"Kalman Filter: Variants Applications and Optimizations" ed. by Asadullah Khalid, Arif Sarwat, Hugo Riggs

This volume is a comprehensive exploration of Kalman filters’ diverse applications and refined optimizations across various domains. It meticulously examines their role in microgrid management, offering adaptive estimation techniques for effective control strategies. The book then delves into distribution system state estimation, showcasing an innovative stochastic programming model using extended Kalman filters for reliable monitoring and control.

In the realm of financial modeling, readers gain insights into how Kalman filters enhance trading strategies like pairs trading and partial co-integration, bridging finance and analytics. The book discusses Kalman filter optimization, addressing challenges in object tracking and error reduction with techniques like dynamic stochastic approximation algorithms and M-robust estimates. With practical examples and interdisciplinary approaches, this book serves as a valuable resource for researchers, practitioners, and students looking to harness Kalman filter techniques for enhanced efficiency and accuracy across diverse fields.

Contents
1. Kalman Filter-Based Harmonic Distortion Mitigation Technique for Microgrid Applications
2. An Application of Particle Filter for Parameter Estimation and Prediction in Geotechnical Engineering
3. Data Sensor Fusion for Surveillance Applications: Evaluation of Extended Kalman Filter vs. Unscented Kalman Filter
4. Optimizing μ-PMU Placement for Estimating Asymmetrical Distribution Network States – Introducing a Novel Stochastic Two-Stage Approach
5. Approximate Kalman Filter Using M-Robust Estimate Dynamic Stochastic Approximation with Parallel Adaptation of Unknown Noise Statistics by Huber’s M-Robust Parameter Estimator
6. Kalman Filtering Applied to Investment Portfolio Management
7. Insights from Kalman Filtering with Correlated Noises Recursive Least-Square Algorithm for State and Parameter Estimation
8. Application of the Kalman Filter in Monitoring, Diagnosis, and Fault Parrying Problems for Observable Dynamical Systems


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