Preprocessing in radar tracking filters

This paper discusses preprocessing in a tracking filter to estimate the parameters of target motion, such as position and velocity. We use orthogonal coordinates, with the target position as the radar observation data. Typical examples of tracking filters are the Kalman filter and the α-β filter. In a Kalman filter, although the tracking accuracy is high, the computation load is heavy. Consequently, a simplified version of the Kalman filter, the α-β filter, is used. The α-β filter has problems in tracking accuracy, although the computation load is low. Another difficulty with the α-β filter concerns its application to radar tracking when the observation noise varies with sampling time or when the sampling interval is non-uniform. In such cases, the Kalman filter must be used to achieve adequate tracking performance. This paper proposes a method in which the tracking filter consists of a Kalman filter with preliminary integration of multiple observation data, obtained at different sampling times, into a single observed datum. It is shown that the proposed tracking filter can be approximated by a tracking filter in which a Kalman filter is used for each sample. The tracking accuracy and the computation time are evaluated by computer simulation.