Beyond the Kalman Filter

The fundamental building block of a target tracking radar system is the filter for recursive target state estimation, with the Kalman filter being the best-known example. The authors of this work (all of Australia's Defense Science and Technology Organization) believe that particle filters relying on sequential Monte Carlo estimation and non-Gaussian dynamic estimation are growing to be more useful than Kalman filters. Writing for engineers, they review the current status of nonlinear/non-Gaussian filtering and describe common techniques. They then turn their attention to an array of target tracking applications, most of which rely on particle filters. Annotation c2004 Book News, Inc., Portland, OR (booknews.com)