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

Keywords: signal detection, empirical mode decomposition, shaft-rate electric field Abstract. In order to effectively extracting out weak ship shaft-rate electric field signal immersed in strong ocean background noise, a multi sub-band sliding detection algorithm capitalizing on Empirical Mode Decomposition (EMD) with Fourth-Order Mixed Cumulant (FOMC) Diagonal Slice is proposed. Firstly, EMD method was employed to adaptively decomposition the signal into a set of Intrinsic Mode Functions (IMFs), of which the validities were determined according to correlation coefficient criterion. Subsequently exploiting the property of higher order cumulant that Gaussian colored noise can be suppressed, sliding power spectrum detection of FOMC diagonal slice of the selected IMFs was carried out. Field data processing result illustrates that, proposed algorithm can effectively and reliably detect target signal even under very low Signal to Noise Ratio (SNR), having a promising application prospect.

A Multi Sub-band Sliding Detection Algorithm of Ship Shaft-Rate Electric Field Signal