低快照数下多目标DOA估计方法  

Multi-target DOA estimation method under low number of snapshots

作　　者：禄宇媛 钱蓉蓉 任文平[1] 卢松琴 LU Yuyuan;QIAN Rongrong;REN Wenping;LU Songqin(School of Information Science and Engineering,Yunnan University,Kunming 650500,China)

机构地区：[1]云南大学信息学院,云南昆明650500

出　　处：《传感器与微系统》2023年第6期120-123,128,共5页Transducer and Microsystem Technologies

基　　金：国家自然科学基金青年科学基金资助项目(61701433);云南省科技厅面上资助项目(2018FB099);云南大学研究生科研创新项目(20200309)。

摘　　要：针对低快照数和较低信噪比条件下多信号到达方向(DOA)估计性能下降问题,提出了基于深度学习的离格DOA估计方法。选择具有特殊结构的非均匀阵列以提高阵列自由度,将样本协方差矩阵建模为真实协方差矩阵的噪声版本,利用堆叠降噪自动编码器(SDAE)重构出新协方差矩阵,最后结合超分辨率算法实现DOA估计。仿真结果表明:在低快照数为10及较低信噪比2 dB情况下,数据先采用SDAE进行处理再进行DOA估计,多目标DOA估计准确率能达到92.06%,相对于传统方法及深度神经网络(DNN)分别提高了55.39%,25.025%。Aiming at the performance degradation problem of multi-signal direction of arrival(DOA)estimation under the conditions of low snapshots and low signal-to-noise ratio,an off-frame DOA estimation method based on deep learning is proposed.Select a non-uniform array with a special structure to increase the degree of freedom of the array,model the sample covariance matrix as a noise version of the real covariance matrix,and use the stacked denoising auto encoder(SDAE)to reconstruct the new covariance matrix.Finally,DOA estimation is achieved by combining with the super-resolution algorithm.The simulation results show that when the number of snapshots is 10 and the low signal-to-noise ratio is 2 dB,the data is firstly processed by SDAE and then DOA estimation is done.The accuracy of multi-target DOA estimation can reach 92.06%,compared with traditional methods and DNN,which is increased by 55.39%and 25.025%,respectively.

关 键 词：到达方向估计 低快照数 堆叠降噪自动编码器 协方差矩阵重构 

分 类 号：TN911.7[电子电信—通信与信息系统] TP391[电子电信—信息与通信工程]