Radar Resource Management for Multiple Hypothesis Tracking
J.B.D. Cabrera, Lucas I. Finn, Shane Fairbrother · 2018
In traditional radar-based Multiple Hypothesis Tracking (MHT), objects are revisited on the basis of a scan of the Area of Interest or object-by-object with focused beams directed to the estimated position of each object. Both schemes aim to obtain a track picture, which represents the tracks in the scene in terms of their positions and uncertainties. This paper introduces three radar resource management algorithms with different philosophies but based on the common premise that densely packed objects should receive a larger amount of energy than isolated objects. In Algorithm 1, we only direct energy to objects with gate intersection, i.e. objects for which a measurement could gate with more than one track. The purpose is to resolve the potential conflicts between measurement-to-track assignments that would occur with gate intersections. This results in a increase of the update period of the remaining tracks. In Algorithm 2 the objective is to consolidate the track picture as a collection of tracks including those under temporary confusion. To do so, we select different times-on-object (TOO) to different tracks, to maximize an upper bound of the entropy of the track picture, viewed as a normalized intensity function. Algorithm 3 combines Algorithm 1 and Algorithm 2. Performance of the three algorithms is evaluated using the track purity, the RMS (Root-Mean-Squared) of the total track error, and the Mean Optimized Subpattern Assignment metric for tracks (T-MOSPA). Computer simulations indicate the superiority of Algorithm 3 over the other two and the baseline algorithm. Quantitatively, Algorithm 3 results on a 25.3% decrease in the RMS tracking error and an increase of 8.2% in the track purity with respect to the baseline scheme which uses constant TOOs and update periods for all tracks.