Radar probabilistic data association filter/DGPS fusion for target selection and relative range determination for a ground vehicle convoy

Abstract

As navigation systems are being developed, it is apparent that cost-effective accurate and precise positioning is an imperative for both military and civilian ground vehicle guidance. As this need increases, navigation systems incorporating multiple sensors have been developed and relied upon in many navigation situations. In this work, radar and global positioning system (GPS) measurements are utilized in a multi-sensor fusion scheme allowing for a robust ranging solution utilizing the accuracy of a differential GPS (DGPS) solution and higher update rate of the radar solution in a Kalman filter. A probabilistic data association filter (PDAF) is utilized to determine a weighted mean of the radar channels' solutions that fall within a validation region set in the algorithm. In this work, radar was used to track vehicles and not surrounding landmarks. This paper intends to evaluate the accuracy and availability of a GPS/radar fusion algorithm in vehicle convoying scenarios.