Abstract
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.
Highlights
With the improvement of people’s living standards, the population aging problem has become increasingly serious in China
The distributed Kalman Filter (dKF) designed in this paper under Colored Measurement Noise (CMN) with switch Colouredness Factor Matrix (CFM) has demonstrated the ability to improve online the performance of the Inertial Navigation System (INS)/Ultra Wide Band (UWB) integrated human localization system in indoor environments
The effect was achieved with determining the optimal CFM by solving the minimization problem and modifying the Kalman Filter (KF)-based fusion filter
Summary
With the improvement of people’s living standards, the population aging problem has become increasingly serious in China. As an important technology to assist indoor medical care, localization and tracking of target personnel appear in many works (Chen et al, 2020; Tian et al, 2020), and many approaches have been developed to provide the localization with sufficient accuracy. The Global Positioning System (GPS) is most widely used for localization solution (El-Sheimy & Youssef, 2020; Li et al, 2020; Mosavi & Shafiee, 2016). The GPS signals are used in Sekaran et al (2020) to navigate a robot car. A drawback of GPS is its signals are not always available in indoor environments (El-Sheimy & Li, 2021)
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