Tracking and Data Fusion: A Handbook of Algorithms

Tracking and Data Fusion: A Handbook of Algorithms

This book, which is the<br>revised version of the 1995 text<br>MULTITARGET-MULTISENSOR<br>TRACKING: PRINCIPLES AND TECHNIQUES, at double the length, is the<br>most<br>comprehensive state of the art compilation of practical<br>algorithms for the estimation of the states of<br>targets in surveillance systems operating in a<br>multitarget environment using data fusion.<br>This problem<br>is characterized by measurement origin uncertainty,<br>typical for low observables.<br>The tools for design of algorithms for the association of<br>measurements and tracking are presented. Explicit<br>consideration is given for measurements<br>obtained from different sensors under realistic<br>assumptions --- lack of synchronicity and<br>different detection and accuracy characteristics. Several<br>real-data examples are given to illustrate<br>the techniques discussed.<br>The modeling accounts for target maneuvers, non-unity detection probability,<br>false alarms, interference from other targets and the finite<br>resolution capability of sensors. The problems of track initiation,<br>maintenance and multisensor data fusion are considered. The<br>optimization of certain signal processing parameters based on<br>tracking performance is also discussed. The latest results on measurement extraction for unresolved targets, sensor management and data fusion are included.<br>Many of these techniques have applications to state estimation when using<br>multiple sensors in control systems, autonomous vehicle navigation, robotics and wireless communication.<br>An extensive index is provided with all the indexed terms highlighted in the text for the convenience of the reader.