Switched Kalman filter-interacting multiple model algorithm based on optimal autoregressive model for manoeuvring target tracking

Abstract

A manoeuvring target tracking algorithm based on the autoregressive (AR) model is proposed. First, the AR model is incorporated into the Kalman filter (KF) for target tracking. The closed-form solution of the AR model coefficients is obtained by minimising the mean-square tracking error, and subject to the polynomial constraint of target motion. Then, based on the AR model, the proposed algorithm is constructed by combining the KF with the interacting multiple model (IMM) filter, coupled with the proposed detection schemes for manoeuvre occurrence and termination, as well as for switching initialisation. Simulations are performed to demonstrate the effectiveness of the AR model, and the proposed algorithm is compared with the IMM filter and variable-dimension filter in the manoeuvring scenario.