自适应无线传感器网络室内RSSI估计

Estimation of indoor RSSI in adaptive wireless sensor networks

针对接收信号强度指示(RSSI)在无线传感器网络室内应用中,难以随环境变化实现自适应准确估计的问题.首先结合无线传感器节点处理能力较低的特点,对卡尔曼滤波算法进行简化,降低算法复杂度;然后设计出适用于室内环境变化特点的环境自适应算法;最后通过2种算法的融合,提出了自适应室内RSSI估计算法(AIRE).仿真和实验结果均表明,与典型的估计算法相比,AIRE在环境变化时可自适应地实现更快、更准确的RSSI估计.AIRE算法复杂度低,能在室内环境中准确估计RSSI值,并可实现环境变化的自适应估计,满足无线传感器网络在室内应用时对RSSI估计的需求.

RSSI （received signal strength indication） is difficult to estimate accurately when indoor environment changes. On the basis of wireless sensor network nodes with low processing capacity, Kalman filtering algorithm was simplified to reduce the complexity of the algorithm. An adaptive algorithm was used to the changeable indoor environment. Then an adaptive indoor RSSI estimation （AIRE） algorithm based on the two algorithms is proposed. Simulation and experiment results show that when environment changes, AIRE adaptively achieves faster and more accurate RSSI estimation than classic estimation algorithms. AIRE has lower complexity, estimates RSSI accurately in indoor environment, achieves adaptive estimation with the change of environment, and satisfies the requirement of RSSI estimation for indoor wireless sensor network.