Results 31 to 40 of about 1,423 (188)
Application of Strong Tracking Modified SRCKF Algorithm in Single Observer Passive Tracking [PDF]
Jisuanji gongcheng, 2016 In order to improve the performance of Square Root Cubature Kalman Filtering(STSRCKF) algorithm to track maneuvering target in single observer passive tracking,a Strong Tracking Modified SRCKF(ST-MSRCKF) algorithm is presented.Target state variables and ...
ZHANG Zhuoran,YE Guangqiang,ZHAO Xiaolin
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An Improved Location Algorithm by Extend Square-root Cubature Kalman Filter [PDF]
Journal of Computers, 2013 In this paper, the new nonlinear filter method Cubature Kalman Filter (CKF) is improved to solve the passive location problem. Firstly, the Empirical Mode Decomposition (EMD) algorithm is used to estimate the new measurement noise covariance in the filter process; And then the new covariance of the noise is brought into the circle; Meanwhile, the ...
Rui Guo Sheng, Yang Zhang, Jun Miao
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Adaptive Cubature Kalman Filter Based on the Expectation-Maximization Algorithm
IEEE Access, 2019 A cubature Kalman filter is considered to be one of the most useful methods for nonlinear systems. However, when the statistical characteristics of noise are unknown, the estimation accuracy is degraded. Therefore, an adaptive square-root cubature Kalman
Weidong Zhou, Lu Liu
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A modified bayesian filter for randomly delayed measurements [PDF]
, 2017 © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new ...
Bhoumik, S, Date, P, Singh, AK
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Moment Estimation Using a Marginalized Transform [PDF]
, 2012 We present a method for estimating mean and covariance of a transformed Gaussian random variable. The method is based on evaluations of the transforming function and resembles the unscented transform and Gauss-Hermite integration in that respect.
Sandblom, Fredrik, Svensson, Lennart
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Control Optimization of Stochastic Systems Based on Adaptive Correction CKF Algorithm
International Journal of Aerospace Engineering, 2020 Standard cubature Kalman filter (CKF) algorithm has some disadvantages in stochastic system control, such as low control accuracy and poor robustness.
FengJun Hu, Qian Zhang, Gang Wu
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Cognitive Computation and Systems, 2022 Aiming at meetiing the need to filtering flight trajectory data for aircraft testing, a novel adaptive cubature Kalman filter (CKF) is proposed based on the maximum correntropy and Gaussian‐sum in this paper.
Jing G. Bai +4 more
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Sensors, 2022 The accurate estimation of the mass and center of gravity (CG) position is key to vehicle dynamics modeling. The perturbation of key parameters in vehicle dynamics models can result in a reduction of accurate vehicle control and may even cause serious ...
Zhiguo Zhang, Guodong Yin, Zhixin Wu
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On the vehicle sideslip angle estimation: a literature review of methods, models and innovations [PDF]
, 2018 Typical active safety systems controlling the dynamics of passenger cars rely on real-time monitoring of the vehicle sideslip angle (VSA), together with other signals like wheel angular velocities, steering angle, lateral acceleration, and the rate of ...
Bao +19 more
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Extended Kalman Filter Using Orthogonal Polynomials
IEEE Access, 2021 This paper reports a new extended Kalman filter where the underlying nonlinear functions are linearized using a Gaussian orthogonal basis of a weighted $\mathcal {L}_{2}$ space.
Kundan Kumar +2 more
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