Optimal Estimation and Information Fusion: Theory and Algorithms
Optimal Estimation and Information Fusion: Theory and Algorithms
Theory and Algorithms
Lei, Ming
Springer Nature Switzerland AG
04/2025
295
Dura
9789819631728
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Overview of Stochastic Systems and Basic Concepts of Estimation.- Linear Estimation of Static Systems.- Linear Dynamic Systems with Random Inputs.- State Estimation for Discrete Time Linear Systems.- Extension of State Estimation for Discrete Time Linear Systems.- State Estimation for Discrete Time Nonlinear Systems.- Extended Kalman Filtering Unscented Transform Kalman Filtering.- Particle Filtering.- Theory and Methods of Data Association.- Maneuvering Target Tracking Theory and Methods.- Information Fusion Concepts, Models, and Structures.- Information Fusion Methods.- Application Examples: Algorithms, Simulation, and Analysis.
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Stochastic Estimation;Optimized Filtering;Multi-sensor Information Fusion;Maneuvering Target Tracking;Linear/Non-linear System-based Optimal Data Processing
Overview of Stochastic Systems and Basic Concepts of Estimation.- Linear Estimation of Static Systems.- Linear Dynamic Systems with Random Inputs.- State Estimation for Discrete Time Linear Systems.- Extension of State Estimation for Discrete Time Linear Systems.- State Estimation for Discrete Time Nonlinear Systems.- Extended Kalman Filtering Unscented Transform Kalman Filtering.- Particle Filtering.- Theory and Methods of Data Association.- Maneuvering Target Tracking Theory and Methods.- Information Fusion Concepts, Models, and Structures.- Information Fusion Methods.- Application Examples: Algorithms, Simulation, and Analysis.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.