一种基于自适应RSSI测距模型的无线传感器网络定位方法∗

摘要

为了提高无线传感器网络的节点定位精度和环境适应性，研究了环境因素及信道噪声对无线信号传输特性的影响，对测量误差进行修正，得到精确的环境自适应RSSI测距模型，在此基础上结合距离加权修正的改进WELSE算法，得到了一种新的混合定位算法。在ZigBee平台CC2430上的测试结果表明本算法在未知环境中不需要预整定模型参数，在定位精度上，本文算法相比WELSE提高了49%，比WCLA提高了36%，可见其具备优秀的环境适应性和较高的定位精度。%In order to improve the adaptability and precision of wireless positioning technology of the nodes in WSN, we first analyzed the effects of environmental factors and channel noises on the characteristics of signal transmission and then get the accurate RSSI distance measurement model of environment adaptive. On the base of the distance model and improved WELSE alghorithm with distance weighted correction,we get a new hybrid positioning algorithm of WSN. The tests on the CC2430 platform show that in unknown environments there is no need to calibrate algo-rithm parameters in advance and the accuracy of positioning is increased by 49% compared to WELSE and by 36%compared to WCLA. The results prove that,the algorithm is well environment adaptive with high precision.