2019
DOI: 10.1016/j.ast.2019.105405
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A conditional cubature Kalman filter and its application to transfer alignment of distributed position and orientation system

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Cited by 28 publications
(18 citation statements)
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“…(1) Flexure angle model Considering that the flexure angles 𝜂 𝑥 , 𝜂 𝑦 , 𝜂 𝑧 in the three directions are independent of each other, the flexure angles can be modelled as (Lu et al, 2017;Gong and Chen, 2019):…”
Section: Dynamic Angular Deformation Modelmentioning
confidence: 99%
See 1 more Smart Citation
“…(1) Flexure angle model Considering that the flexure angles 𝜂 𝑥 , 𝜂 𝑦 , 𝜂 𝑧 in the three directions are independent of each other, the flexure angles can be modelled as (Lu et al, 2017;Gong and Chen, 2019):…”
Section: Dynamic Angular Deformation Modelmentioning
confidence: 99%
“…The empirical model of the dynamic angular deformation is usually considered as a second-order Markov process, and the model parameters are usually set empirically or identified beforehand according to the test data (Wendel et al, 2004;Wu et al, 2013;Lu et al, 2017). However, the actual dynamic angular deformation changes complicatedly due to the internal complex structure, external random interference and other factors (Verhaegen and Zbikowski, 2017;Gong and Chen, 2019). Therefore, when the preset empirical model does not conform to the actual change of the dynamic angular deformation, the mismatch between the empirical model and the actual dynamic angular deformation will reduce the transfer alignment accuracy (Wendel et al, 2004;Wu et al, 2013;Gong et al, 2014).…”
Section: Introductionmentioning
confidence: 99%
“…The user heading, absolute velocity, and coordinates were considered in the measurement model. This KF-based algorithms may not apply to all positioning estimation scenarios; some other non-linear models that are derivatives of the EKF are also suggested by authors to face the estimation accuracy problems of the sensor states [112]. However, the KF-based algorithm is the most frequent method used by the authors of the selected articles discussed in this review.…”
Section: Positioning and Trackingmentioning
confidence: 99%
“…e state variables of the transfer-aligned nonlinear mathematical model were divided into two groups. One group was linear variables independent of nonlinear variables, and the other group was composed of nonlinear variables and coupling of linear variables [12]. Zhu et al proposed a new real-time gravity compensation method, which took the gravity disturbance as the error state of the POS Kalman filter.…”
Section: Introductionmentioning
confidence: 99%