1. Introduction -- 2. Wireless sensor networks -- 3. Distributed sensor fusion -- 4. Distributed Kalman filtering -- 5. Expectation maximization -- 6. Wireless estimation methods -- 7. Multi-sensor fault estimation -- 8. Multi-sensor data fusion -- 9. Approximate distributed estimation -- 10. Estimation via information matrix -- 11. Filtering in sensor networks

Wireless sensor networks (WSNs) produce much data that needs to be processed, delivered, and assessed according to application objectives. Information fusion arises as a response to data gathered by sensor nodes and benefits from their processing capability. This book is about the current state of information fusion. It presents the known methods, algorithms, architectures, and models of information fusion, and discusses their applicability in the context of WSNs. Consideration is given to the range of topics treated in the current literature and presenting results of typical case studies