一种城市环境中移动传感器网络的RF信号估值算法  

RF Signal Estimation Algorithm for Mobile Sensor Networks in Urban Environment

作　　者：李振杰[1] 尹立新[1] 张绚[1] 米立红 

机构地区：[1]山东大学信息科学与工程学院,济南250199

出　　处：《计算机科学》2014年第1期183-186,共4页Computer Science

摘　　要：在城市环境中移动传感器网络节点之间的RF信号受反射、衍射以及多径衰落等多种传播方式的影响很大,导致基于节点RF接收信号的定位、跟踪等移动传感器网络应用很难实用化。针对该问题提出一种对城市复杂环境具有鲁棒性的基于阈值的RF信号估值算法。通过分析可知,该算法复杂度低,能够实现复杂环境下RF信号的突变检测,并充分利用Kalman算法的优势进行最优的RF信号估值。最后仿真实验证明,该算法比传统的Kalman算法和滑动窗口算法具有更优的估计性能。RF signals between the mobile sensor networks nodes in an urban environment are greatly impacted by mul- tipath fading and reflection diffraction mode of transmission, which makes practical applications such as mobile sensor networks positioning, tracking so difficult. In this paper, a robust estimation algorithm based on the threshold of the RF signal was presented which fits a complex urban environment. The algorithm low complexity possesses, and can achieve mutation detection of the RF signal in the complex environment, and fully utilize the advantages of the Kalman algo- rithm to optimal RF signal valuation. Finally, the simulation also proves the better performance of the algorithm than traditional Kalman and the sliding window algorithm.

关 键 词：移动传感器网络 卡尔曼滤波 滑动窗口算法 RF信号 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]