Yan Wang*, You Lu, Yuqing Zhou, Zhijian Zhao
CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2673-2703, 2024, DOI:10.32604/cmes.2023.046743
Abstract Indoor positioning is a key technology in today’s intelligent environments, and it plays a crucial role in many application areas. This paper proposed an unscented Kalman filter (UKF) based on the maximum correntropy criterion (MCC) instead of the minimum mean square error criterion (MMSE). This innovative approach is applied to the loose coupling of the Inertial Navigation System (INS) and Ultra-Wideband (UWB). By introducing the maximum correntropy criterion, the MCCUKF algorithm dynamically adjusts the covariance matrices of the system noise and the measurement noise, thus enhancing its adaptability to diverse environmental localization requirements. Particularly in the presence of non-Gaussian noise,… More >
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