A Comparison of Three Algorithms for Tracking Dim Targets

Tracking of dim, or low signal-to-noise ratio (SNR), targets is commonly achieved using track-before-detect (TBD) techniques. While traditional tracking algorithms operate on detections, typically formed by applying an intensity threshold to the sensor data, TBD algorithms operate directly on un-thresholded sensor data. Increasing the information available to the tracker in this way potentially allows tracking of lower SNR targets compared to trackers using detections. This paper compares three algorithms on simulated data containing a single dim target: a histogram PMHT algorithm and a particle filter, both of which could be classified as track-before-detect algorithms, and a PDA algorithm which operates on detections. The algorithms are compared in terms of detection performance, false track rate and RMS error.