Amita Biswal, Dah-Jing Jwo^*

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.1, pp. 927-944, 2025, DOI:10.32604/cmes.2025.067299 - 31 July 2025

Abstract The extended Kalman filter (EKF) is extensively applied in integrated navigation systems that combine the global navigation satellite system (GNSS) and strap-down inertial navigation system (SINS). However, the performance of the EKF can be severely impacted by non-Gaussian noise and measurement noise uncertainties, making it difficult to achieve optimal GNSS/INS integration. Dealing with non-Gaussian noise remains a significant challenge in filter development today. Therefore, the maximum correntropy criterion (MCC) is utilized in EKFs to manage heavy-tailed measurement noise. However, its capability to handle non-Gaussian process noise and unknown disturbances remains largely unexplored. In this paper,… More >

Dah-Jing Jwo^1,2,*, Yi Chang², Ta-Shun Cho³

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.3, pp. 2771-2789, 2025, DOI:10.32604/cmes.2025.057825 - 03 March 2025

Abstract In this paper, an advanced satellite navigation filter design, referred to as the Variational Bayesian Maximum Correntropy Extended Kalman Filter (VBMCEKF), is introduced to enhance robustness and adaptability in scenarios with non-Gaussian noise and heavy-tailed outliers. The proposed design modifies the extended Kalman filter (EKF) for the global navigation satellite system (GNSS), integrating the maximum correntropy criterion (MCC) and the variational Bayesian (VB) method. This adaptive algorithm effectively reduces non-line-of-sight (NLOS) reception contamination and improves estimation accuracy, particularly in time-varying GNSS measurements. Experimental results show that the proposed method significantly outperforms conventional approaches in estimation More >

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 - 11 March 2024

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… More >

Dah-Jing Jwo^*, Jui-Tao Lee

CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 857-876, 2021, DOI:10.32604/cmc.2021.016894 - 22 March 2021

Abstract This paper investigates the kernel entropy based extended Kalman filter (EKF) as the navigation processor for the Global Navigation Satellite Systems (GNSS), such as the Global Positioning System (GPS). The algorithm is effective for dealing with non-Gaussian errors or heavy-tailed (or impulsive) interference errors, such as the multipath. The kernel minimum error entropy (MEE) and maximum correntropy criterion (MCC) based filtering for satellite navigation system is involved for dealing with non-Gaussian errors or heavy-tailed interference errors or outliers of the GPS. The standard EKF method is derived based on minimization of mean square error (MSE)… More >