JOURNAL ARTICLE

Unscented Particle Filter Algorithm for Ballistic Target Tracking

Jun Wei ZhaoMing Jun ZhangYong YanYong Peng Yan

Year: 2011 Journal:   Applied Mechanics and Materials Vol: 130-134 Pages: 369-372   Publisher: Trans Tech Publications

Abstract

At present, the ballistic Target tracking has a higher demand in convergence rate and tracking precision of filter algorithm. In the paper, a filter algorithm was improved based on particle filter. The algorithm was carried out from the aspects such as particle degradation and particle diversity lack. A novel ballistic coefficient parameter model was built, and was expanded to the state vector for filtering. Finally, the improved algorithm was simulated by MATLAB software. The simulation results show that the algorithm can obtain better convergence speed and tracking precision.

Keywords:
Tracking (education) Particle filter Convergence (economics) State vector Algorithm MATLAB Rate of convergence Computer science Filter (signal processing) Control theory (sociology) Auxiliary particle filter Extended Kalman filter Kalman filter Artificial intelligence Ensemble Kalman filter Computer vision Physics

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Topics

Target Tracking and Data Fusion in Sensor Networks
Physical Sciences →  Computer Science →  Artificial Intelligence
Inertial Sensor and Navigation
Physical Sciences →  Engineering →  Aerospace Engineering
Robotics and Sensor-Based Localization
Physical Sciences →  Engineering →  Aerospace Engineering
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