Beyond The Kalman Filter Particle Filters For Tracking Applications


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Beyond the Kalman Filter: Particle Filters for Tracking Applications


Beyond the Kalman Filter: Particle Filters for Tracking Applications

Author: Branko Ristic

language: en

Publisher: Artech House

Release Date: 2003-12-01


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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 cutting-edge 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.

Beyond the Kalman Filter


Beyond the Kalman Filter

Author: Branko Ristic

language: en

Publisher: Artech House Publishers

Release Date: 2004-01


DOWNLOAD





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.

BEYOND THE KALMAN FILTER: PARTICLE FILTERS FOR TRACKING APPLICATIONS.


BEYOND THE KALMAN FILTER: PARTICLE FILTERS FOR TRACKING APPLICATIONS.

Author: BRANCO. RISTIC

language: en

Publisher:

Release Date: 2004


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