Interacting Multiple Sensor Filter for Sensor Networks

摘要：

Due to limited sensing range for sensors,moving object tracking has to be realized by relaying from one sensor to the other in sensor networks.And so the tracking procedure can be modeled as a Markov chain system.By reconstructing the innovation equation,the RKF algorithm is designed in the light of Bayesian theory.On this basis,the IMSF algorithm is proposed further by mixing the initial state and covariance at one cycle,which has a bit better tracking performance than the RKF algorithm,but at the cost of the computational complexity.Finally,simulation results show the effectiveness of the proposed IMSF algorithm.

关键词： wireless sensor networks object tracking Markov chain Bayesian theory

作者: Zhigang Liu Jinkuan Wang Yanbo Xue

作者单位: Insitute of Engineering Optimization and Smart Antenna Northeastern University Qinhuangdao 066004,China

会议类型: 国际会议

会议名称: 2010 4th International Conference on Intelligent Information Techonlogy Application(第四届智能信息技术应用国际学术研讨会 IITA 2010)

会议地点: 秦皇岛

会议语种:英文

页码: 360-363

在线出版日期: 2010-11-05（万方平台首次上网日期，不代表论文的发表时间）