| Edition |
1st ed. 2023. |
| Descript. |
VI, 118 pages 58 illustrations, 53 illustrations in color. online resource. |
| Phys Desc |
text file PDF rda |
| Series |
Studies in Big Data,
2197-6511 ; 126
|
|
Studies in Big Data, 2197-6511 ; 126
|
| Contents |
Introduction -- Bayesian Single Target Tracking -- Bayesian Particle Filtering -- Simple Multiple Target Tracking -- Intensity Filters. |
| Summary |
This book provides a quick but insightful introduction to Bayesian tracking and particle filtering for a person who has some background in probability and statistics and wishes to learn the basics of single-target tracking. It also introduces the reader to multiple target tracking by presenting useful approximate methods that are easy to implement compared to full-blown multiple target trackers. The book presents the basic concepts of Bayesian inference and demonstrates the power of the Bayesian method through numerous applications of particle filters to tracking and smoothing problems. It emphasizes target motion models that incorporate knowledge about the target's behavior in a natural fashion rather than assumptions made for mathematical convenience. The background provided by this book allows a person to quickly become a productive member of a project team using Bayesian filtering and to develop new methods and techniques for problems the team may face. |
| Sys Details |
eBook access requires you to log in as a Federation University Australia library user |
| Notes |
Springer Nature eBook |
| Subject |
Engineering -- Data processing.
|
|
Statistics.
|
|
Big data.
|
| Other Author |
Streit, Roy L. author.
|
|
Anderson, Stephen L. author.
|
|
SpringerLink (Online service)
|
| ISBN |
9783031322426 |
| ISBN/ISSN |
10.1007/978-3-031-32242-6 doi |
|
