Publications (2)0 Total impact

  • Xun-Xue Cui · Zhen Fang · Ji-chun Zhang
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    ABSTRACT: One of the important applications in sensor networks is target tracking. Usually it is difficult to balance the optimization goals of the tracking precision, computation cost and network communication traffic for target localization in a distributed manner. The binary sensing model is analyzed where individual sensor only returns the information regarding target's presence or absence within its sensing range. A cooperative distributed algorithm based on the triplet circle intersection principle is proposed for maneuvering target tracking by this kind of sensor network. The central point of a common intersection arc among sensor range circles is considered as the target estimation position through a compact computation manner. By combining data from neighboring sensors, this algorithm enables tracking with a resolution higher than that of the traditional average method. The triplet circle intersection model is applied to decrease the localization cost and communication traffic; therefore it fits low-power sensor networks. Simulation experimentations have been designed to verify the algorithm performance. A good tracking quality can be achieved to optimize comprehensive goals of precision, computation and traffic. Moreover, in the paper the conventional performance evaluation criterions about average error and root mean square error are improved to reflect the intrinsic measurement effectiveness of a target tracking problem in a more excellent way.
    Wireless Sensor Network, 2010. IET-WSN. IET International Conference on; 12/2010
  • Xun-Xue Cui · Ji-chun Zhang · Pu-Cheng Zhou
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    ABSTRACT: Recently target detection is widely regarded as a typical hot spot in research of sensor networks. A fast target detection algorithm is proposed by using the hypothesis testing (HT) method in the paper. The objective is to determine whether a target is present in a sensor network for decision-makers. Due to the nature of sensor networks, it is desirable to have a fast algorithm to accomplish the detection and judgment process with low computation cost on a distributed network end node. In the paper mobile target detection is formulated as a statistical inference problem according to the mathematical statistics theory. Moreover, a data fusion process with several sensors is also designed to optimize the final decision result for detection synthesis. It has the advantage of low computational complexity, good performance of real time, and yields high target detection correctness. Numerical experiments are used to demonstrate the efficiency of the HT detection algorithm, where magnetic sensors are applied to collect the output signal from an undetermined target.
    Seventh International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2010, 10-12 August 2010, Yantai, Shandong, China; 01/2010