A New Adaptive High-Order Unscented Kalman Filter for Improving the Accuracy and Robustness of Target Tracking

In target tracking, the tracking process needs to constantly update the data information. For maneuvering target, model mismatch and loss of high-order moment information disrupt the accuracy of the state estimation. In this paper, an adaptive high-order unscented Kalman filter (AHUKF) algorithm is...

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Veröffentlicht in:	IEEE access 2019, Vol.7, p.118484-118497
Hauptverfasser:	Zhou, Weidong, Hou, Jiaxin
Format:	Artikel
Sprache:	eng
Schlagworte:	Adaptation models Adaptive algorithms adaptive filtering Adaptive filters Algorithms Covariance matrices Covariance matrix Dynamic models Estimation Exact solutions Heuristic algorithms high-order UT sampling Kalman filters Maneuvering targets Mutation optimal adaptive factor orthogonality principle Parameters Robustness Stability analysis State estimation Target tracking Tracking Tracking problem UKF
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