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Performance Prediction of the MHT Algorithm for Tracking under Cluttered Environments  

정영헌 (국방과학연구소)
Publication Information
Journal of the Institute of Electronics Engineers of Korea SC / v.41, no.4, 2004 , pp. 13-20 More about this Journal
Abstract
In this paper, we developed a method for predicting the tracking performance of the multiple hypothesis tracking (MHT) algorithm. The MHT algerithm is known to be a measurement-oriented optimal Bayesian approach and is superior to any other tracking filters because it takes into account the events that the measurements can be originated from new targets and false alarms as well as interesting targets. In the MHT algorithm, a number of candidate hypotheses are generated and evaluated later as more data are received. The probability of each candidate hypotheses is approximately evaluated by using the hybrid conditional average approach (HYCA). We performed numerical experiments to show the validity of our performance prediction.
Keywords
Target-tracking; MHT algorithm; Performance prediction; HYCA approach;
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