|Abstract:||As navigation systems are being developed, it is apparent that accurate and precise positioning is an imperative for both military and civilian ground vehicle guidance. There is also a significant desire for cost-effective navigation systems that civilians can afford. As the need for this technology increases, navigation systems incorporating multiple sensors have been developed and relied upon in many navigation situations. In this work, radar and GPS measurements are utilized in a multisensor fusion scheme that allows for a robust ranging solution utilizing the accuracy of a DGPS solution and the higher update rate of the radar solution in a Kalman filter. One difficulty when navigating with radar is the problem of target selection, which is the determination of the correct channel of the radar that is tracking the desired target. To accomplish this task, a probabilistic data association filter (PDAF) is utilized to determine a weighted mean of the channels’ solutions that fall within a validation region set in the algorithm. This paper intends to evaluate and make conclusions on the performance of a GPS/Radar fusion algorithm in various vehicle convoying scenarios.|
Proceedings of the ION 2017 Pacific PNT Meeting
May 1 - 4, 2017
Marriott Waikiki Beach Resort & Spa
|Pages:||419 - 428|
|Cite this article:||
Sherer, Tyler P., Martin, Scott M., Bevly, David M., "Keynote: Radar Probabilistic Data Association Filter with GPS Aiding for Target Selection and Relative Position Determination," Proceedings of the ION 2017 Pacific PNT Meeting, Honolulu, Hawaii, May 2017, pp. 419-428.
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