Refocusing High-Resolution SAR Images of Complex Moving Vessels Using Co-Evolutionary Particle Swarm Optimization

Abstract

To increase the global convergence and processing efficiency of particle swarm optimization (PSO) applied in the adaptive joint time-frequency, in this study an improved PSO is proposed to refocus the high-resolution SAR images of complex moving vessels in high sea states. According to the characteristics of the high-order multi-component polynomial phase signal, this algorithm provides parallel processing and co-evolution methods by setting the different permissions of the sub-population and sharing its search information. As a result, the multiple components can be extracted simultaneously. Experiments were conducted using the simulation data and Gaofen-3 (GF-3) SAR data. Results showed the processing speed increased by more than 40% and the global convergence was significantly improved. The imaging results verify the efficiency and robustness of this co-evolutionary PSO.

Editorial for the Special Issue “Remote Sensing of the Oceans: Blue Economy and Marine Pollution”

“…Detection of targets such as marine raft aquaculture, moving vessels, and the shoreline [1][2][3]; • Observation of spatio-temporal pattern of oil spills and coastal marine litter [4][5][6]; • Study of natural sea processes, including typhoon-induced storm surges, sub-mesoscale eddies and migration of the along-slope counter-flow [7][8][9]; • Analysis of scattering and spectral properties of the sea surface [10,11].…”

“…Those goals have been pursued using multi-platform and multi-frequency remote sensing tools together with theoretical models, numerical simulations, and in-situ measurements. Most of the study exploited satellite data, including microwave-synthetic aperture radar (SAR) imagery collected in single-, dual-and quad-polarimetric imaging modes, radar altimeters [1][2][3][4][5]7,11], and optical-spin-scanning radiometers and spectroradiometers [7,8]. Other studies used airborne or shore-based sensors, including UAV cameras and high-frequency (HF) coastal radars [6,9].…”

“…Other studies used airborne or shore-based sensors, including UAV cameras and high-frequency (HF) coastal radars [6,9]. Numerical tools and simulations were also considered in [3,4,[8][9][10], while in-situ information was exploited in [5,7,8].…”

“…In [3], a new method to improve the refocusing of moving vessels under high sea state conditions is proposed. Experimental results, performed on C-band Gaofen-3 SAR satellite imagery, showed that the adaptive time-frequency analysis based on the particle swarm optimization results in an increased and faster global convergence and better processing effectiveness and robustness.…”