Application of Optimal Smoothing to Beamforming Tracking Data based on a Singer Model
This paper presents an application of optimal smoothing algorithm for a model rocket trajectory based on beamforming data using microphone array.The model rocket is designed to move along a one degree of freedom linear wire guide for measuring the sound waves transmitted from a fast moving compact source in outdoor environment.The peak value of the beamforming data is used to estimate the model rocket trajectory with a velocity of 50 m/s.Then,Kalman filter and optimal smoothing algorithm are adopted to improve accuracy of trajectory estimation.In addition,a Singer acceleration model considered for realistic process and measurement noise covariance are derived from experimental measurement data.The Kalman filter results show better tracking performance than the basic beamforming technique,and the estimation results of the optimal smoother outperform the Kalman filter in terms of trajectory accuracy.
Kalman filter (KF) Backward filter Optimal smoothing scheme Beamforming Singer model
Junho Jeong Gyeonghun Kim Yeong-Ju Go Jaehyung Lee Seungkeun Kim Jong-Soo Choi
Unmanned Systems Group,Department of Aerospace Engineering,Chungnam National University,Daejeon,305- Aerodynamics and Aeroacoustics Laboratory,Department of Aerospace Engineering,Chungnam National Univ
国际会议
2014 Asia-Pacific International Symposium on Aerospace Technology(2014亚太航空航天技术学术会议)
上海
英文
1-8
2014-09-24（万方平台首次上网日期，不代表论文的发表时间）