Beyond the Kalman Filter: Particle Filters for Tracking Applications
Be the First to Write a Review and tell the world about this title!Books on similar topics, in best-seller order: Books from the same publisher, in best-seller order:
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.
Table of Contents
Part I - Theoretical Concepts.
Introduction - Nonlinear Filtering. The Problem
and Its Conceptual Solutions. Optimal Algorithms. Multiple Switching Dynamic Models.
Basics of Target Tracking. Summary.
Suboptimal Nonlinear Filters - Analytic Approximations. Numerical
Methods. Gaussian Sum Filters. Unscented Kalman Filter. Summary.
A Tutorial on Particle Filters - Monte Carlo Integration.
Sequential Importance Sampling. Resampling. Selection of Importance Density.
Versions of Particle Filters. Summary.
Cramér-Rao Bounds for Nonlinear Filtering - Background. General
Recursive Calculations. Special Cases. Multiple Switching Dynamic Models. Probability
of Detection Less than 1. Summary.
Part II - Tracking Applications.
Tracking a Ballistic Object.
Bearings-Only Tracking.
Range-Only Tracking.
Bistatic Radar Tracking.
Tracking Targets Through Blind
Doppler.
Terrain Aided Tracking.
Detection and Tracking of Stealthy Targets.
Group and Extended Object Tracking.
About the Author(s)
Branko
Ristic is a senior research scientist in the Tracking and Sensor
Fusion Group at the ISR Division of DSTO, Edinburgh, Australia. In 2002 he was
awarded the Defence Science Fellowship by the Information Sciences Laboratory
of DSTO. He earned his Ph.D. at the Signal Processing Research Centre of Queensland
University of Technology, Australia.
Sanjeev
Arulampalam is a senior research scientist in the Submarine Combat
Systems Group, Maritime Operations Division of DSTO, Edinburgh, Australia. In
2000 he was awarded the Anglo-Australian postdoctoral fellowship by the Royal
Academy of Engineering, London. He earned his Ph.D. in electrical and electronics
engineering at the University of Melbourne, Australia.
Neil
Gordon is a senior research scientist in the Tracking and Sensor
Fusion Group at the ISR Division of DSTO, Edinburgh, Australia. Dr Gordon earned
his Ph.D. in statistics at the Imperial College, University of London.
|
