Research On Coherent Source Localization Algorithm Based On Sensor Array

Direction of Arrival(DOA)estimation of spatial signals is the main research content in the field of array signal processing,which can achieve accurate angle estimation of air source signals and specific and accurate detection of parameters such as source orientation,and also has high resolution.It is widely used in radar,sonar,geological survey,medical diagnosis and other fields.Traditional subspace class algorithms usually have good estimation performance under independent signal conditions,but in the actual environment,due to the complex and variable spatial environment,the signals received by radar arrays contain a large number of coherent signals,and the existence of coherent signals causes a decrease in the rank of the signal covariance matrix,which makes it impossible to accurately distinguish the signal subspace from the noise subspace,leading to the failure of traditional algorithms.Therefore,the processing of coherent source signals has been a difficult and hot topic of research,which is also the focus of this paper.The main work and research methods in this paper are summarized as follows.Firstly,based on the basic model of boda direction estimation and the theoretical knowledge in detail,the advantages and disadvantages of the spatial spectral signal estimation model,several common antenna array models(uniform equidistant array,uniform equidistant L-array,uniform planar array and uniform equidistant circular array)and the far-field narrow-band signal model with noise model are analyzed,and their usage is pointed out.Secondly,the theories of three classical subspace class algorithms and four classical decoherence algorithms are derived and proved,and simulation experiments are conducted using MATLAB software.For the shortcoming that the multiple signal classification(MUSIC)algorithm will fail in processing coherent signals,an improved algorithm,the modified MUSIC algorithm,is proposed in this paper,and the effectiveness of the algorithm for decoherence is verified by simulation experiments.Finally,this paper proposes an improved Toeplitz algorithm,which first arranges the correlation functions between the received data of each array element and the received data of the reference array element to construct a full-rank Toeplitz matrix R.Then,the matrix R is reconstructed to obtain a lower triangular Toeplitz full-rank matrix RM;then the RM is conjugately rearranged to obtain the matrix;finally,combined with the Finally,the improved Toeplitz algorithm is obtained by combining the idea of forward-backward smoothing and taking the average of the three matrices.The simulation experiments show that the improved Toeplitz algorithm has better DOA estimation in the case of multiple sources,and the normalized success probability,average maximum estimation deviation and average estimation variance of the algorithm are better than the forward-backward smoothing algorithm.