The inertial navigation system(INS),which is frequently used in emergency rescue operations and other situations,has the benefits of not relying on infrastructure,high positioning frequency,and strong real-time perfor...The inertial navigation system(INS),which is frequently used in emergency rescue operations and other situations,has the benefits of not relying on infrastructure,high positioning frequency,and strong real-time performance.However,the intricate and unpredictable pedestrian motion patterns lead the INS localization error to significantly diverge with time.This paper aims to enhance the accuracy of zero-velocity interval(ZVI)detection and reduce the heading and altitude drift of foot-mounted INS via deep learning and equation constraint of dual feet.Aiming at the observational noise problem of low-cost inertial sensors,we utilize a denoising autoencoder to automatically eliminate the inherent noise.Aiming at the problem that inaccurate detection of the ZVI detection results in obvious displacement error,we propose a sample-level ZVI detection algorithm based on the U-Net neural network,which effectively solves the problem of mislabeling caused by sliding windows.Aiming at the problem that Zero-Velocity Update(ZUPT)cannot suppress heading and altitude error,we propose a bipedal INS method based on the equation constraint and ellipsoid constraint,which uses foot-to-foot distance as a new observation to correct heading and altitude error.We conduct extensive and well-designed experiments to evaluate the performance of the proposed method.The experimental results indicate that the position error of our proposed method did not exceed 0.83% of the total traveled distance.展开更多
To better improve the emergency communication and location-based services of disaster information reporting network for serious natural response and relieL disaster emergency the national natural disaster reduction ap...To better improve the emergency communication and location-based services of disaster information reporting network for serious natural response and relieL disaster emergency the national natural disaster reduction application platform based on BeiDou navigation satellite system is constructed. The administrative distributed platform is integrated with BeiDou positioning and multiple communication ways so as to achieve main disaster reduction application services, including disaster information acquisition and monitoring, emergency relief for trapped people, on-site emergency relief command service, relief supplies＇ transportation monitoring, and disaster information publishing service. By the platform, serious disaster information reporting time may be reduced to one hour and the emergency decision-making information service for serious natural disasters can be effectively improved, and it will be helpful to provide technical references for the industrial application and promotion of BeiDou inte- grated disaster reduction.展开更多
基金supported in part by National Key Research and Development Program under Grant No.2020YFB1708800China Postdoctoral Science Foundation under Grant No.2021M700385+5 种基金Guang Dong Basic and Applied Basic Research Foundation under Grant No.2021A1515110577Guangdong Key Research and Development Program under Grant No.2020B0101130007Central Guidance on Local Science and Technology Development Fund of Shanxi Province under Grant No.YDZJSX2022B019Fundamental Research Funds for Central Universities under Grant No.FRF-MP-20-37Interdisciplinary Research Project for Young Teachers of USTB(Fundamental Research Funds for the Central Universities)under Grant No.FRF-IDRY-21-005National Natural Science Foundation of China under Grant No.62002026。
文摘The inertial navigation system(INS),which is frequently used in emergency rescue operations and other situations,has the benefits of not relying on infrastructure,high positioning frequency,and strong real-time performance.However,the intricate and unpredictable pedestrian motion patterns lead the INS localization error to significantly diverge with time.This paper aims to enhance the accuracy of zero-velocity interval(ZVI)detection and reduce the heading and altitude drift of foot-mounted INS via deep learning and equation constraint of dual feet.Aiming at the observational noise problem of low-cost inertial sensors,we utilize a denoising autoencoder to automatically eliminate the inherent noise.Aiming at the problem that inaccurate detection of the ZVI detection results in obvious displacement error,we propose a sample-level ZVI detection algorithm based on the U-Net neural network,which effectively solves the problem of mislabeling caused by sliding windows.Aiming at the problem that Zero-Velocity Update(ZUPT)cannot suppress heading and altitude error,we propose a bipedal INS method based on the equation constraint and ellipsoid constraint,which uses foot-to-foot distance as a new observation to correct heading and altitude error.We conduct extensive and well-designed experiments to evaluate the performance of the proposed method.The experimental results indicate that the position error of our proposed method did not exceed 0.83% of the total traveled distance.
基金supported by National Bei Dou Special Project and National Science & Technology planning project of China (Grant No. 2014BAK12B04)
文摘To better improve the emergency communication and location-based services of disaster information reporting network for serious natural response and relieL disaster emergency the national natural disaster reduction application platform based on BeiDou navigation satellite system is constructed. The administrative distributed platform is integrated with BeiDou positioning and multiple communication ways so as to achieve main disaster reduction application services, including disaster information acquisition and monitoring, emergency relief for trapped people, on-site emergency relief command service, relief supplies＇ transportation monitoring, and disaster information publishing service. By the platform, serious disaster information reporting time may be reduced to one hour and the emergency decision-making information service for serious natural disasters can be effectively improved, and it will be helpful to provide technical references for the industrial application and promotion of BeiDou inte- grated disaster reduction.
