Current Statistical Model Based on Maximum Entropy Fuzzy Clustering

摘要：

In the view of the unfitness to the actual maneuver of targets that a fixed maneuvering frequency used in the current statistical model. Firstly, predicted measurements of special maneuvering frequency are clustered with the aid of maximum entropy fuzzy clustering. Then, the estimated means and covariance of the state are mixed by utilizing the fuzzy membership degree of the predicted measurements. Unscented kalman filter is employed to solving the nonlinearity of the measurement equations. Simulation results show that the proposed method has higher accuracy than some existing methods based on the current statistical model in the estimation.

关键词： Hybrid States maximum entropy fuzzy clustering current statistical maneuvering target tracking UKF

作者: LI Dong-wei XIE Wei-xin HUANG Jian-jun HUANG Jing-xiong JIN Kai-chun

作者单位: School of Electronic Engineering, Xidian Univ., Xi’an 710071, China Air Defence Forces Command Acade ATR Lab, Shenzhen University, Shenzhen, 518060 ATR Lab, Shenzhen University, Shenzhen, 518060 Air Defence Forces Command Academy, Zhengzhou, 450052 Air Defence Forces Command Academy, Zhengzhou, 450052

会议类型: 国际会议

会议名称: 2010 IEEE 10th International Conference on Signal Processing(第十届信号处理国际会议 ICSP 2010)

会议地点: 北京

会议语种:英文

页码: 1414-1417

在线出版日期: 2010-08-24（万方平台首次上网日期，不代表论文的发表时间）