Research on indoor localization algorithm of rescue scene based on LSTM and IFHDE
ZHANG Mingyue
PENG Cheng
BU Xiangli
LI Guan
YU Xingchen
WANG Yang
Abstract：To address the critical challenge of precise first responder localization in indoor emergency rescue scenarios,this study proposes,an indoor positioning scheme was designed by using the Long Short-Term Mem-ory(LSTM)model and an innovatively improved fusion heuristic drift elimination algorithm(IFHDE)to assist the inertial navigation system.A zero-velocity detection algorithm based on LSTM was developed.Through the learning ability of the model,the threshold was adaptively adjusted to improve the accuracy of zero-velocity de-tection and eliminate the cumulative positioning error caused by the fixed threshold.The IFHDE algorithm was innovatively improved.By distinguishing different motion states and setting correction conditions,the heading angle error can be corrected specifically,thereby improving the positioning accuracy.By integrating the LSTM algorithm and the IFHDE algorithm in the inertial navigation system framework and performing measurement updates,the precise restoration of the personnel's calculated trajectory was achieved.Experimental results show that compared with the zero-velocity detection algorithm with a fixed threshold,the LSTM zero-velocity detec-tion algorithm significantly reduced the positioning error in mixed motion modes,with a reduction of 24.2％to 46.9％.After integrating the IFHDE algorithm,the positioning error further decreases by 9.2％to 14.4％,and the error ratio does not exceed 0.7％of the total route,which can meet the demand for precise indoor positio-ning of rescue personnel and improve the accuracy of trajectory restoration.
Keywords：indoor positioningzero-speed detection algorithmcourse correction algorithminertial naviga-tion
Publication Date：2025-06-30
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：11( 67-76,87 )