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  • Open Access

    ARTICLE

    Maximum Correntropy Criterion-Based UKF for Loosely Coupling INS and UWB in Indoor Localization

    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 >

  • Open Access

    ARTICLE

    Time Delay Estimation in Radar System using Fuzzy Based Iterative Unscented Kalman Filter

    T. Jagadesh1,2, B. Sheela Rani3,*

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 2569-2583, 2023, DOI:10.32604/csse.2023.027239

    Abstract RSs (Radar Systems) identify and trace targets and are commonly employed in applications like air traffic control and remote sensing. They are necessary for monitoring precise target trajectories. Estimations of RSs are non-linear as the parameters TDEs (time delay Estimations) and Doppler shifts are computed on receipt of echoes where EKFs (Extended Kalman Filters) and UKFs (Unscented Kalman Filters) have not been examined for computations. RSs, certain times result in poor accuracies and SNRs (low signal to noise ratios) especially, while encountering complicated environments. This work proposes IUKFs (Iterated UKFs) to track online filter performances while using optimization techniques to… More >

  • Open Access

    ARTICLE

    Kalman Filter Estimation of Lithium Battery SOC Based on Model Capacity Updating

    Min Deng1, Quan Min1, Ge Yang1, Man Yu2,3,*

    Energy Engineering, Vol.119, No.2, pp. 739-754, 2022, DOI:10.32604/ee.2022.018025

    Abstract High-precision estimation of lithium battery SOC can effectively optimize vehicle energy management, improve lithium battery safety protection, extend lithium battery cycle life, and reduce new energy vehicle costs. Based on the forgetting factor recursive least square method (FFRLS), Thevenin equivalent circuit model and Singular Value Decomposition-Unscented Kalman Filter (SVD-UKF), the SVD-UKF combined lithium battery SOC estimation algorithm with model capacity update is proposed, aiming at further improving the SOC estimation accuracy of lithium battery. The parameter identification of Thevenin model is studied by using the forgetting factor recursive least square method. To overcoming the shortcomings of Kalman filter linearization error… More >

  • Open Access

    ARTICLE

    Estimation Performance for the Cubature Particle Filter under Nonlinear/Non-Gaussian Environments

    Dah-Jing Jwo1,*, Chien-Hao Tseng2

    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1555-1575, 2021, DOI:10.32604/cmc.2021.014875

    Abstract This paper evaluates the state estimation performance for processing nonlinear/non-Gaussian systems using the cubature particle filter (CPF), which is an estimation algorithm that combines the cubature Kalman filter (CKF) and the particle filter (PF). The CPF is essentially a realization of PF where the third-degree cubature rule based on numerical integration method is adopted to approximate the proposal distribution. It is beneficial where the CKF is used to generate the importance density function in the PF framework for effectively resolving the nonlinear/non-Gaussian problems. Based on the spherical-radial transformation to generate an even number of equally weighted cubature points, the CKF… More >

  • Open Access

    ARTICLE

    Robust Remaining Useful Life Estimation Based on an Improved Unscented Kalman Filtering Method

    Shenkun Zhao, Chao Jiang*, Zhe Zhang, Xiangyun Long

    CMES-Computer Modeling in Engineering & Sciences, Vol.123, No.3, pp. 1151-1173, 2020, DOI:10.32604/cmes.2020.08867

    Abstract In the Prognostics and Health Management (PHM), remaining useful life (RUL) is very important and utilized to ensure the reliability and safety of the operation of complex mechanical systems. Recently, unscented Kalman filtering (UKF) has been applied widely in the RUL estimation. For a degradation system, the relationship between its monitored measurements and its degradation states is assumed to be nonlinear in the conventional UKF. However, in some special degradation systems, their monitored measurements have a linear relation with their degradation states. For these special problems, it may bring estimation errors to use the UKF method directly. Besides, many uncertain… More >

  • Open Access

    ARTICLE

    A New Optimized Algorithm with Nonlinear Filter for Ultra-Tightly Coupled Integrated Navigation System of Land Vehicle

    Chien-Hao Tseng1, Dah-Jing Jwo2, Chih-Wen Chang1

    CMC-Computers, Materials & Continua, Vol.27, No.1, pp. 23-54, 2012, DOI:10.3970/cmc.2012.027.023

    Abstract The extended particle filter (EPF) assisted by the Takagi-Sugeno (T-S) fuzzy logic adaptive system (FLAS) is used to design the ultra-tightly coupled GPS/INS (inertial navigation system) integrated navigation, which can maneuver the vehicle environment and the GPS outages scenario. The traditional integrated navigation designs adopt a loosely or tightly coupled architecture, for which the GPS receiver may lose the lock due to the interference/jamming scenarios, high dynamic environments, and the periods of partial GPS shading. An ultra-tight GPS/INS architecture involves the integration of I (in-phase) and Q (quadrature) components from the correlator of a GPS receiver with the INS data.… More >

  • Open Access

    ARTICLE

    Improved GNSS Cooperation Positioning Algorithm for Indoor Localization

    Taoyun Zhou1,2, Baowang Lian1, Siqing Yang2,*, Yi Zhang1, Yangyang Liu1,3

    CMC-Computers, Materials & Continua, Vol.56, No.2, pp. 225-245, 2018, DOI: 10.3970/cmc.2018.02671

    Abstract For situations such as indoor and underground parking lots in which satellite signals are obstructed, GNSS cooperative positioning can be used to achieve high-precision positioning with the assistance of cooperative nodes. Here we study the cooperative positioning of two static nodes, node 1 is placed on the roof of the building and the satellite observation is ideal, node 2 is placed on the indoor windowsill where the occlusion situation is more serious, we mainly study how to locate node 2 with the assistance of node 1. Firstly, the two cooperative nodes are located with pseudo-range single point positioning, and the… More >

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