Estimation Of Target Direction Using Vector Coprime Arrays

Direction of Arrival(DOA)estimation is a crucial component in the field of array signal processing,which has been widely applied in radar,sonar,and wireless communication.Currently,traditional DOA estimation algorithms are based on uniform linear arrays.However,to achieve larger array aperture and higher array degrees of freedom,additional physical array elements are often required,which increases the system’s hardware and software costs.To address this issue,using coprime arrays is a good choice.Compared to uniform linear arrays,coprime arrays exhibit better performance in terms of array aperture and array degrees of freedom with the same number of array elements,thus receiving widespread applications.In this paper,based on coprime array signal processing,we investigate the DOA estimation algorithm of vector coprime arrays.The main work is as follows:1.Firstly,a DOA estimation algorithm based on vector coprime array subarray decomposition is proposed for the array structure of vector coprime arrays.This algorithm first decomposes the vector coprime array into two vector sparse uniform linear subarrays,and then processes each of these two subarrays using traditional DOA estimation algorithms.Finally,the results of the two subarrays are combined and analyzed to obtain the true direction of the incident signal.This algorithm fully utilizes the advantage of the large aperture of the vector coprime array.Compared with a vector uniform linear array with the same number of elements,it has higher angular resolution and DOA estimation performance.Simulation results verify the effectiveness of the algorithm.2.Although the DOA estimation algorithm based on vector coprime array subarray decomposition well utilizes the advantage of vector coprime arrays in terms of aperture,this algorithm has limited degrees of freedom due to the number of elements in the subarray.To increase the number of degrees of freedom,we propose a DOA estimation algorithm based on vector coprime array virtual domain processing.This algorithm extends the vector coprime array to the virtual domain and generates an equivalent virtual linear array in the virtual domain.This virtual linear array is only uniformly continuous in the middle part.Since traditional DOA estimation algorithms are designed for uniform linear arrays,we only process the virtual uniform linear subarray in the middle part and use spatial smoothing techniques or Toplitz matrix reconstruction techniques to obtain a full-rank covariance matrix.Finally,the traditional DOA estimation algorithm is used to process this full-rank covariance matrix.Compared with the DOA estimation algorithm of a vector uniform linear array,this algorithm based on vector coprime array virtual domain processing can obtain higher degrees of freedom under the same physical number of elements.Simulation results verify the effectiveness of the algorithm.3.Although the DOA estimation algorithm based on vector coprime array virtual domain processing can achieve high degrees of freedom,signal information and degrees of freedom are lost because only the virtual uniform linear subarrays that are continuous in the middle part of the virtual linear array are processed during the processing of the virtual linear array.To reduce this loss,we propose a DOA estimation algorithm based on vector supplementary coprime array virtual domain processing.This algorithm uses an additional vector coprime array to supplement the virtual linear array generated by the original vector coprime array,thus improving the continuity and uniformity of the virtual linear array.The algorithm then uses the traditional DOA estimation algorithm to process the full-rank covariance matrix of the extended virtual uniform linear array,which can achieve higher degrees of freedom and maintain the signal information of the virtual linear array.Simulation results verify the effectiveness of the algorithm.