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  • Open Access


    FPGA Implementation of Extended Kalman Filter for Parameters Estimation of Railway Wheelset

    Khakoo Mal1,2,*, Tayab Din Memon1,3, Imtiaz Hussain Kalwar4, Bhawani Shankar Chowdhry5

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3351-3370, 2023, DOI:10.32604/cmc.2023.032940

    Abstract It is necessary to know the status of adhesion conditions between wheel and rail for efficient accelerating and decelerating of railroad vehicle. The proper estimation of adhesion conditions and their real-time implementation is considered a challenge for scholars. In this paper, the development of simulation model of extended Kalman filter (EKF) in MATLAB/Simulink is presented to estimate various railway wheelset parameters in different contact conditions of track. Due to concurrent in nature, the Xilinx® System-on-Chip Zynq Field Programmable Gate Array (FPGA) device is chosen to check the onboard estimation of wheel-rail interaction parameters by using the National Instruments (NI) myRIO®More >

  • Open Access


    Improved Adaptive Iterated Extended Kalman Filter for GNSS/INS/UWB-Integrated Fixed-Point Positioning

    Qingdong Wu1, Chenxi Li2, Tao Shen2, Yuan Xu2,3,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.3, pp. 1761-1772, 2023, DOI:10.32604/cmes.2022.020545

    Abstract To provide stable and accurate position information of control points in a complex coastal environment, an adaptive iterated extended Kalman filter (AIEKF) for fixed-point positioning integrating global navigation satellite system, inertial navigation system, and ultra wide band (UWB) is proposed. In this method, the switched global navigation satellite system (GNSS) and UWB measurement are used as the measurement of the proposed filter. For the data fusion filter, the expectation-maximization (EM) based IEKF is used as the forward filter, then, the Rauch-Tung-Striebel smoother for IEKF filter’s result smoothing. Tests illustrate that the proposed AIEKF is able to provide an accurate estimation. More >

  • Open Access


    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


    Estimator-Based GPS Attitude and Angular Velocity Determination

    Dah-Jing Jwo*

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 6107-6124, 2022, DOI:10.32604/cmc.2022.024722

    Abstract In this paper, the estimator-based Global Positioning System (GPS) attitude and angular velocity determination is presented. Outputs of the attitude estimator include the attitude angles and attitude rates or body angular velocities, depending on the design of estimator. Traditionally as a position, velocity and time sensor, the GPS also offers a free attitude-determination interferometer. GPS research and applications to the field of attitude determination using carrier phase or Doppler measurement has been extensively conducted. The raw attitude solution using the interferometry technique based on the least-squares approach is inherently noisy. The estimator such as the Kalman filter (KF) or extended… More >

  • Open Access


    A New Estimation of Nonlinear Contact Forces of Railway Vehicle

    Khakoo Mal1,2, Imtiaz Hussain Kalwar3, Khurram Shaikh2, Tayab Din Memon2,4, Bhawani Shankar Chowdhry1, Kashif Nisar5,*, Manoj Gupta6

    Intelligent Automation & Soft Computing, Vol.28, No.3, pp. 823-841, 2021, DOI:10.32604/iasc.2021.016990


    The core part of any study of rolling stock behavior is the wheel-track interaction patch because the forces produced at the wheel-track interface govern the dynamic behavior of the whole railway vehicle. It is significant to know the nature of the contact force to design more effective vehicle dynamics control systems and condition monitoring systems. However, it is hard to find the status of this adhesion force due to its complexity, highly non-linear nature, and also affected with an unpredictable operation environment. The purpose of this paper is to develop a model-based estimation technique using the Extended Kalman Filter (EKF)… More >

  • Open Access


    Kernel Entropy Based Extended Kalman Filter for GPS Navigation Processing

    Dah-Jing Jwo*, Jui-Tao Lee

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

    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) and is optimal only under… More >

  • Open Access


    Minimum Error Entropy Based EKF for GPS Code Tracking Loop

    Dah-Jing Jwo1,*, Jen-Hsien Lai2

    CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 2883-2898, 2021, DOI:10.32604/cmc.2021.015102

    Abstract This paper investigates the minimum error entropy based extended Kalman filter (MEEKF) for multipath parameter estimation of the Global Positioning System (GPS). The extended Kalman filter (EKF) is designed to give a preliminary estimation of the state. The scheme is designed by introducing an additional term, which is tuned according to the higher order moment of the estimation error. The minimum error entropy criterion is introduced for updating the entropy of the innovation at each time step. According to the stochastic information gradient method, an optimal filer gain matrix is obtained. The mean square error criterion is limited to the… More >

  • Open Access


    Estimation of Quaternion Motion for GPS-Based Attitude Determination Using the Extended Kalman Filter

    Dah-Jing Jwo*

    CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 2105-2126, 2021, DOI:10.32604/cmc.2020.014241

    Abstract In this paper, the Global Positioning System (GPS) interferometer provides the preliminarily computed quaternions, which are then employed as the measurement of the extended Kalman filter (EKF) for the attitude determination system. The estimated quaternion elements from the EKF output with noticeably improved precision can be converted to the Euler angles for navigation applications. The aim of the study is twofold. Firstly, the GPS-based computed quaternion vector is utilized to avoid the singularity problem. Secondly, the quaternion estimator based on the EKF is adopted to improve the estimation accuracy. Determination of the unknown baseline vector between the antennas sits at… More >

  • Open Access


    Observability Analysis in Parameters Estimation of an Uncooperative Space Target

    Xianghao Hou1, *, Gang Qiao1

    CMES-Computer Modeling in Engineering & Sciences, Vol.122, No.1, pp. 175-205, 2020, DOI:10.32604/cmes.2020.08452

    Abstract To study the parameter estimating effects of a free-floating tumbling space target, the extended Kalman filter (EKF) scheme is utilized with different high-nonlinear translational and rotational coupled kinematic & dynamic models on the LIDAR measurements. Applying the aforementioned models and measurements results in the situation where one single state can be estimated differently with varying accuracies since the EKFs based on different models have different observabilities. In the proposed EKFs, the traditional quaternions based kinematics and dynamics and the dual vector quaternions (DVQ) based kinematics and dynamics are used for the modeling of the relative motions between a chaser satellite… More >

  • Open Access


    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 >

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