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|Title:||Incorporating classifications in the PMHT|
|Citation:||Proceedings of the 2001 Workshop on Defence Applications of Signal Processing, July 2002, Barossa Valley, Australia / pp. 74-78.|
|Conference Name:||Workshop on Defence Applications of Signal Processing (2002 : Barossa Valley, South Australia)|
|D A Gray , S J Davey , and R L Streit|
|Abstract:||When tracking more than one object a key problem is that of associating measurements with particular tracks. Recently, powerful statistical approaches such as Probabilistic Multi-Hypothesis Tracking (PMHT) and Probabilistic Least Squares Tracking have been proposed to solve the problem of measurement to track association. However, in practice other information may often be available, typically classification measurements from automatic target recognition algorithms, which help associate certain measurements with particular tracks. An extension to the Bayesian PMHT approach which allows noisy classification measurements to be incorporated in the tracking and association process is presented. Example results are given to illustrate the performance improvement that can result from this approach.|
|Appears in Collections:||Electrical and Electronic Engineering publications|
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