Study on on-axis tracking algorithm of modified current statistical model
- Resource Type
- Conference
- Authors
- Xiong, Zhenkai; Li, Fanying
- Source
- 2017 IEEE 2nd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC) Advanced Information Technology, Electronic and Automation Control Conference (IAEAC), 2017 IEEE 2nd. :1570-1573 Mar, 2017
- Subject
- Computing and Processing
Robotics and Control Systems
Target tracking
Acceleration
Mathematical model
Computational modeling
Adaptation models
Filtering theory
systems engineering
on-axis tracking
modified current statistical model
nonlinear system
filter
- Language
On-axis tracking is the difficult point and hot point in the tracking field. It is the expression of computer tracking. The target state is unknown and dynamic. The filter algorithm can affect tracking precision. The tracking effect can be enhanced by synthesized the target model and filter algorithm. On-axis tracking study is the point, for the tracking precision demand of current statistical model to the weak and non-maneuvering maneuvering target, the paper propose an adaptive function, the function is used to confim the error covariance of the acceleration and amplify the range. The Unscented Kalman Filter algorithm calculates the target position and velocity. The ability is raise to maneuvering target. The simulation results show the modified current statistical model and Unscented Kalman Filter algorithm improve the precision of tracking and ability.