Name
Abstract | ||
|---|---|---|
The probability hypothesis density (PHD) filter, which was derived from finite set statistics is a promising approach to multi-target tracking. An analytical closed-form solution for the PHD, named Gaussian mixture PHD Filter, is given for linear Gaussian target dynamics with Gaussian births by B. Vo and W. Ma. Based on the Gaussian mixture PHD filter, in this paper, without consideration of data association technique, a method using three passive sensors for multi-target location system is proposed, which can restrain greatly the false triangulations, calls ghosts, where the measurements of the bearing-only multi-target location system are spoiled by clutter. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/ICIF.2007.4407968 | Fusion |
Keywords | Field | DocType |
finite set statistics,bearing-only,multitarget tracking,multi-target location,probability hypothesis density filter,gaussian mixture,multitarget location,target tracking,false triangulations,random finite set,linear gaussian target dynamics,data association technique,bearing-only multitarget location,gaussian processes,direction-of-arrival estimation,filtering theory,clutter,sensor fusion,probability,gaussian mixture phd filter,closed form solution,statistics,aerodynamics | Gaussian filter,Gaussian random field,Pattern recognition,Computer science,Clutter,Closed-form expression,Sensor fusion,Gaussian,Gaussian process,Artificial intelligence,Gaussian function | Conference |
Volume | Issue | ISBN |
null | null | 978-0-662-45804-3 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| hongjian zhang | 1 | 29 | 2.56 |
| Zhongliang Jing | 2 | 351 | 39.38 |
| Shiqiang Hu | 3 | 56 | 6.96 |