EFFICIENT TARGET TRACKING USING DYNAMIC-PROGRAMMING

A new dynamic programming (DP) algorithm has been developed for the detection and tracking of subpixel-sized, low signal-to-noise ratio (SNR) targets observed by side- or forward-looking imaging sensors. The advantages of DP are its sensitivity to weak targets and its robustness to maneuvers, sensor jitter, and impulsive noise. A distinguishing feature of (his approach is that target detection and tracking are combined into a single optimization procedure that takes into account statistical models of target motion, background noise, and clutter. Current work has led to a number of technical innovations that improve the performance and efficiency of the DP tracking algorithm, including the development of a new track scoring function, and an extension to the basic DP algorithm that reduces computational requirements by over an order of magnitude. A prototype infrared (IR) target tracking system incorporating these enhancements has been implemented for a step-staring IR camera application. Sensitivity improvements of several decibels over conventional sequential detection and tracking algorithms were realized.