Filtering Techniques for Stochastic Hybrid Systems

ISBN-13: 9786206787136 / Angielski / Miękka / 104 str.

Robinson Paul; Vishvjit Thakar; Hetal Patel

Opis

Stochastic Hybrid Systems (SHS) blend continuous and discrete dynamics, relevant to communication, vehicle control, finance, and tracking. Our research focuses on state estimation for linear and non-linear SHS, emphasizing solutions for missing measurements. Historically, SHS state estimation leaned towards deterministic models, overlooking issues like measurement loss. Researchers now explore probabilistic and guard condition-based state transitions. For example, in flying objects, SHS captures discrete flight modes and continuous dynamics. We introduce the Data Loss Detection Kalman Filter for linear SHS, bolstered by Chi-square statistics for measurement loss. In non-linear SHS, the Reallocation Resample Particle Filter and Systematic Resample Particle Filter excel in handling missing measurements. Our research illuminates state estimation intricacies, offering practical solutions.

O autorze

Dr. Robinson Paul is a dedicated Electronics Engineering Faculty with 15+ years of experience. Passionate educator in Signal Processing, VLSI - RTL Design, and Machine Learning. Committed to student success with 1000+ guided to excellence. A prolific researcher with numerous publications, adept at securing funding from prestigious organizations.