Title :
A particle filter for track-before-detect
Author :
Salmond, D.J. ; Birch, H.
Author_Institution :
Defence Evaluation & Res. Agency, Farnborough, UK
Abstract :
A Bayesian track-before-detect particle filter is proposed. The filter provides a sample based approximation to the distribution of the target state directly from pixel array data. The filter also provides a measure of the probability that a target is present
Keywords :
Bayes methods; filtering theory; observers; probability; target tracking; Bayesian particle filter; approximation; observers; probability; state estimation; target tracking; track-before-detect problem; Background noise; Bayesian methods; Data mining; Maximum likelihood detection; Particle filters; Particle tracking; Position measurement; Sensor arrays; Target tracking; Time measurement;
Conference_Titel :
American Control Conference, 2001. Proceedings of the 2001
Conference_Location :
Arlington, VA
Print_ISBN :
0-7803-6495-3
DOI :
10.1109/ACC.2001.946220
