cell system[J]. IEEE Transactions on Wireless Communications, 2012, 11(10): 3692-3703. [16]HARRISON B F. The eigencomponent association method for adaptive interference suppression[J]. Journal of the Acoustical Society of America, 2004; 115(5): 2122-2128. [17]徐亮, 曾操, 廖桂生, 等. 基于特征波束形成的强弱信号波达方向与新源数估计方法[J]. 电子与信息学报, 2011, 33(2): 321-325. XU Liang, ZENG Cao, LIAO Guisheng, et al. DOA and source number estimation method for strong and weak signals based on eigen beamforming[J]. Journal of Electronics and Information Technology, 2011, 33 (2): 321-325. [18]任岁玲, 葛凤翔, 郭良浩. 基于特征分析的自适应干扰抑制[J]. 声学学报, 2013, 38(3): 272-280. REN Suiling, GE Fengxiang, GUO Lianghao. Eigenanalysis-based adaptive interference suppression[J]. Acta Acustica, 2013, 38(3): 272-280. [19]石万山, 徐鹏, 任岁玲. 基于干扰抑制方法和引导声源的水平阵被动目标测距[J]. 声学技术, 2014, 33(3): 193-198. SHI Wanshan, XU Peng, REN Suiling. Passive source ranging using a horizontal array based on an adaptive interference suppression method and a guide source[J]. Technical Acoustics, 2014, 33(3): 193-198. [20]郭鑫, 葛凤翔, 任岁玲, 等. 一种最差情况下性能最优化的特征分析自适应波束形成方法[J]. 声学学报, 2015, 40(2): 187-197. GUO Xin, GE Fengxiang, REN Suiling, et al. Eigenanalysis-based adaptive beamforming using worst-case performance optimization[J]. Acya Acustica, 2015, 40(2): 187-197. [21]戴文舒, 陈新华, 孙长瑜. 被动线谱检测的子带分解和分方位区间融合算法[J].应用声学, 2015, 34(3): 227-235. DAI Wenshu, CHEN Xinhua, SUN Changyu. A fusion algorithm for passive detection of the line spectrum target based on the sub frequency and sub interval statistics[J]. Journal of Applied Acoustics, 2015, 34(3): 227-235. [22]郑恩明, 孙长瑜, 陈新华, 等.基于主副瓣比加权的未知线谱目标检测方法研究[J]. 应用声学, 2015, 34(4): 311-319. ZHENG Enming, SUN Changyu, CHEN Xinhua, et al. Unknown target detection weighted method based on the main side lobe ratio[J]. Journal of Applied Acoustics, 2015, 34(4): 311-319. [23]ZHENG E M, CHEN X H, YU H B, et al. Robust high-resolution beam-forming based on high order cross sensor processing method[J]. Journal of System Engineering and Electronics, 2015, 26(5): 932-940. [24]郑恩明, 黎远松, 余华兵, 等.基于高阶次Cross Sensor 处理的波束形成方法[J]. 振动与冲击, 2015, 34(24): 12-19. ZHENG Enming, LI Yuansong, YU Huabing, et al. Beamforming method based on high order cross sensor processing[J]. Journal of Vibration and Shock, 2015, 34(24): 12-19.
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