Research on Target Parameter Estimation Method of Radar Communication Integrated System Based on Grid-less Compression Sensing

‍ ‍In this paper， an integrated radar and communication system based on Orthogonal Frequency Division Multiplexing （OFDM） is considered. And based on the excellent sparsity of target delay and Doppler in time and frequency domain， a variety of grid-less two-dimensional delay-Doppler estimation methods are provided solve the problem of poor performance caused by mismatch of estimation dictionary of traditional sparse recovery methods， effectively improving the performance of moving target parameter estimation. For the problems of poor target estimation accuracy and low recovery success rate under low SNR， this paper provides a multiple measurement vector （MMV） model to effectively solve the problem of poor target parameter estimation performance under the above problems. Aiming at the problem that the two-dimensional atomic norm based on the traditional vector calculation method will generate a huge amount of calculation. this paper uses semi-definite programming （SDP） to decouple the high-dimensional Toeplitz matrix of the traditional method into two low-dimensional Toeplitz matrices， which can reduce the computational complexity by several orders of magnitude， while retaining the advantages of atomic norm in super resolution performance. This method can be applied to OFDM multi subcarrier and multi symbol waveform systems. Numerical results show that the algorithm maintains the estimation performance advantage of atomic norm class algorithms， and simulation reduces the computational complexity.