Shitong Ye¹, Bo Yang^2,*, Hao Quan³, Shan Liu⁴, Minyi Tang⁵, Jiawei Tian^6,*

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.2, pp. 2287-2306, 2025, DOI:10.32604/cmes.2025.066195 - 31 August 2025

Abstract Computer-aided surgical navigation technology helps and guides doctors to complete the operation smoothly, which simulates the whole surgical environment with computer technology, and then visualizes the whole operation link in three dimensions. At present, common image-guided surgical techniques such as computed tomography (CT) and X-ray imaging (X-ray) will cause radiation damage to the human body during the imaging process. To address this, we propose a novel Extended Kalman filter-based model that tracks the puncture needle-point using an ultrasound probe. To address the limitations of Kalman filtering methods based on position and velocity, our method of More >

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 >

Tanvir Fatima Naik Bukht¹, Abdulwahab Alazeb², Naif Al Mudawi², Bayan Alabdullah³, Khaled Alnowaiser⁴, Ahmad Jalal¹, Hui Liu^5,*

CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 2987-3002, 2024, DOI:10.32604/cmc.2024.053547 - 18 November 2024

Abstract In the field of computer vision and pattern recognition, knowledge based on images of human activity has gained popularity as a research topic. Activity recognition is the process of determining human behavior based on an image. We implemented an Extended Kalman filter to create an activity recognition system here. The proposed method applies an HSI color transformation in its initial stages to improve the clarity of the frame of the image. To minimize noise, we use Gaussian filters. Extraction of silhouette using the statistical method. We use Binary Robust Invariant Scalable Keypoints (BRISK) and SIFT More >

Dah-Jing Jwo^*

CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 2137-2155, 2023, DOI:10.32604/cmc.2023.034308 - 29 November 2023

Abstract The goal of this work is to provide an understanding of estimation technology for both linear and nonlinear dynamical systems. A critical analysis of both the Kalman filter (KF) and the extended Kalman filter (EKF) will be provided, along with examples to illustrate some important issues related to filtering convergence due to system modeling. A conceptual explanation of the topic with illustrative examples provided in the paper can help the readers capture the essential principles and avoid making mistakes while implementing the algorithms. Adding fictitious process noise to the system model assumed by the filter… More >

Khakoo Mal^1,2,*, Tayab Din Memon^1,3, Imtiaz Hussain Kalwar⁴, Bhawani Shankar Chowdhry⁵

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3351-3370, 2023, DOI:10.32604/cmc.2023.032940 - 31 October 2022

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… More >

Qingdong Wu¹, Chenxi Li², Tao Shen², Yuan Xu^2,3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.3, pp. 1761-1772, 2023, DOI:10.32604/cmes.2022.020545 - 20 September 2022

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 More >

T. Jagadesh^1,2, B. Sheela Rani^3,*

Computer Systems Science and Engineering, Vol.44, No.3, pp. 2569-2583, 2023, DOI:10.32604/csse.2023.027239 - 01 August 2022

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… More >

Dah-Jing Jwo^*

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 6107-6124, 2022, DOI:10.32604/cmc.2022.024722 - 14 January 2022

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… More >

Khakoo Mal^1,2, Imtiaz Hussain Kalwar³, Khurram Shaikh², Tayab Din Memon^2,4, Bhawani Shankar Chowdhry¹, Kashif Nisar^5,*, Manoj Gupta⁶

Intelligent Automation & Soft Computing, Vol.28, No.3, pp. 823-841, 2021, DOI:10.32604/iasc.2021.016990 - 20 April 2021

Abstract

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

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