TY - GEN
T1 - Multiple transition mode multiple target track-before-detect with partitioned sampling
AU - Ebenezer, Samuel P.
AU - Papandreou-Suppappola, Antonia
PY - 2014/1/1
Y1 - 2014/1/1
N2 - In this paper, we extend the multiple model track-before-detect method to track all possible target combinations at low signal-to-noise ratios. Given a maximum number of targets, the method estimates the posterior probability density function of the multitarget state vector, the corresponding target existence probabilities, and the probabilities of all possible target combinations. As the particle filter implementation of this method requires a large number of particles to achieve high tracking performance, we propose an efficient partition based proposal function method by partitioning the multiple target space into a set of single target spaces. We also integrate the Markov chain Monte Carlo Metropolis-Hastings method into the particle proposal process to improve sample diversity. The proposed algorithm is validated by tracking five targets in very low signal-to-noise ratios (SNRs).
AB - In this paper, we extend the multiple model track-before-detect method to track all possible target combinations at low signal-to-noise ratios. Given a maximum number of targets, the method estimates the posterior probability density function of the multitarget state vector, the corresponding target existence probabilities, and the probabilities of all possible target combinations. As the particle filter implementation of this method requires a large number of particles to achieve high tracking performance, we propose an efficient partition based proposal function method by partitioning the multiple target space into a set of single target spaces. We also integrate the Markov chain Monte Carlo Metropolis-Hastings method into the particle proposal process to improve sample diversity. The proposed algorithm is validated by tracking five targets in very low signal-to-noise ratios (SNRs).
UR - http://www.scopus.com/inward/record.url?scp=84905266274&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84905266274&partnerID=8YFLogxK
U2 - 10.1109/ICASSP.2014.6855160
DO - 10.1109/ICASSP.2014.6855160
M3 - Conference contribution
AN - SCOPUS:84905266274
SN - 9781479928927
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - 8008
EP - 8012
BT - 2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014
Y2 - 4 May 2014 through 9 May 2014
ER -