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AWCL:Adaptive Weighted Centroid Target Localization Algorithm Based on RSSI in WSN

机译:AWCL:WSN中基于RSSI的自适应加权质心目标定位算法

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Target localization and tracking is the canonical application of Wireless Sensor Networks. Unlike a centralized system, a sensor network is subject to a unique set of resource constraints such as limited on-board battery power and limited network communication bandwidth. So the traditional tracking algorithm can be directly used in WSN. Therefore efficient localization algorithms that consume less energy for computation and less bandwidth for communication are needed. The weighted centroid localization algorithm (WCL) based on RSSI is applied in most of actual systems. Only one uniform path loss exponent obtained through experiments is used to calculate the weights of nodes in general WCL. It is well known that the path loss exponent is the essential reflection of sensing surroundings. The actual sensing scenario can't be revealed in the traditional WCL algorithm, and therefore it is not appropriate that only one exponent is accepted all through the area covered by the sensor nodes. A new algorithm, adaptively weighted centroid localization (AWCL), is proposed in this paper. Firstly a more reasonable path loss exponent is adaptively estimated according to the surroundings where the target nodes situates. Secondly the target position will be calculated by using the weighted centroid method in which exponents estimated in the first stage are adopted. Theoretical analysis are presented to demonstrate the performance of the proposed localization method, the simulation results show that that the proposed algorithm outperforms the general WCL algorithm.
机译:目标定位和跟踪是无线传感器网络的典型应用。与集中式系统不同,传感器网络受到一组独特的资源约束,例如有限的车载电池电量和有限的网络通信带宽。因此传统的跟踪算法可以直接在WSN中使用。因此,需要有效的定位算法,该算法消耗较少的计算能量和较少的通信带宽。基于RSSI的加权质心定位算法(WCL)应用于大多数实际系统中。通过实验获得的统一路径损耗指数仅用于计算一般WCL中节点的权重。众所周知,路径损耗指数是感知周围环境的本质反映。传统的WCL算法无法揭示实际的传感情况,因此在整个传感器节点覆盖的区域中仅接受一个指数是不合适的。提出了一种新的自适应加权质心定位算法。首先,根据目标节点所处的环境自适应地估计出更合理的路径损耗指数。其次,将采用加权质心法计算目标位置,其中采用第一阶段估计的指数。理论分析证明了所提出的定位方法的性能,仿真结果表明所提出的算法优于常规的WCL算法。

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