Mobile phone location method for buried personnel after earthquake based on particle swarm optimization BP neural network technology
In recent years,global earthquake disasters have occurred frequently,making the rapid and accurate localization of buried personnel a focal and challenging aspect of post-earthquake search and rescue operations.This paper proposes a novel method for locating buried personnel based on particle swarm-optimized BP neural network technology,which indirectly determines the position of buried individuals through the localization of their buried mobile phones.By capturing the received signal strength data emitted by buried mobile phones using WiFi probes,the data is processed using Gaussian-Kalman hybrid filtering.Utilizing the distance to buried personnel calculated by the particle swarm-optimized BP neural network,a multi-decay model fusion approach is established by combining logarithmic attenuation and polynomial attenuation models to create a more precise correction model for the buried distance.The buried mobile phone location is then determined using the weighted six-point centroid localization algorithm.Experimental results demonstrate that the multi-decay model fusion-based buried distance correction model achieves a positioning error of 0.579 meters,yielding an improvement of 43.5%,30.9%,and 12.7%in localization accuracy compared to single-channel attenuation models and neural networks,respectively.
万方数据
维普
