Tracking multiple targets in MIMO radar via adaptive asymmetric joint diagonalization with deflation

In view of the low performance of adaptive asymmetric joint diagonalization (AAJD), especially its failure in tracking high maneuvering targets, an adaptive asymmetric joint diagonalization with deflation (AAJDd) algorithm is proposed. The AAJDd algorithm improves performance by estimating the direction of departure (DOD) and direction of arrival (DOA) directly, avoiding the reuse of the previous moment information in the AAJD algorithm. On this basis, the idea of sequential estimation of the principal component is introduced to turn the matrix operation into a constant operation, reducing the amount of computation and speeding up the convergence. Meanwhile, the eigenvalue is obtained, which can be used to estimate the number of targets. Then, the estimation of signal parameters via rotational invariance technique (ESPRIT) algorithm is improved to realize the automatic matching and association of DOD and DOA. The simulation results show that the AAJDd algorithm has higher tracking performance than the AAJD algorithm, especially when the high maneuvering target is tracked. The efficiency of the proposed method is verified.