Results 11 to 20 of about 8,926,578 (308)
IEEE Access, 2018 In tracking a maneuverable target, a proper estimation method with better filtering accuracy, stronger robustness, and faster convergence speed is crucial to the tracking system.
Jian Wang, Tao Zhang, Xiang Xu, Yao Li
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Strong tracking SCKF based on adaptive CS model for manoeuvring aircraft tracking [PDF]
IET Radar, Sonar & Navigation, 2018 A novel tracking algorithm is proposed by the integration of the adaptive current statistical (CS) model and the modified strong tracking (ST) square‐root cubature Kalman filter (SCKF) for the manoeuvring aircraft tracking problem. Firstly, the acceleration recursion equation and the acceleration mean input estimation are combined in order to realise ...
Haowei Zhang +4 more
semanticscholar +4 more sources
Strong tracking extended particle filter for manoeuvring target tracking [PDF]
IET Radar, Sonar & Navigation, 2020 To improve the stability and accuracy of manoeuvring target tracking in three‐dimensional space based on the angle of arrival (AOA) and its rate of change observations, this study presents a new observation fusion method by fusing the received signal strength (RSS) with AOA and the rate of change of AOA.
Zhilei Ge +4 more
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C/N0 Estimator Based on the Adaptive Strong Tracking Kalman Filter for GNSS Vector Receivers. [PDF]
Sensors (Basel), 2020 The carrier-to-noise ratio (C/N0) is an important indicator of the signal quality of global navigation satellite system receivers. In a vector receiver, estimating C/N0 using a signal amplitude Kalman filter is a typical method.
Liu S, Li S, Zheng J, Fu Q, Yuan Y.
europepmc +2 more sources
Target Tracking Algorithm Based on Adaptive Strong Tracking Extended Kalman Filter
ElectronicsKalman filtering is a common filtering method for millimeter-wave traffic radars. The proposal is for an Adaptive Strong Tracking Extended Kalman Filter (EKF) algorithm that aims to address the issues of classic EKF’s low accuracy and lengthy convergence time. This method, which incorporates time-varying fading effects into the covariance matrix of the
Feng Tian, Xinzhao Guo, Weibo Fu
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IEEE Access, 2019 Unknown biases or perturbations in the INS/GNSS integrated navigation system may produce unforeseeable negative effects when the navigation states are estimated by using the Kalman filtering and its variants.
Tai-Shan Lou +3 more
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Strong Tracking of a H-Infinity Filter in Lithium-Ion Battery State of Charge Estimation
Energies, 2018 The accuracy of state-of-charge (SOC) estimation, one of the most important functions of a battery management system (BMS), is the basis for the proper operation of an electric vehicle. This study proposes a method for accurate SOC estimation. To achieve
Bizhong Xia +6 more
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An Adaptive Compensation Algorithm for Temperature Drift of Micro-Electro-Mechanical Systems Gyroscopes Using a Strong Tracking Kalman Filter [PDF]
Sensors, 2015 We present an adaptive algorithm for a system integrated with micro-electro-mechanical systems (MEMS) gyroscopes and a compass to eliminate the influence from the environment, compensate the temperature drift precisely, and improve the accuracy of the ...
Yibo Feng, Xisheng Li, Xiaojuan Zhang
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A novel strong tracking cubature Kalman filter and its application in maneuvering target tracking
Chinese Journal of Aeronautics, 2019 The fading factor exerts a significant role in the strong tracking idea. However, traditional fading factor introduction method hinders the accuracy and robustness advantages of current strong-tracking-based nonlinear filtering algorithms such as ...
An Zhang, Shuida Bao, Fei Gao, W. Bi
semanticscholar +3 more sources
An Improved Strong Tracking Kalman Filter Algorithm for the Initial Alignment of the Shearer
Complexity, 2019 The strap-down inertial navigation system (SINS) is a commonly used sensor for autonomous underground navigation, which can be used for shearer positioning under a coal mine.
Yuming Chen +4 more
doaj +2 more sources