Research On High Accuracy Angle Estimation Algorithm For MIMO Radar Under Array Error Condition

MIMO radar is an emerging hot research topic in the past decade.Its full name is multi-input multi-output radar.Among the many research directions of MIMO radar,the angle estimation of the target has been paid much attention by many researchers.In order to have better practical value in practical engineering,this paper takes MIMO radar as the research object,takes tensor algebra as the mathematical foundation,and introduces a high-precision angle estimation algorithm for MIMO radar based on tensor under the condition of array error.Firstly,in order to better introduce the traditional MIMO radar angle estimation algorithm,the working principle and signal model of MIMO radar are described in detail.On this basis,several classical MIMO radar angle estimation algorithms are introduced,including Capon algorithm,MUSIC algorithm,ESPRIT algorithm and ESPRIT-MUSIC algorithm.Starting from the theoretical basis of these algorithms,this paper introduces the derivation process of the algorithms,and then uses numerical experiments to analyze and evaluate the performance of each algorithm,summarizes the advantages and disadvantages of each algorithm,and summarizes the characteristics of each algorithm.Secondly,the basic concepts and basic algorithms of tensors are described in detail,and then the radar signal model of MIMO based on tensors is established.The estimation of joint direction-of-departure(DOD)and direction-of-arrival(DOA)for strictly noncircular targets in multiple-input multiple-output(MIMO)radar with unknown mutual coupling is considered,and a tensor-based angle estimation method is proposed.In the proposed method,making use of the banded symmetric Toeplitz structure of the mutual coupling matrix,the influence of the unknown mutual coupling is removed in the tensor domain.Due to the use of both non-circularity and multidimensional structure of the detected signal,the algorithm in this paper has more outstanding angle estimation performance than the others subspace based algorithms.The results of numerical experiments show that the estimation performance of the proposed algorithm is better than that of other algorithms.Then,in order to effectively reduce the computational redundancy of the algorithm and improve the computational efficiency,a robust angle estimation method for noncircular targets based on unitary tensor decomposition with mutual coupling in multiple-input multiple-output(MIMO)radar is proposed.In this method,taking advantage of the centro-Hermitian characteristic of the augmented tensor to transform the sub-tensor into real-values tensor by the unitary transformation.Because the algorithm only needs real value operation,it has low operation complexity and greatly reduces the operation time.Simulation experiments verify the effectiveness and superiority of the proposed algorithm.Then,this paper investigates the issue of angle and array gain-phase error estimation in multiple-input multiple-output(MIMO)radar,and a tensor-based angle and gain-phase error estimation scheme is proposed.In our approach,the parallel factor(PARAFAC)decomposition is performed to estimate the transmit and receive direction matrices.Then the estimation of gain error can be obtained according to the relationship between the columns of direction matrices.After that,the linear feature of phase in the additional well-calibrated array element is utilized to estimate the angles.Finally,by fully using the phase characteristics of all arrays,the phase error can be obtained.Our approach can remove the influence of error accumulation,and thus it has superior angle and gain-phase error estimation performance,particularly under the condition of low signal-to-noise ratio(SNR).Numerical examples validate the superiority and effectiveness of the proposed scheme.Finally,in this paper,the estimation of joint angle and array gain-phase error in multiple-input multiple-output(MIMO)radar with unknown colored noise is investigated,and the tensor-based joint angle and array gain-phase error estimation is proposed.In the proposed method,the temporal uncorrelated property of unknown colored noise is utilized to construct a third-order tensor to remove the effect of unknown colored noise.Then parallel factor(PARAFAC)decomposition is utilized to achieve transmit direction matrix estimation and receive direction matrix estimation.The gain-phase error is estimated through Lagrange multipliers.After that,the angle estimation can be achieved through the estimation of gain-phase error.The proposed approach not only eliminates the influence of gain-phase error,but also removes the impact of unknown colored noise.Therefore,our method achieves superior estimation performance.Numerical examples demonstrate the superiority of the proposed approach.