Unmanned Ship Tracking Algorithm Based on MIMO Radar

With the rapid development and widespread application of autonomous unmanned systems, the application scenarios of unmanned ships in maritime traffic are also expanding. However, this also brings hidden dangers to navigation safety and maritime traffic safety. In order to reduce the occurrence of maritime accidents, it is particularly important to improve the perception ability of unmanned ships of target information in the surrounding environment, especially the information of moving targets. This paper proposes an unmanned ship tracking algorithm based on MIMO radar to solve the problem of real-time tracking of surrounding moving targets by unmanned ships in a marine environment with impulse noise characteristics. This study uses the multi-input and multi-output characteristics of MIMO radar, combines the maximum correntropy criterion and the projected approximate subspace tracking (PAST) algorithm to estimate the feature vector in the impulse noise environment, and then combines the estimation of signal parameters via invariance techniques (ESPRIT) algorithm to accurately estimate the target's direction of departure (DOD) and direction of arrival (DOA), and proposes the MCC-PAST-ESPRIT algorithm. The simulation experimental results show that compared with the PAST-ESPRIT algorithm which is based on the minimum mean square error criterion, the method proposed in this paper shows better robustness and accuracy in the impulse noise environment.