TDM-MIMO High-resolution Radar Array Optimization And DOA Algorithm Research

Spatial resolution is an important indicator of radar detection capability.Achieving high resolution of radar can obtain detailed target information,which is beneficial to the identification of target categories and attributes.Therefore,the research on highresolution radar is of greater significance in both military and civilian fields.When the uniform linear array performs DOA estimation,the resolution and the maximum number of estimable targets are limited by the actual number of array elements.The sparse array can break through this limitation,The difference coarray or sum-difference coarray can be obtained by difference or sum-difference of the received signals from each element,which improve the resolution of DOA estimation and overcome a difficulty of underdetermined estimation of the number of targets is more than elements'.TDMMIMO radar is widely used because of its simple system structure and low hardware cost.Based on the above reasons,the thesis studies the array optimization method of sparse arrays based on TDM-MIMO and the corresponding DOA algorithm.The main work is as follows:First of all,the thesis introduces two kinds of coarray for sparse arrays—difference coarray and sum-difference coarray.According to these two coarrays,the genetic algorithm,particle swarm optimization,and simulated annealing algorithm are respectively applied with redundancy as the cost function.By optimizing the arrangement of non-uniform sparse arrays,the minimum redundant arrays under the two optimization methods are obtained,and the final optimization effects of the three algorithms are compared.In addition,for the joint optimization of the TDM-MIMO transmitting array and receiving array,three algorithms are applied to obtain the optimal arrangement of the transmitting and receiving array.Secondly,Aiming at the problem that the equivalent receiving array of the sparse transmitting and receiving antenna array of TDM-MIMO is also sparse,the thesis studies the DOA algorithm of the sparse arrays.Use spatial smoothing algorithm and matrix reconstruction algorithm to reconstruct the received signal covariance matrix of the difference coarray,use the VCAM algorithm to generate the received signal covariance matrix of the sum-difference coarray,and use the MUSIC algorithm to the processed covariance matrix performing DOA estimation.The simulation results show that the sparse array can achieve higher resolution and degree of freedom,in other words,higher DOA performance,than the uniform array with the same number of elements.Finally,for the problem of a large number of coherent signal sources in radar array signal processing,the thesis introduces a method for generating virtual arrays based on array interpolation,which can be used for virtual uniform arrays generated by sparse arrays,and then use the same algorithm as uniform arrays performs DOA estimation of coherent signal sources.Simulations show that the algorithm can solve the problem of coherent target resolution.