中文摘要：

这份报纸集中于传感器为目标在无线传感器网络(WSN ) 追踪安排和信息量子化问题。减少 WSN 的精力消费，选择下一个 tasking 传感器并且使量子化必要、有效 WSN 数据。在存在工作，传感器安排目标包括最大化追踪精确性并且最小化精力费用。在这份报纸，传感器安排和量子化技术的集成被用来平衡在追踪精确性和精力消费之间的折衷。建议计划的主要特征包括为扩大 Kalman 过滤器(EKF ) 安排计划，和一个压缩使量子化的算法的一个新奇过滤过程。使算法更有效，建议站台采用减少的一个方法到还原剂的采样间隔的阀值所有操作的实行时间。为测试安排的新奇传感器和量子化计划的一个真实追踪系统平台被开发。精力消费和在不同计划下面的站台的追踪的精确性最后被比较。

英文摘要：

This paper focuses on sensor scheduling and information quantization issues for target tracking in wireless sensor networks （WSNs）. To reduce the energy consumption of WSNs, it is essential and effective to select the next tasking sensor and quantize the WSNs data. In existing works, sensor scheduling＇ goals include maximizing tracking accuracy and minimizing energy cost. In this paper, the integration of sensor scheduling and quantization technology is used to balance the tradeoff between tracking accuracy and energy consumption. The main characteristic of the proposed schemes includes a novel filtering process of scheduling scheme, and a compressed quantized algorithm for extended Kalman filter （EKF）. To make the algorithms more efficient, the proposed platform employs a method of decreasing the threshold of sampling intervals to reduce the execution time of all operations. A real tracking system platform for testing the novel sensor scheduling and the quantization scheme is developed. Energy consumption and tracking accuracy of the platform under different schemes are compared finally.