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A unique guide to the state of the art of tracking, classification, and sensor managementThis book addresses the tremendous progress made over the last few decades in algorithm development and mathematical analysis for filtering, multitarget multisensor tracking, sensor management and control, and target classification. It provides for the first time an integrated treatment of these advanced topics, complete with careful mathematical formulation, clear description of the theory, and realworld applications.Written by experts in the field, Integrated Tracking, Classification, and Sensor Management provides readers with easy access to key Bayesian modeling and filtering methods, multitarget tracking approaches, target classification procedures, and large scale sensor management problemsolving techniques. Features include: An accessible coverage of random finite set based multitarget filtering algorithms such as the Probability Hypothesis Density filters and multiBernoulli filters with focus on problem solving A succinct overview of the trackoriented MHT that comprehensively collates all significant developments in filtering and tracking A stateoftheart algorithm for hybrid Bayesian network (BN) inference that is efficient and scalable for complex classification models New structural results in stochastic sensor scheduling and algorithms for dynamic sensor scheduling and management Coverage of the posterior CramerRao lower bound (PCRLB) for target tracking and sensor management Insight into cuttingedge military and civilian applications, including intelligence, surveillance, and reconnaissance (ISR)With its emphasis on the latest research results, Integrated Tracking, Classification, and Sensor Management is an invaluable guide for researchers and practitioners in statistical signal processing, radar systems, operations research, and control theory.
⚠️ WARNING (California Proposition 65):
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birth defects, or other reproductive harm.
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