Multiple-Hypothesis Trilateration and Tracking with Distributed Radars

Abstract

A novel algorithm to associate and trilaterate detections from multiple distributed radars is presented. The algorithm provides for flexible track state representations. The coordinate system of a track is switched from the measurement coordinates (range-Doppler) to cartesian coordinates when a detection from another sensor is associated to the track. In the case of multiple targets and false alarms we run into the complication of multiple association possibilities. These can be resolved by using a multi-hypothesis algorithm. In general, correctly formed tracks will have more likely associations. Therefore, hypotheses describing these tracks will be favored. Simulations with one or two targets and different false alarm rates show the need to preserve multiple hypotheses of the world state. Tracking performance for various false alarms rates is evaluated