CAJ | 학술논문

基于子空间DOA估计的MUSIC算法,是将阵列输出数据的协方差矩阵进行特征分解后,利用与信号分量相正交的噪声子空间来估计信号波达方向.然而在进行谱估计之前,需要对信号源的数目进行估计,以确定信号子空间和噪声子空间的维数,这将增大DOA估计的复杂度.对利用部分噪声子空间进行谱估计的方法进行了阐述,由于其不需要进行信源数目的估计,因此可以减小谱估计的复杂度.计算机仿真实验和性能分析验证了该方法的性能.
기우자공간DOA고계적MUSIC산법,시장진렬수출수거적협방차구진진행특정분해후,이용여신호분량상정교적조성자공간래고계신호파체방향.연이재진행보고계지전,수요대신호원적수목진행고계,이학정신호자공간화조성자공간적유수,저장증대DOA고계적복잡도.대이용부분조성자공간진행보고계적방법진행료천술,유우기불수요진행신원수목적고계,인차가이감소보고계적복잡도.계산궤방진실험화성능분석험증료해방법적성능.
The principle of MUSIC algorithm based on the subspace DOA estimation is to use the noise subspace orthogo?nal to signal component to estimate the direction of the signal wave,throught eigen decomposition of the covariance matrix with array output data. However,before the spectrum estimation,the number of the signal source should be estimated to determine the dimensions of the signal subspace and noise subspace,Which would increase the complexity of DOA estimation. The paper illustrates the method of using the partial noise subspace to estimate the DOA. As the estimation of the signal number is unneces?sary,the complexity of the spectrum estimation is reduced. The simulation and performance analysis demonstrate the validity and feasibility of the partial noise algorithm.