Sensor and Data Fusion: A Tool for Information Assessment and Decision Making

Klein, a consultant in data and sensor fusion applications, describes the benefits of sensor fusion by considering the characteristics of infrared, microwave, and millimeter-wave sensors. Data fusion algorithms discussed in detail include classical inference, Bayesian inference, Dempster-Shafer evidential theory, artificial neural networks, voting logic as derived from Boolean algebra expressions, and fuzzy logic. The text can be used in courses on multisensor, multitarget data fusion techniques for tracking and identification of potential targets. Annotation © 2004 Book News, Inc., Portland, OR