Name
Abstract | ||
|---|---|---|
Target tracking using delayed, out-of-sequence measurements is a problem of growing importance due to an increased reliance on networked sensors interconnected via complex communication network architectures. In such systems, it is often the case that measurements are received out-of-time-order at the fusion center. This paper presents a Bayesian solution to this problem and provides approximate, implementable algorithms for both cluttered and non-cluttered scenarios involving single and multiple time-delayed measurements. Such an approach leads to a solution involving the joint probability density of current and past target states. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1016/S1566-2535(03)00037-X | Information Fusion |
Keywords | Field | DocType |
Time delayed measurement,Networked sensor,Smoothing,Augmented state,Target tracking | Mathematical optimization,Joint probability distribution,Joint Probabilistic Data Association Filter,Clutter,Kalman filter,Gaussian,Smoothing,Fusion center,Mathematics,Bayesian probability | Journal |
Volume | Issue | ISSN |
4 | 3 | 1566-2535 |
Citations | PageRank | References |
30 | 4.08 | 1 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Subhash Challa | 1 | 252 | 24.96 |
| Robin J. Evans | 2 | 1333 | 168.58 |
| Xuezhi Wang | 3 | 30 | 4.08 |