Waveform selection based on detection-tracking performance
Wei Cao, Peter Willett, Yaakov Bar‐Shalom, Ruixin Niu · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1998
In this paper, radar/sonar waveform selection is investigated form a system engineering viewpoint using the hybrid conditional averaging (HYCA) method. HYCA is a recently developed technique for evaluating tracking performance, and is meeting with increased acceptance due to this ability to work with the dynamic interaction between tracking and imperfect detection. In a previous paper HYCA was used as an analysis tool to select among various apportionments of constant-frequency and linear frequency- sweep waveforms, and the effect of missed detections was incorporated; the tracking mechanism was taken as a Kalman filter. In this paper our analysis is refined to deal both with false alarms and an improved detection model. With respect to the former, the Kalman estimator has been replaced by a probabilistic data association filter, in which Poisson-distributed false-alarms may be included in a natural way. With respect to the latter, the resolution cells have been redefined according to a tessellating grid in range and range-rate, with the effect of detections in neighboring cells caused by ambiguity-function 'sidelobes' and over/undersampling accounted for.