For most tracking applications the Kalman filter is reliable and efficient, but it is limited to a relatively restricted class of linear Gaussian problems. To solve problems beyond this restricted class, particle filters are proving to be dependable methods for stochastic dynamic estimation. This cutting-edge book introduces the latest advances in particle filter theory, discusses their relevance to defence surveillance systems, and examines defence-related applications of particle filters to nonlinear and non-Gaussian problems. nonlinear filter designs and more precisely predict the performance of these designs. You can also apply particle filters to tracking a ballistic object, detection and tracking of stealthy targets, tracking through the blind Doppler zone, bi-static radar tracking, passive ranging (bearings-only tracking) of manoeuvering targets, range-only tracking, terrain-aided tracking of ground vehicles, and group and extended object tracking.
- | Author: Branko Ristic
- | Publisher: Artech Print on Demand
- | Publication Date: January 31, 2004
- | Number of Pages: 318 pages
- | Language: English
- | Binding: Hardcover
- | ISBN-10: 158053631X
- | ISBN-13: 9781580536318
