PREPROCESSING IN RADAR TRACKING FILTERS

This paper discusses preprocessing in a tracking filter to estimate th e parameters of target motion, such as position and velocity. We use o rthogonal coordinates, with the target position as the radar observati on data. Typical examples of tracking filters are the Kalman filter an d the alpha-beta filter. In a Kalman filter, although the tracking acc uracy is high, the computation load is heavy. Consequently, a simplifi ed version of the Kalman filter, the alpha-beta filter, is used. The a lpha-beta filter has problems in tracking accuracy, although the compu tation load is low. Another difficulty with the alpha-beta filter conc erns its application to radar tracking when the observation noise vari es with sampling time or when the sampling interval is non-uniform. In such cases, the Kalman filter must be used to achieve adequate tracki ng performance. This paper proposes a method in which the tracking fil ter consists of a Kalman filter with preliminary integration of multip le observation data, obtained at different sampling times, into a sing le observed datum. It is shown that the proposed tracking filter can b e approximated by a tracking filter in which a Kalman filter is used f or each sample. The tracking accuracy and the computation time are eva luated by computer simulation. (C) 1998 Scripta Technica.