Paper Info
Title
Radiation Sensitivity Analysis of Ocean Wake Information Detection System Based on Visible Light Remote Sensing
Abstract
Various ships and submerged moving objects in the ocean are key targets of numerous remote sensors. Wake has developed into one of the key detection targets of ocean visible light remote sensing as the visible trail information left by moving objects on the ocean surface. In the situation of slow ship speed, deep draft, and the existence of air clouds and fog, the wake target signal is weak, and the signal-to-noise ratio is low due to the low reflectivity of the sea surface and the interference of the background waves on the sea surface. This paper analyzes the radiative sensitivity of visible light imaging systems for the most crucial wake detection indicator in order to address the aforementioned issues. The noise equivalent reflectance difference, which is widely used to describe radiative sensitivity in engineering, is derived and numerically simulated by establishing the imaging link model based on TDICCD. We calculated the noise equivalent reflectivity difference for eight bands commonly used in ocean remote sensing; results show that the index is generally on the order of 10 4, and with the increase in the central wavelength, the value of noise equivalent reflectance difference also shows a downward trend and is stable within a certain value range. This research provides theoretical guidance for the engineering design of a visible spectrum imaging system for wake detection, aids in improving the imaging system's capacity to detect weak wake signals, and provides a basis for subsequent wake detection and enhancement processing, removal of false wakes, and retrieval of ship information.
Year
DOI
Venue
2022
10.3390/rs14164054
REMOTE SENSING
Keywords
DocType
Volume
wake detection, radiation sensitivity, noise equivalent reflectance difference
Journal
14
Issue
ISSN
Citations 
16
2072-4292
0
PageRank 
References 
Authors
0.34
0
5
Name
Order
Citations
PageRank
Shipeng Ying100.68
Hongsong Qu201.35
Shuping Tao302.03
Liangliang Zheng402.03
Xiaobin Wu501.01