Tracking and Data Fusion: A Handbook of Algorithms

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