This second edition has undergone substantial revision from the 1999 first edition, recognizing that a lot has changed in the multiple target tracking field. One of the most dramatic changes is in the widespread use of parti...

Buy Now From Amazon

This second edition has undergone substantial revision from the 1999 first edition, recognizing that a lot has changed in the multiple target tracking field. One of the most dramatic changes is in the widespread use of particle filters to implement nonlinear, non-Gaussian Bayesian trackers. This book views multiple target tracking as a Bayesian inference problem. Within this framework it develops the theory of single target tracking. In addition to providing a detailed description of a basic particle filter that implements the Bayesian single target recursion, this resource provides numerous examples that involve the use of particle filters.

Similar Products

Beyond the Kalman Filter: Particle Filters for Tracking Applications (Artech House Radar Library) (Artech House Radar Library (Hardcover))Design and Analysis of Modern Tracking Systems (Artech House Radar Library)Advanced Kalman Filtering, Least-Squares and Modeling: A Practical HandbookApplied Optimal Estimation (The MIT Press)Optimal Control Theory: An Introduction (Dover Books on Electrical Engineering)Optimal Control and Estimation (Dover Books on Mathematics)Optimal State Estimation: Kalman, H Infinity, and Nonlinear ApproachesEstimation with Applications to Tracking and Navigation