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Beyond the Kalman Filter, Particle Filters for Tracking Applications
Beyond the Kalman Filter, Particle Filters for Tracking Applications
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Beyond the Kalman Filter: Particle Filters for Tracking Applications

Author: Branko Ristic, Sanjeev Arulampalam, Neil Gordon
Item# 1141

For most tracking applications the Kalman filter is reliable and efficient, but it is limited to a relatively restricted class of linear Gaussian problems. 302 pages, hard cover. View Full Description

Category: Kalman Filter & Integration
Publisher: Artech House
Manufacturer Number: 1-58053-631-X
 


 
 
 
 

Beyond the Kalman Filter: Particle Filters for Tracking Applications

Author: Branko Ristic, Sanjeev Arulampalam, Neil Gordon

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. Packed with 867 equations, this book introduces the latest advances in particle filter theory, discusses their relevance to defense surveillance systems, and examines defense-related applications of particle filters to nonlinear and non-Gaussian problems.

With this hands-on guide, you can develop more accurate and reliable 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 maneuvering targets, range-only tracking, terrain-aided tracking of ground vehicles, and group and extended object tracking.

 

Publisher: Artech House Publishers
Copyright: 2004
ASIN: B011T7ZHFU