Research On Decoupling Technique And DOA Estimation Algorithm In MIMO Radar System

Multi input multi output radar is a new radar system based on MIMO communication technology.MIMO radar system transmits a group of mutually orthogonal signals by transmitting antennas,forming broadband non-directional beam in space.Then,it receives and processes the echo signal through the multi receive antennas.Because the waveform diversity technology is used in the MIMO radar,the MIMO radar system can make up for the shortcomings of the traditional phased array radar to a certain extent,such as improving the resolution performance of the target,enhancing the interference suppression ability,improving the system freedom,flexible design of the transmitting pattern,etc.Due to the advantages of MIMO radar,a large number of super-resolution algorithms based on the ideal array model have appeared in recent years.However,the performance of the algorithm will be seriously degraded due to the mutual coupling effect between the array elements in the actual project,so the MIMO radar super-resolution algorithm with unknown mutual coupling effect has become the research trend in recent years.Based on the single input multi output system,this paper focuses on the design of DOA estimation algorithm,the unknown coupling effect between elements and the decoupling technology in the basics MIMO radar system.The main research contents and contributions can be summarized as follows:1.The direction of arrival estimation model of single input radar system is introduced.The music algorithm and ESPRIT algorithm based on the on grid DOA estimation model and the sparse Bayesian learning algorithm(OGSBI)based on the off grid DOA estimation model are studied.Through simulation experiments,the performance advantages of off grid DOA estimation model over grid model in DOA estimation are described.2.Introduces the on-grid DOA estimation model,matched filtering method,music algorithm and ESPRIT algorithm in MIMO radar system.A reduced dimension transform is proposed to compress the matched data,and the Vandermonde structure of the direction matrix of the MIMO radar system is obtained.Then a sparse model is established to link the DOA estimation problem with the off-grid optimization problem,and the root sparse Bayesian learning algorithm(OGRSBL)is used to solve the DOA estimation of the MIMO radar system.3.The unknown mutual coupling between antenna in DOA estimation model and the estimation model of DOA on-grid and off-grid in MIMO radar system with unknown mutual coupling effect are studied.The sparse Bayesian learning algorithm with unknown mutual coupling effect is studied.The algorithm estimates all unknown parameters including DOA,unknown mutual coupling and so on.In order to reduce the computational complexity of the algorithm,a grid evolution method is proposed.In this method,a coarse initial grid is set up.In the process of iterative learning,new grid is continuously fission at the position where the true DOAs target may exist,so that the grid is not evenly arranged.By setting the fission conditions,the optimal fission can be achieved.Thus,the number of grids in the off-grid DOA estimation model is reduced and the computational complexity of the algorithm is reduced.