Title :
Improved particle filtering schemes for target tracking
Author :
Chen, Zhe ; Kirubarajan, Thia ; Morelande, Mark R.
Author_Institution :
Commun. Res. Lab., McMaster Univ., Hamilton, Ont., Canada
Abstract :
In this paper, we propose two improved particle filtering schemes for target tracking, one based on a gradient proposal and the other based on the turbo principle. We present the basic ideas and derivations and show detailed results of three tracking applications. Favorable experimental findings have shown the efficiency of our proposed schemes and their potential in other tracking scenarios.
Keywords :
Bayes methods; Kalman filters; Monte Carlo methods; gradient methods; recursive estimation; sequential estimation; target tracking; tracking filters; Bayesian bootstrap filter; extended Kalman filter; filtering schemes; gradient method; recursive Bayesian estimation; sequential Monte Carlo sampling; sequential important sampling; target tracking; tracking filters; turbo principle; Bayesian methods; Filtering; Noise measurement; Particle filters; Proposals; Recursive estimation; Signal processing; State-space methods; Target tracking; Yield estimation;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 2005. Proceedings. (ICASSP '05). IEEE International Conference on
Print_ISBN :
0-7803-8874-7
DOI :
10.1109/ICASSP.2005.1415966
