A Study on Maneuvering Obstacle Motion State Estimation for Intelligent Vehicle Using Adaptive Kalman Filter Based on Current Statistical Model
Joint Authors
Han, Bao
Xin, Guan
Xin, Jia
Fan, Liu
Source
Mathematical Problems in Engineering
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-08-31
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
The obstacle motion state estimation is an essential task in intelligent vehicle.
The ASCL group has developed such a system that uses a radar and GPS/INS.
When running on the road, the acceleration of the vehicle is always changing, so it is hard for constant velocity (CV) model and constant acceleration (CA) model to describe the motion state of the vehicle.
This paper introduced Current Statistical (CS) model from military field, which uses the modified Rayleigh distribution to describe acceleration.
The adaptive Kalman filter based on CS model was used to estimate the motion state of the target.
We conducted simulation experiments and real vehicle tests, and the results showed that the estimation of position, velocity, and acceleration can be precise.
American Psychological Association (APA)
Han, Bao& Xin, Guan& Xin, Jia& Fan, Liu. 2015. A Study on Maneuvering Obstacle Motion State Estimation for Intelligent Vehicle Using Adaptive Kalman Filter Based on Current Statistical Model. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-14.
https://search.emarefa.net/detail/BIM-1074026
Modern Language Association (MLA)
Han, Bao…[et al.]. A Study on Maneuvering Obstacle Motion State Estimation for Intelligent Vehicle Using Adaptive Kalman Filter Based on Current Statistical Model. Mathematical Problems in Engineering No. 2015 (2015), pp.1-14.
https://search.emarefa.net/detail/BIM-1074026
American Medical Association (AMA)
Han, Bao& Xin, Guan& Xin, Jia& Fan, Liu. A Study on Maneuvering Obstacle Motion State Estimation for Intelligent Vehicle Using Adaptive Kalman Filter Based on Current Statistical Model. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-14.
https://search.emarefa.net/detail/BIM-1074026
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1074026