Marine Target Detection Using Dual-polarimetric SAR Imagery

In this study,we provide a summary of research advances in the field of maritime target detection using DP(dualpolarimetric)SAR(Synthetic Aperture Radar)imagery,accomplished during the European and China collaboration in the framework of the Dragon-4 program ID 32235.The main innovative contribution is twofold:(1)We addressed ship detection proposing an improved GP-PNF(Geometrical Perturbation-Polarimetric Notch Filter),termed as IGP-PNF,that is characterized by a new feature vector that includes three new scattering features;(2)We addressed oil platform detection by contrasting singlepolarization SAR methods with polarimetric ones in order to quantify the extra-benefit carried on polarimetric information.The proposed theoretical framework is tested against actual multi-polarization SAR data.In particular,ship detection methods are verified against a Sentinel-1 SAR scene where a large number of ships is present;while,oil platform detection is discussed using Terra SAR-X SAR data.Experimental analysis shows that:(1)The IGP-PNF method performs best in terms of clutter-to-target ratio;(2)Coherent polarimetric information significantly outperforms single-polarization SAR measurements in highlighting targets in challenging cases.

Evaluation of wave retrieval for Chinese Gaofen-3 synthetic aperture radar

The goal of this study was to investigate the performance of a spectral-transformation wave retrieval algorithm and confirm the accuracy of wave retrieval from C-band Chinese Gaofen-3(GF-3)Synthetic Aperture Radar(SAR)images.More than 200 GF-3 SAR images of the coastal China Sea and the Japan Sea for dates from January to July 2020 were acquired in the Quad-Polarization Strip(QPS)mode.The images had a swath of 30 km and a spatial resolution of 8 m pixel size.They were processed to retrieve Significant Wave Height(SWH),which is simulated from a numerical wave model called Simulating WAves Nearshore(SWAN).The first-guess spectrum is essential to the accuracy of Synthetic Aperture Radar(SAR)wave spectrum retrieval.Therefore,we proposed a wave retrieval scheme combining the theocratic-based Max Planck Institute Algorithm(MPI),a Semi-Parametric Retrieval Algorithm(SPRA),and the Parameterized First-guess Spectrum Method(PFSM),in which a full wave-number spectrum and a non-empirical ocean spectrum proposed by Elfouhaily are applied.The PFSM can be driven using the wind speed without calculating the dominant wave phase speed.Wind speeds were retrieved using a Vertical-Vertical(VV)polarized geophysical model function C-SARMOD2.The proposed algorithm was implemented for all collected SAR images.A comparison of SAR-derived wind speeds with European Center for Medium-Range Weather Forecasts(ECMWF)ERA-5 data showed a 1.95 m/s Root-Mean-Squared Error(RMSE).The comparison of retrieved SWH with SWAN-simulated results demonstrated a 0.47 m RMSE,which is less than the 0.68 m RMSE of SWH when using the PFSM algorithm.