DocumentCode
22018
Title
Bernoulli Forward-Backward Smoothing for Track-Before-Detect
Author
Shanhung Wong ; Ba Tuong Vo ; Papi, Francesco
Author_Institution
Dept. of Electr. & Comput. Eng., Curtin Univ., Bentley, WA, Australia
Volume
21
Issue
6
fYear
2014
fDate
Jun-14
Firstpage
727
Lastpage
731
Abstract
Track-before-detect (TBD) refers to an alternative approach to tracking which utilizes the full sensor information rather than detections obtained from thresholding. In this letter we investigate whether forward-backward smoothing for TBD can increase performance. We propose a novel algorithm based on the random finite set framework which incorporates the TBD sensor model with multi-scan information. The algorithm is tested on a typical scenario which confirms improved tracking.
Keywords
Bayes methods; random processes; set theory; signal detection; smoothing methods; tracking filters; Bernoulli filter; Bernoulli forward-backward smoothing; TBD sensor model; full sensor information; multiscan information; random finite set framework; recursive Bayesian approach; track-before-detect; tracking filter; Bayes methods; Density measurement; Proposals; Signal processing algorithms; Signal to noise ratio; Smoothing methods; Time measurement; Random finite set; smoothing; track-before- detect;
fLanguage
English
Journal_Title
Signal Processing Letters, IEEE
Publisher
ieee
ISSN
1070-9908
Type
jour
DOI
10.1109/LSP.2014.2310137
Filename
6758349
Link To Document