Issues in Target Tracking
Peter Willett · 2010
In this lecture we discuss a number of concerns and items of interest that related to the tracking of targets in clutter. We begin with a discussion of performance evaluation methods. The familiar CRLB is shown to be adjusted in a straightforward way when deterministic trajectories are estimated in the presence of measurement-origin uncertainty (false alarms and missed detections); indeed, the same is true for nondeterministic ones, meaning those with process noise. We then mention the HYCA (hybrid conditional averaging) approach, which has considerable appeal in that it can predict the track-life as opposed to the accuracy of tracks that are kept. We then discuss track testing: the sequential probability ratio test (SPRT) for track acceptance, the Page test for track deletion, and here we most especially discuss variants (such as Shiryaev) for the case of fluctuating targets, as would be found in multi-static (fused) systems. Finally, we mention some management issues, specifically aspects of sampling time for multi-sensor systems, sensor placement with target tracking in mind, and the choice of waveform when the goal is tracking. I. PERFORMANCE EVALUATION A. The Static Case: The CRLB When Measurements are of Uncertain Origin 1) Introduction: In many estimation situations measurements are of uncertain origin. This is best exemplified by the target-tracking situation in which at each scan a number mt of measurements are obtained, and it is not known which, if any, of these