基于LSTM场景分类的行人自适应低功耗定位方案  

Adaptive Low-power Localization Scheme for Pedestrians Based on LSTM Scene Classification

作　　者：余晴 江金光[1,2,3] 谢东朋 刘江华 YU Qing;JIANG Jinguang;XIE Dongpeng;LIU Jianghua(GNSS Research Center,Wuhan 430072,China;Hubei Luojia Laboratory,Wuhan 430072,China;School of Microelectronics,Wuhan University,Wuhan 430072,China;School of Electronics and Information Engineering,Hubei University of Science and Technology,Xianning 437100,China)

机构地区：[1]武汉大学卫星导航定位技术研究中心,湖北武汉430072 [2]湖北珞珈实验室,湖北武汉430072 [3]武汉大学微电子学院,湖北武汉430072 [4]湖北科技学院电子与信息工程学院,湖北咸宁437100

出　　处：《计算机与现代化》2025年第2期44-51,共8页Computer and Modernization

基　　金：湖北科技学院博士科研启动基金资助项目(BK201801)。

摘　　要：针对基于GNSS/INS的足绑式行人定位系统,提出一种基于场景分类的低功耗定位方案,以解决室外复杂环境下的行人定位精度差与系统功耗高的问题。该方案采集GNSS和温湿度传感器信息,使用长短期记忆网络(Long Short-Term Memory,LSTM)对典型的几种室外场景进行分类并针对不同场景调整微控制单元的时钟频率。此外,该方案提出一种基于改进的Sage-Husa方法来减小GNSS异常值对定位结果的影响。实验结果表明本文方案的场景分类准确率达到了97.64%,系统功耗仅有193.074 mW,相比传统的零速更新(Zero Velocity Update,ZUPT)、GNSS、GNSS/INS组合与Sage-Husa方法,本文方案均方根定位误差降低了83.15%、42.88%、21.91%和11.49%。因此,本文方案能够在系统低功耗条件下改善室外行人的定位精度。To address the challenges of pedestrian localization accuracy and high power consumption in outdoor complex environ-ments,this paper proposes a low-power localization scheme based on scene classification for foot-mounted pedestrian navigation systems using GNSS/INS technology.This scheme collects GNSS,temperature and humidity sensor data,uses LSTM to classify typical outdoor scenes and adjusts the clock frequency of the MCU according to different scenes.Additionally,the scheme pro-poses an improved Sage-Husa method to mitigate the impact of GNSS outliers on localization results.The experimental results demonstrate that this solution achieves a scene classification accuracy of 97.64%with a system power consumption of only 193.074 mW.Compared with traditional ZUPT,GNSS,GNSS/INS integration and Sage-Husa methods,the proposed scheme reduces the root mean square localization error by 83.15%,42.88%,21.91%and 11.49%respectively.Therefore,this scheme can improve pedestrian localization accuracy in outdoor environments with low system power consumption.

关 键 词：行人定位 低功耗 LSTM 场景分类 Sage-Husa算法 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]