Joint Space-time Parameter Estimation With Coprime Sampling On A Uniform Circular Array

Space-time parameter estimation is an important research topic of array signal processing technology,and studied intensively in cognitive radio and synthetic aperture radar.In order to achieve a joint estimation of the space-time parameters,the signal needs to be digitally sampled.The traditional uniform sampling scheme requires a higher sampling rate to meet the Nyquist condition,which brings a great burden to both analog and digital processing.Because of its low sampling rate and better capability of multi-target processing,the coprime sampling is becoming attractive in the field of space-time parameter estimation.However,the existing methods only are limited to linear array and can not be directly extended to other array configurations.Because of the flexibility in applications and 360° azimuth coverage,the uniform circular array has a wide range of applications in practice.In this paper,the space-time parameters estimation for uniform circular array with coprime sampling is studied.The main work is summarized as follows:1.The subspace based space-time parameter estimation method for uniform circular array with coprime sampling is studied.By utilizing the phase-mode excitation theory,the uniform circular array is mapped to the linear array,and the space-time two dimensional virtual array with Vandermonde structure is constructed,the method of spatial smoothing is used to recover the covariance matrix with full rank,so as to extend the coprime sampling method to the uniform circular array and proposed the subspace method based joint angle-Doppler estimation method for uniform circular array with coprime sampling.Simulation results show that compared with the uniform sampling method,the proposed method has better multi-target processing capability and better estimation accuracy.Furthermore,the influence of residual term of the beamspace transformation is analyzed in the case of sparse uniform circular array,thus the space-time virtual array for sparse uniform circular array with coprime sampling can be modeled.Based on the array interpolation method,we construct uniform rectangular array structure of space-time virtual array and apply the subspace method to joint angle-Doppler estimation for sparse uniform circular array with coprime sampling.Simulation results show that by introducing a sparse uniform circular array,a larger array aperture can be obtained with fewer antenna elements,and thus better target estimation performance is achieved.2.The joint estimation of the space-time parameters of uniform circular array based on continuous compression is studied.The subspace based space-time parameters estimation methods for coprime sampling uniform circular array rely on spatial smoothing to construct the covariance matrix,which suffer from loss of array aperture.On the other hand,when introducing phase mode transformation,the mapping error inevitably exists,which leads to the performance degradation of the algorithm.For the sparse uniform circular array,the angle coverage may be reduced because of the array interpolation.Aiming at the above problems,this paper is based on the phase mode excitation theory,put forward a compressed sensing continuous space-time parameter estimation method for uniform circular array with coprime sampling.Here,the beamspace transformation is used to establish the relationship between the beamspace array steering vector and the Vandermonde structure matrix,so that the continuous compressive sensing method is extended to the space-time parameter estimation of the uniform circular array.The method can effectively reduce the mapping error and achieve the angle coverage without loss of the array aperture.Simulations show the better estimation accuracy and target resolution compared with subspace based method.