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COLLABORATIVE TRACKING VIA PARTICLE FILTER IN WIRELESS SENSOR NETWORKS 被引量:2

COLLABORATIVE TRACKING VIA PARTICLE FILTER IN WIRELESS SENSOR NETWORKS
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摘要 Target tracking is one of the main applications of wireless sensor networks. Optimized computation and energy dissipation are critical requirements to save the limited resource of the sensor nodes. A framework and analysis for collaborative tracking via particle filter are presented in this paper. Collaborative tracking is implemented through sensor selection, and results of tracking are propagated among sensor nodes. In order to save communication resources, a new Gaussian sum particle filter, called Gaussian sum quasi particle filter, to perform the target tracking is presented, in which only mean and covariance of mixands need to be communicated. Based on the Gaussian sum quasi particle filter, a sensor selection criterion is proposed, which is computationally much simpler than other sensor selection criterions. Simulation results show that the proposed method works well for target tracking. Target tracking is one of the main applications of wireless sensor networks. Optimized computation and energy dissipation are critical requirements to save the limited resource of the sensor nodes. A framework and analysis for collaborative tracking via particle filter are presented in this paper Collaborative tracking is implemented through sensor selection, and results of tracking are propagated among sensor nodes. In order to save communication resources, a new Gaussian sum particle filter, called Gaussian sum quasi particle filter, to perform the target tracking is presented, in which only mean and covariance of mixands need to be communicated. Based on the Gaussian sum quasi particle filter, a sensor selection criterion is proposed, which is computationally much simpler than other sensor selection criterions. Simulation results show that the proposed method works well for target tracking.
出处 《Journal of Electronics(China)》 2008年第3期311-318,共8页 电子科学学刊(英文版)
基金 Supported by the National Natural Science Foundation of China (No. 60372107) Ph.D. Innovation Program of Ji-angsu Province (No. 200670) Major Science Foundation of Jiangsu Province (BK2007729) Major Science Foundation of Jiangsu Universities (06KJ510001)
关键词 Collaborative tracking Wireless sensor network Sensor selection Particle filter 滤波器 无线传感器 最优化设计 人工智能系统
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参考文献11

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二级参考文献25

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