English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

This paper presents a novel automatic real-time remote sensing algorithm that uses radar images and global positioning satellite system measurements to estimate the ice-drift velocity vector in a region around a free-floating and potentially moving vessel. It is motivated by the low image frequency of satellite systems together with the inconvenience of deploying and retrieving ice trackers (beacons) on the ice. The algorithm combines radar image processing with two Kalman filters to produce the estimated local drift vector decoupled from the ship motion. The proposed design is verified using a full-scale data set from an ice management operation north of Svalbard in 2015. It is found that the performance of the algorithm is comparable with that of trackers on the ice.

An Ice-Drift Estimation Algorithm Using Radar and Ship Motion Measurements