传感器网络中信息融合的几个基本问题

Some Basic Problems in Information Fusion of Sensor Networks

  • 摘要: 系统地阐述了传感器网络环境中几个基本而又重要的信息融合问题的最近进展,包括:最一般条件下全局最优的多传感器分布式统计判决;传感器观测数据或局部估计的最优维数压缩;一般条件下最优线性无偏估计融合公式及其有效算法;传感器观测噪声相关情形下动态系统的卡尔曼滤波融合;容错条件下的区间估计融合.这些结果对传感器网络的设计与应用具有重要意义.

     

    Abstract: Latest progresses on some fundamental and important problems about information fusion in sensor networks are presented,including the multisensor distributed decision in the most general case in the sense of globally optimal fusion;the optimal dimension compression of the sensor observations or local estimates;the best linear unbiased estimation fusion formula and the efficient iterative algorithm;the distributed Kalman filtering fusion for the(multisensor) dynamic systems with cross-correlated sensor noises;and the fault-tolerant interval estimation fusion.These results are significant to the design and application of sensor networks.

     

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