Name
Abstract | ||
|---|---|---|
The geographic information (air route, sea route, air corridor, prohibited area, airport and etc.) and the spatial relative relation of the aircraft formation represent the equality and inequality constraints of the targets. The establishment of association and fusion between constraint information and passive multi-sensor is an important approach to improve the performance of target detection and tracking. The algorithm implementation of the passive multi-sensor box particle Probability Hypothesis Density (PHD) based on the boundary constraint is proposed. This algorithm utilizes the priori known constraints to narrow the birth targets searching and sampling region, which in favor of reducing invalid detections and calculations. The utilization of constraints information projection can further improve the tracking performance. The simulation results show that the proposed algorithm remarkably reduce the calculation with comparative tracking performance. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/ICInfA.2016.7831825 | 2016 IEEE International Conference on Information and Automation (ICIA) |
Keywords | Field | DocType |
Constraint information,passive sensor,target tracking,PHD | Probability hypothesis density filter,Mathematical optimization,Clutter,Computer science,Control theory,Information projection,Sampling (statistics),Atmospheric measurements,Filtering theory,Particle | Conference |
ISBN | Citations | PageRank |
978-1-5090-4103-9 | 0 | 0.34 |
References | Authors | |
4 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Feng Yang | 1 | 18 | 4.42 |
| Keli Liu | 2 | 0 | 0.34 |
| Hao Chen | 3 | 211 | 37.88 |
| Wanying Zhang | 4 | 0 | 0.68 |