Scaled UKF with reduced sigma points particle filter for a red shift navigation system

Zhao, Guangqiong; Fu, Kui; Chen, Shaogang; Tang, Zhong-Liang; He, Wei

doi:10.1109/chicc.2015.7260453

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Unscented Kalman Filter (Ukf)1

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2017

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“…The UKF [28,29] is based on the propagation of the sigma points, calculated from the state and the state covariance matrix, on non-linear equations of the model. This algorithm needs to run recursively starting from the initial condition: …”

Section: Unscented Kalman Filter (Ukf)mentioning

confidence: 99%

DocuScooter: An Innovative Underwater Scooter add-on for Scuba Diving and Citizen Science

Panebianco

Scaradozzi

Ciuccoli

et al. 2017

IRATJ

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In order to obtain robust and measurable data from the marine environment, citizen science projects need user-friendly tools that, during dives, autonomously gather information in an easy, low-cost and integrated way. Data collected from different devices and by different untrained divers must have good estimation of the position where the information has been acquired. With this goal, in the context of the Green Bubbles project, a novel platform, called DocuScooter has been designed and developed. DocuScooter implements all the algorithms to filter and merge data with correct timestamp and position preparing the complete mission report. After the mission, the diver can upload the report on an appropriate web service to produce a 3D documentation. In order to obtain the underwater position during the dive, a tailored device compatible with the platform is also presented. Result of the prototype of the platform and the first results of the position estimation algorithm are presented and discussed.

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Section: Unscented Kalman Filter (Ukf)mentioning

confidence: 99%