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http://dx.doi.org/10.5139/JKSAS.2015.43.12.1062

Estimation of Moving Target Trajectory using Optimal Smoothing Filter based on Beamforming Data  

Jeong, Junho (Department of Aerospace Engineering, Chungnam National University)
Kim, Gyeonghun (Department of Aerospace Engineering, Chungnam National University)
Go, Yeong-Ju (Department of Aerospace Engineering, Chungnam National University)
Lee, Jaehyung (Department of Aerospace Engineering, Chungnam National University)
Kim, Seungkeun (Department of Aerospace Engineering, Chungnam National University)
Choi, Jong-Soo (Department of Aerospace Engineering, Chungnam National University)
Ha, Jae-Hyoun (Agency for Defence Development)
Publication Information
Journal of the Korean Society for Aeronautical & Space Sciences / v.43, no.12, 2015 , pp. 1062-1070 More about this Journal
Abstract
This paper presents an application of an optimal smoothing filter for moving target tracking problem based on measured noise source. In order to measure distance and velocity for the moving target, a beamforming method is applied to use the noise source by using microphone array. Also a Kalman filter and an optimal smoothing algorithm are adopted to improve accuracy of trajectory estimation by using a Singer target model. The simulation is conducted with a missile dynamics to verify performance of the optimal smoothing filter, and a model rocket is used for experiment environment to compare the trajectory estimation results between the beamforming, the Kalman filter, and the smoother. The Kalman filter results show better tracking performance than the beamforming technique, and the estimation results of the optimal smoother outperform the Kalman filter in terms of trajectory accuracy in the experiment results.
Keywords
Trajectory Estimation; Singer Target Model; Kalman Filter; Optimal Smoothing Filter; Beamforming Technique;
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Times Cited By KSCI : 1  (Citation Analysis)
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