For the stability problem of spatial spectrum estimation based on the minimum variance distortionless response (MVDR) method, a kind of spatial spectrum estimation method based on coherent cumulative preprocessing is proposed. First, complex analytic data with a certain frequency band is transformed by complex analytic wavelet transform from the collected data of receiving array, and the sub-group data is obtained according to the idea of spatial smoothing from the complex analytic data. Next, making full use of the phase information of sensor data, a group of data with high signal-to-noise ratio is obtained by accumulating the complex analytic data of each sub-group after time delay compensation. Then, the covariance matrix of the new data is constructed via multi-point cumulative processing in time domain. Finally, spatial spectrum estimation is realized according to the orthogonal property of the covariance matrix. The processing results of numerical simulation and measured data show that, compared with the MVDR method and the diagonal loading MVDR method, the data source of constructing the covariance matrix is changed in this method through time domain complex analytic transform and coherent accumulation pretreatment. The full rank covariance matrix is stably obtained by multiple sampling points accumulation in this method. According to the relation of spatial bearing and the phase difference of the sensor data, this method can effectively improve the stability of spatial spectrum estimation via double exponential function addition.
YU Huabing,ZHENG Enming,CHEN Xinhua
. A Spatial Spectrum Estimation Method Based on
Coherent Cumulative Preprocessing[J]. Journal of Shanghai Jiaotong University, 2020
, 54(11)
: 1209
-1217
.
DOI: 10.16183/j.cnki.jsjtu.2019.332
［1］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 Systems Engineering and Electronics, 2015, 26(5): 932-940.
［2］CHEN X H, LIU C, YU H B, et al. Robust broadband beam-forming based on the feature of underwater target radiated noise［J］. China Ocean Engineering, 2016, 30(6): 1004-1011.
［3］VOROBYOV S A, GERSHMAN A B, LUO Z Q. Robust adaptive beamforming using worst-case performance optimization: A solution to the signal mismatch problem［J］. IEEE Transactions on Signal Processing, 2003, 51(2): 313-324.
［4］YOO D S. Subspace-based DOA estimation with sliding signal-vector construction for ULA［J］. Electronics Letters, 2015, 51(17): 1361-1363.
［5］崔琳, 李亚安, 房媛媛, 等. 一种基于支持向量机的对角加载鲁棒波束形成方法［J］. 兵工学报, 2013, 34(5): 598-604.
CUI Lin, LI Ya’an, FANG Yuanyuan, et al. The robust diagonal loading beamforming method using support vector machines［J］. Acta Armamentarii, 2013, 34(5): 598-604.
［6］郑恩明, 张恩宾, 孙长瑜, 等. 一种基于重置协方差矩阵的波束形成优化方法［J］. 振动与冲击, 2015, 34(17): 185-190.
ZHENG Enming, ZHANG Enbin, SUN Changyu, et al. An optimization approach for beam-forming based on reset covariance matrix［J］. Journal of Vibration and Shock, 2015, 34(17): 185-190.
［7］唐孝国, 张剑云, 洪振清. 一种改进的MVDR相干信源DOA估计算法［J］. 电子信息对抗技术, 2012, 27(6): 6-10.
TANG Xiaoguo, ZHANG Jianyun, HONG Zhen-qing. DOA estimation of coherent signals via improved MVDR algorithm［J］. Electronic Information Warfare Technology, 2012, 27(6): 6-10.
［8］周彬, 赵安邦, 龚强, 等. 基于对角减载的水声阵列SMI-MVDR空间谱估计技术［J］. 系统工程与电子技术, 2014, 36(12): 2381-2387.
ZHOU Bin, ZHAO Anbang, GONG Qiang, et al. Underwater acoustic array SMI-MVDR spatial spectral estimation based on diagonal reduction［J］. Systems Engineering and Electronics, 2014, 36(12): 2381-2387.
［9］LIU Y, XIE C, ZHANG Y R. Direction of arrivals estimation for correlated broadband radio signals by MVDR algorithm using wavelet［J］. China Communications, 2017, 14(3): 190-197.
［10］郑恩明, 黎远松, 陈新华, 等. 改进的最小方差无畸变响应波束形成方法［J］. 上海交通大学学报, 2016, 50(2): 188-193.
ZHENG Enming, LI Yuansong, CHEN Xinhua, et al. Improved bearing resolution approach for MVDR beam-forming［J］. Journal of Shanghai Jiao Tong University, 2016, 50(2): 188-193.
［11］李智忠, 许忠良, 李海涛, 等. 基于傅里叶变换的快速TAMVDR算法［J］. 舰船科学技术, 2016, 38(1): 85-89.
LI Zhizhong, XU Zhongliang, LI Haitao, et al. Fast TAMVDR algorithm based on fourier transform［J］. Ship Science and Technology, 2016, 38(1): 85-89.
［12］YANG L S, MCKAY M R, COUILLET R. High-dimensional MVDR beamforming: Optimized solutions based on spiked random matrix models［J］. IEEE Transactions on Signal Processing, 2018, 66(7): 1933-1947.
［13］李冰, 汪永明, 黄海宁. 基于时域解析估计的多重信号分类波束形成方法［J］. 上海交通大学学报, 2019, 53(8): 928-935.
LI Bing, WANG Yongming, HUANG Haining. Multiple signal classification beam-forming method based on time domain analysis［J］. Journal of Shanghai Jiao Tong University, 2019, 53(8): 928-935.
［14］张家凡, 易启伟, 李季. 复解析小波变换与振动信号包络解调分析［J］.振动与冲击, 2010, 29(9): 93-96.
ZHANG Jiafan, YI Qiwei, LI Ji. Complex analytic wavelet transform and vibration signals envelope-demodulation analysis［J］. Journal of Vibration and Shock, 2010, 29(9): 93-96.
［15］郑恩明, 陈新华, 宋春楠. 基于全相位预处理的低旁瓣波束形成方法［J］. 兵工学报, 2018, 39(10): 1971-1978.
ZHENG Enming, CHEN Xinhua, SONG Chunnan. Low side-lobe beam-forming method based on all-phase preprocessing［J］. Acta Armamentarii, 2018, 39(10): 1971-1978.
［16］陈新华, 郑恩明. 基于分组时延预处理的时域波束形成方法［J］. 应用声学, 2019, 38(4): 545-552.
CHEN Xinhua, ZHENG Enming. Time domain beam-forming algorithm based on sub-group & time delay preprocessing［J］. Journal of Applied Acoustics, 2019, 38(4): 545-552.
