Statistical multisource-multitarget information fusion
Author(s)
Bibliographic Information
Statistical multisource-multitarget information fusion
（Artech House information warfare library）
Artech House, c2007
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Note
Includes bibliographical references (p. 821-836) and index
Description and Table of Contents
Description
Information fusion is the process of gathering, filtering, correlating and integrating relevant information from various sources into one representational format. It is used by signal processing engineers and information operations specialists to help them make decisions involving tasks like sensor management, tracking, and system control. This comprehensive resource provides practitioners with an in-depth understanding of finite-set statistics (FISST) - a recently developed method that has been gaining much attention among professionals because it unifies information fusion, utilizing statistics that most engineers learn as undergraduates. The book helps professionals use FISST to create efficient information fusion systems that can be implemented to address real-world challenges in the field.
Table of Contents
Unified Single-Target Multisource Integration - Conventional Single-Sensor, Single-Target Tracking. General Data Modeling. Unambiguously Generated Ambiguous (UGA) Measurements. Ambiguously Generated Ambiguous (AGA) Measurements. Ambiguously Generated Unambiguous (AGU) Measurements. Finite-Set Measurements. Unified Multitarget Multisource Integration - Conventional Multisource-Multitarget Information Fusion. Multitarget Differential and Integral Calculus. Multitarget Markov Densities. The Multisource-Multitarget Bayes Filter. Approximate Multitarget Filtering - Multitarget Particle Approximation. Multitarget-Moment Approximation.
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