Name
Abstract | ||
|---|---|---|
The Histogram-Probabilistic Multi-Hypothesis Tracker (H-PMHT) is an efficient multi-target tracking approach to the Track-Before-Detect (TkBD) problem. However, it cannot adequately deal with fluctuating targets and this can degrade track management performance. By assuming an alternative measurement model based on a Poisson distribution, the H-PMHT algorithm can be re-derived to incorporate a time-correlated estimate of the component mixing terms, allowing for an improved measure for track quality. |
Year | Venue | Keywords |
|---|---|---|
2015 | 2015 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING (ICASSP) | Track-Before-Detect |
Field | DocType | ISSN |
Histogram,Pattern recognition,Computer science,Signal-to-noise ratio,Artificial intelligence,Poisson distribution,Track-before-detect | Conference | 1520-6149 |
Citations | PageRank | References |
1 | 0.39 | 4 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Han X. Vu | 1 | 12 | 1.69 |
| Samuel J. Davey | 2 | 103 | 10.27 |
| Sanjeev Arulampalam | 3 | 142 | 19.13 |
| Fiona Fletcher | 4 | 1 | 1.40 |
| Cheng-chew Lim | 5 | 963 | 65.94 |