Research On Source Location Algorithm Of Near-Field And Mixed-Field Based On High Order Cumulants

Passive source location is an important research topic in array signal processing.According to the distance between the signal source and the array,the signal source can be divided into the far field source and the near field source.When the far field source and the near field source coexist,it is a mixed source.For the far-field source,the positioning parameter only needs to Direction-of-Arrival(DOA);For near field sources,location parameters include DOA and distance.High-order cumulants are widely used in near field and mixed field source location algorithms due to their advantages such as the ability to separate DOA from distance parameters by selecting symmetric array elements,avoiding two-dimensional search and being insensitive to gaussian noise.However,the existing high-order cumulant mixed source location algorithms have high computational complexity,lack of effective separation methods of far-field source and near-field source,and the arrays used are uniform linear array and nested array,rather than coprime array with larger array aperture.In order to solve the above problems,this thesis explores combining ESPRIT method and second-order statistics to reduce computational complexity,and uses signal kurtosis estimation to realize the separation of far-field source and near-field source,and proposes two new localization parameter estimation algorithms.Based on the existing sparse array,a new symmetric coprime array,the displaced symmetric coprime array,is proposed and applied to the hybrid source location algorithm.The main work and innovation points of this thesis are as follows:(1)A mixed order based near field source location algorithm is proposed.To overcome the shortcoming of high computational complexity of near-field source location algorithm based on high-order cumulants,this algorithm starts from avoiding DOA spectrum search and reducing the use of high-order cumulants,separates DOA from range parameters by high-order cumulants,uses ESPRIT method to get DOA estimation of signals,and uses MUSIC search to get the range estimation of signals,so as to reduces the computational complexity of near-field source location algorithm based on high-order cumulants.(2)A mixed source location algorithm based on signal kurtosis estimation is proposed.In order to overcome the shortcomings of lacking effective mixed source separation method,the algorithm restructures the near field component cumulant matrix by estimating the kurtosis of the far field signal,so as to realize the effective separation of the far and near field information sources.ESPRIT algorithm and second order statistics are used to reduce the computational complexity of the algorithm.(3)A new symmetric coprime array,displaced symmetric coprime array,is proposed.Based on the existing sparse array,a displaced symmetric coprime array is proposed,and its properties are analyzed and proved,including the influence of each parameter of the array on the total array element number and the continuous array element number of the difference array,and the fuzziness analysis of the physical array element range estimation.Compared with the existing symmetric nested arrays,displaced symmetric coprime array has larger physical array aperture and more virtual degree of freedom,which can effectively improve the estimation performance of signal positioning parameters.