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研究定位无线传输信号受干扰较大以及定位精度达不到要求等问题,应该建立起更准确的定位机制,以减少环境等因素的干扰。针对基于RSSI定位算法中的问题,提出了一种基于改进的模拟退火法的定位算法。首先利用贝叶斯算法进行滤波处理,然后应用改进的退火算法表示节点的通信范围和移动范围,根据移动点每时刻最大移动范围和移动点的通信范围形成解区域,然后随机采集样节点进行优化处理。实验结果表明,改进的模拟退火算法能获得较好的定位精度,优于传统的极大似然估计等算法,有效实现了移动点在复杂空间的定位且无须额外增加硬件,减少了成本。
Research and localization of wireless transmission signal interference and positioning accuracy of less than the requirements and other issues, should establish a more accurate positioning mechanism to reduce environmental interference and other factors. Aimed at the problems based on RSSI localization algorithm, a localization algorithm based on improved simulated annealing is proposed. Firstly, the Bayesian algorithm is used to filter the data. Then, the improved annealing algorithm is used to represent the communication range and the moving range of the node. The solution area is formed according to the maximum moving range of the moving point and the communication range of the moving point. deal with. The experimental results show that the improved simulated annealing algorithm can get better positioning accuracy than the traditional maximum likelihood estimation algorithm, which can effectively locate the moving point in the complex space without additional hardware and reduce the cost.