CAJ | 학술논문

为了充分利用多输入多输出（multiple input multiple output ，MIMO ）声纳的虚拟阵列孔径的性能，针对目标的方位估计问题，提出了一种M IMO声纳系统的目标方位估计方法，该方法由发射阵列发射正交信号，接收阵列首先对接受信号进行匹配滤波，然后构造子空间拟合关系，最后采用马尔可夫蒙特卡罗吉布斯抽样方法解决子空间拟合求解运算量大的问题．仿真研究表明，两目标条件下，采用该方法的MIMO声纳系统方位估计精度在中低信噪比条件下接近MIMO最大似然方位估计，优于其它MIMO阵列方位估计方法，而运算量只是最大似然方法的约1/4．水池试验结果验证了算法的有效性．
위료충분이용다수입다수출（multiple input multiple output ，MIMO ）성납적허의진렬공경적성능，침대목표적방위고계문제，제출료일충M IMO성납계통적목표방위고계방법，해방법유발사진렬발사정교신호，접수진렬수선대접수신호진행필배려파，연후구조자공간의합관계，최후채용마이가부몽특잡라길포사추양방법해결자공간의합구해운산량대적문제．방진연구표명，량목표조건하，채용해방법적MIMO성납계통방위고계정도재중저신조비조건하접근MIMO최대사연방위고계，우우기타MIMO진렬방위고계방법，이운산량지시최대사연방법적약1/4．수지시험결과험증료산법적유효성．
A new DOA(direction of arrival )estimator based on MIMO sonar system is proposed to estimate the DOA of tar-gets .First ,orthogonal signals are sent out by transmitting sensors and the output of receiving sensors is matched filter by transmitting signal .Then ,solution of space fitting is achieved .Finally ,Markov Monte Carlo methods Gibbs sampling is combined with subspace fitting method (GSF ) to lighten computation burden .The simulations show that on the condition of two sources ,GSF provides simi-lar performance to that achieved by the ML method and better performance than other method in low and mid SNR range but its computational cost is only 1/4 of ML .Moreover ,our proposed method is verified by the pool experiment .