- We will send in 10–14 business days.
/images/books/11268577/9781580536318.jpg)
- Author: Branko Ristic
- Publisher: Artech House Publishers
- ISBN-10: 158053631X
- ISBN-13: 9781580536318
- Format: 16.2 x 23.5 x 2.3 cm, hardcover
- Language: English
- SAVE -10% with code: EXTRA
Reviews
Description
For most tracking applications the Kalman filter is reliable and efficient, but it is limited to a relatively restricted class of linear Gaussian problems. To solve problems beyond this restricted class, particle filters are proving to be dependable methods for stochastic dynamic estimation. This cutting-edge book introduces the latest advances in particle filter theory, discusses their relevance to defence surveillance systems, and examines defence-related applications of particle filters to nonlinear and non-Gaussian problems. nonlinear filter designs and more precisely predict the performance of these designs. You can also apply particle filters to tracking a ballistic object, detection and tracking of stealthy targets, tracking through the blind Doppler zone, bi-static radar tracking, passive ranging (bearings-only tracking) of manoeuvering targets, range-only tracking, terrain-aided tracking of ground vehicles, and group and extended object tracking.
EXTRA 10 % discount with code: EXTRA
The promotion ends in 21d.01:53:45
The discount code is valid when purchasing from 10 €. Discounts do not stack.
- Author: Branko Ristic
- Publisher: Artech House Publishers
- ISBN-10: 158053631X
- ISBN-13: 9781580536318
- Format: 16.2 x 23.5 x 2.3 cm, hardcover
- Language: English English
For most tracking applications the Kalman filter is reliable and efficient, but it is limited to a relatively restricted class of linear Gaussian problems. To solve problems beyond this restricted class, particle filters are proving to be dependable methods for stochastic dynamic estimation. This cutting-edge book introduces the latest advances in particle filter theory, discusses their relevance to defence surveillance systems, and examines defence-related applications of particle filters to nonlinear and non-Gaussian problems. nonlinear filter designs and more precisely predict the performance of these designs. You can also apply particle filters to tracking a ballistic object, detection and tracking of stealthy targets, tracking through the blind Doppler zone, bi-static radar tracking, passive ranging (bearings-only tracking) of manoeuvering targets, range-only tracking, terrain-aided tracking of ground vehicles, and group and extended object tracking.
Reviews