Article
Engineering, Aerospace
Minglei Du, Haodong Zou, Tinghui Wang, Ke Zhu
Summary: This paper proposes a passive localization algorithm based on UAV aerial images and Angle of Arrival (AOA). The algorithm calculates the target localization factor based on image information and azimuth elements, and obtains the target coordinate value by solving the joint UAV swarm positional information. Experimental results show that the algorithm can significantly improve target positioning accuracy and ensure stable tracking.
Article
Engineering, Marine
Tianjing Wang, Lanyong Zhang, Sheng Liu
Summary: Robust nonlinear filtering is an important method for tracking maneuvering targets in non-Gaussian noise environments. This paper proposes a novel robust cubature Kalman filter that utilizes a new cubature formula and the maximum correntropy criterion (MCC) to improve the performance of nonlinear filtering in mixed Gaussian and non-Gaussian noise situations. Experimental results demonstrate that the proposed filter achieves higher tracking accuracy and better numerical stability compared to other common nonlinear filters.
JOURNAL OF MARINE SCIENCE AND ENGINEERING
(2022)
Article
Automation & Control Systems
Mohamed Barbary, Mohamed H. Abd ElAzeem
Summary: A novel approach using Cubature Kalman and Multi-Bernoulli filters, combined with variational Bayesian-TBD to estimate measurement variances, is proposed to address the detection and tracking of micro-drones. Simulation results confirm the effectiveness and robustness of the algorithm in estimating the movement state of micro-drones.
Article
Telecommunications
Xiaohan Qi, Jianxiao Xie
Summary: This paper proposes a novel Cubature Kalman Filter framework to track channel state information in OTFS systems, addressing the challenge of high-speed channel variation. By training one beam pair to maintain the communication link and improve the accuracy of the estimated beam angle.
CHINA COMMUNICATIONS
(2023)
Article
Chemistry, Multidisciplinary
Yalun Luo, Zhaoming Li, Yurong Liao, Haining Wang, Shuyan Ni
Summary: This paper proposes a strong tracking cubature Kalman filter adaptive interactive multi-model algorithm for the tracking of hypersonic targets. By introducing fading factors and singular value decomposition, the algorithm improves tracking accuracy and convergence speed.
APPLIED SCIENCES-BASEL
(2022)
Article
Chemistry, Analytical
Xiangzhou Ye, Jian Wang, Dongjie Wu, Yong Zhang, Bing Li
Summary: The features of measurement and process noise are directly related to the optimal performance of the cubature Kalman filter. The maneuvering target model's high level of uncertainty and non-Gaussian mean noise are typical issues that the radar tracking system must deal with, making it impossible to obtain the appropriate estimation. How to strike a compromise between high robustness and estimation accuracy while designing filters has always been challenging.
Article
Engineering, Marine
Sisi Wang, Lijun Wang, Namkyun Im, Weidong Zhang, Xijin Li
Summary: A real-time parameter identification method based on nonlinear Gaussian filtering algorithm and nonlinear ship response model is proposed to improve system identification accuracy and reduce computational complexity.
Article
Chemistry, Analytical
Shun Wang, Sheng Xu, Zhihao Ma, Dashuai Wang, Weimin Li
Summary: This paper focuses on moving-target detection and tracking in a three-dimensional (3D) space, proposing a visual target tracking system that only utilizes a two-dimensional (2D) camera. An improved optical flow method, with modifications in the pyramid, warping, and cost volume network (PWC-Net), is applied for quick target detection. Additionally, a clustering algorithm accurately extracts the moving target from a noisy background. The target position is then estimated using a proposed geometrical pinhole imaging algorithm and cubature Kalman filter (CKF) based on the camera's installation position and inner parameters.
Article
Engineering, Mechanical
M. Nosratollahi, M. Delalat
Summary: This paper investigates the importance of using unmanned vehicles for challenging missions such as search and rescue, surveillance, and recognition, and explores the capability of different dynamic models in tracking high-maneuverability targets. Through testing and comparing 10 different dynamic models and filters, it identifies the most suitable model for tracking aerial targets.
IRANIAN JOURNAL OF SCIENCE AND TECHNOLOGY-TRANSACTIONS OF MECHANICAL ENGINEERING
(2023)
Article
Engineering, Electrical & Electronic
Kai Zhang, Hongjian Wang, Honghan Zhang, Naifu Luo, Jingfei Ren
Summary: Underwater target tracking with signal propagation delay is a challenging task. The unscented Gauss-Helmert filter (UGHF) algorithm is widely used and shows good tracking performance. However, its accuracy is limited due to its second-order unscented transformation. To improve the tracking accuracy, a high-order UGHF (HOUGHF) algorithm using high-order unscented transformation is proposed. The maximum correntropy HOGGHF (MCHOGGHF) algorithm is also proposed to handle non-Gaussian noise. Simulation and sea trial results demonstrate that the proposed algorithms outperform the UGHF algorithm and the MCHOGGH algorithm has higher estimation accuracy under non-Gaussian noise.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
Article
Environmental Sciences
Zihao Huang, Shijin Chen, Chengpeng Hao, Danilo Orlando
Summary: In bearings-only target tracking, the pseudo-linear Kalman filter (PLKF) is popular for stability and low computational burden, but suffers from bias problems due to correlated measurement vector and noise; an unbiased PLKF algorithm (UB-PLKF) is proposed to address this issue, along with a velocity-constrained version (VC-PLKF) to further improve performance, outperforming other methods in both non-manoeuvring and manoeuvring scenarios according to simulations.
Article
Computer Science, Information Systems
Junnan Wang, Zhenhong Jia, Huicheng Lai, Fei Shi
Summary: In this paper, a real-time target face tracking algorithm based on saliency detection and Camshift is proposed to take advantage of the speed advantage of Camshift and overcome the problem of its poor robustness in target tracking. The algorithm first removes the background around the target using the saliency detection algorithm MBplus, and then uses Camshift to search and localize the targets in the processed video frames. Additionally, the Kalman filter is used to predict the position of the target in the current frame to compensate for the lack of tracking ability of Camshift for some characteristic targets.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Remote Sensing
Zhong Shi, Fanyu Zhao, Xin Wang, Zhonghe Jin
Summary: The research proposes a trajectory prediction model for multi-satellite cooperative observation of moving targets, consisting of linear Gaussian and non-linear Gaussian parts, as well as a prediction method combining long short-term memory networks and Bayesian inference.
INTERNATIONAL JOURNAL OF REMOTE SENSING
(2021)
Article
Automation & Control Systems
Juan-Carlos Santos-Leon, Ramon Orive, Daniel Acosta, Leopoldo Acosta
Summary: This paper revisits the construction and effectiveness of the Cubature Kalman Filter (CKF) and its extensions for higher precision, establishing stable cubature rules within a mathematical framework of numerical integration. By discretizing higher order partial derivatives, stable rules for degrees 5 and 7 are provided and tested for application in filter algorithms through various examples.
Article
Engineering, Chemical
Limei Wang, Jiyan Han, Chang Liu, Guochun Li
Summary: This paper introduces an adaptive noise CKF algorithm based on the improved Cubature Kalman Filter (CKF) and an adaptive noise algorithm. The results show that the proposed algorithm can deal with external disturbance better and maintain good stability under most working conditions. The estimation accuracy of online identification parameters is improved compared to offline identification.
INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH
(2022)