Colored Measurement Noise(CMN)has a great impact on the accuracy of human localization in indoor environments with Inertial Navigation System(INS)integrated with Ultra Wide Band(UWB).To mitigate its influence,a distri...Colored Measurement Noise(CMN)has a great impact on the accuracy of human localization in indoor environments with Inertial Navigation System(INS)integrated with Ultra Wide Band(UWB).To mitigate its influence,a distributed Kalman Filter(dKF)is developed for Gauss-Markov CMN with switching Colouredness Factor Matrix(CFM).In the proposed scheme,a data fusion filter employs the difference between the INS-and UWB-based distance measurements.The main filter produces a final optimal estimate of the human position by fusing the estimates from local filters.The effect of CMN is overcome by using measurement differencing of noisy observations.The tests show that the proposed dKF developed for CMN with CFM can reduce the localization error compared to the original dKF,and thus effectively improve the localization accuracy.展开更多
基金NSFC Grant 61803175,Shandong Key R&D Program 2019JZZY021005Mexican Consejo Nacional de Cienciay Tecnologıa Project A1-S-10287 Grant CB2017-2018.
文摘Colored Measurement Noise(CMN)has a great impact on the accuracy of human localization in indoor environments with Inertial Navigation System(INS)integrated with Ultra Wide Band(UWB).To mitigate its influence,a distributed Kalman Filter(dKF)is developed for Gauss-Markov CMN with switching Colouredness Factor Matrix(CFM).In the proposed scheme,a data fusion filter employs the difference between the INS-and UWB-based distance measurements.The main filter produces a final optimal estimate of the human position by fusing the estimates from local filters.The effect of CMN is overcome by using measurement differencing of noisy observations.The tests show that the proposed dKF developed for CMN with CFM can reduce the localization error compared to the original dKF,and thus effectively improve the localization accuracy.
