基于RSSI优化的模型参数实时估计定位算法

摘要

Received signal strength indicator (RSSI) ranging technology is a low-cost distance measurement technique. To reduce the RSSI measurement error because of the influence of environment effectively, and solve the problem of high ranging error which is brought by using the fixed signal propagation model in the traditional algorithms, a localization algorithm of model parameters real-time estimation based on RSSI optimized is put forward. This algorithm processes the all RSSI measured values that the node received by adopting the Gauss model firstly, and determines the minimal region where the location node is placed in according to RSSI values secondly, then environment parameters are estimated by the cooperation of selected beacon nodes, which is placed in the minimal region. The parameters of the signal propagation model is adjusted dynamically according to the actual situation, which makes the ranging precision exacter, thus the positional error is reduced It verifies that the proposed algorithm can provide higher localization accuracy from the simulation results by comparing with the other algorithms.%基于RSSI的测距是一种低成本的距离测量技术.为了有效地降低RSSI因环境影响而产生的测量误差,以及解决传统算法中因使用固定信号传播模型而造成较大测距误差的问题,提出一种RSSI经过优化处理的模型参数实时估计定位算法.该算法运用高斯模型对节点接收到的所有RSSI测量值进行处理,根据RSSI值确定待定位节点所在的最小区域,再通过该区域内选定信标节点间的相互合作估算出当时的环境参数,根据实际情况动态调整传播模型的参数,使测距更准确,从而减少定位误差.将该算法与其它算法进行仿真比较,结果表明了该算法可以有效地提高定位精度.