Improving bias estimation precision via a more accuracy radar bias model (Q1720728)

Summary: Radar bias estimation is an important part of a multisensor tracking system. Because the radar bias models in current efforts are not sufficiently accurate, the bias estimation accuracy is not satisfied. First, a general radar bias model, in which the importance of the sensor-target pair-related bias is emphasized, is proposed in this paper. Moreover, the target-sensor pair-related bias is considered on the grounds of the impact of atmospheric refraction on the electromagnetic wave propagation path. Second, by using the augmented state vector with the target state and radar bias, a dynamic equation and measurement equation under the IMM framework are obtained. Last, the IMM-UKF estimator is utilized to obtain the target state and radar bias simultaneously. The numerical simulations show that the accuracy of the bias estimation together with the target states estimation can be improved via the proposed radar bias model.