Oceanic front extraction from synthetic aperture radar (SAR) images is of great significance to the study of marine ecosystems. At present, the methods for oceanic front extraction are usually based on SAR intensity images, which treat oceanic fronts as edge-like features in the SAR images. However, affected by radar parameters and sea state, sometimes, oceanic front signatures may not be clearly visible in the SAR intensity images. Therefore, existing methods are limited. In order to solve this problem, a method combining intensity and Doppler information for oceanic front extraction is proposed. Using Chinese Gaofen-3 single-look complex (SLC) data, three cases where oceanic front signatures are clearly visible, partially visible and extremely weak in the SAR intensity images are investigated, which demonstrate how the Doppler velocity gradient across a front can be leveraged to enhance the extraction of oceanic fronts from SAR data. The results show that the Doppler data, as supplementary information, not only can complement the oceanic fronts extracted from SAR intensity images, but also can be used as a reference for the oceanic fronts extracted from SAR intensity images.

Ocean waves are the richest texture on the sea surface, from which valuable information can be inversed. In general, the Synthetic Aperture Radar (SAR) images of surface waves will inevitably be distorted due to the intricate motion of surface waves. However, commonly used imaging algorithms do not take the motion of surface waves into consideration. Therefore, surface waves on the obtained SAR images are rather blurred. To solve this problem, an airborne SAR imaging algorithm for ocean waves based on optimum focus setting is proposed in this paper. Firstly, in order to obtain the real azimuth phase speed of dominant wave, the geometric and scanning distortion in the blurred SAR image is calibrated. Subsequently, according to the SAR integration time and wavelength of the dominant wave, a proper focus setting variation section is selected. Afterwards, all the focus settings in this variation section are used to refocus the image, which are then compared to decide the optimum focus setting for dominant wave. Finally, by redesigning the azimuth matched filter using this optimum focus setting, a well-focused SAR image for the dominant wave can be obtained. The proposed algorithm is applied to both simulation and field data, and SAR images of surface waves are obtained. Furthermore, the obtained images are compared with those obtained with a zero-focus setting. The comparison shows that the focus of surface waves is significantly improved, which verifies the effectiveness of the proposed algorithm. Finally, how to choose the appropriate focus setting variation section under different parameters and the applicability of the algorithm are analyzed.

The Kuroshio is the strongest warm current in the western North Pacific, which plays a crucial role in climate and human activities. In terms of this, the accurate acquisition of ocean surface current velocity and direction in the Kuroshio region is of great research value. Gaofen-3 synthetic aperture radar (SAR) provides data support for the study of ocean surface current measurements in the Kuroshio region, but no relevant experimental result has been published yet. In this paper, four available stripmap mode SARs’ data acquired by Gaofen-3 in the Kuroshio region are used for measuring the ocean surface current field. In general, the Doppler centroid anomaly (DCA) estimation is a common method to infer ocean surface currents from single-antenna stripmap data, but only the radial velocity component can be retrieved. In order to measure current vectors, a novel method combining the sub-aperture processing and the least squares (LS) technology is suggested and demonstrated by applying to the Gaofen-3 SAR data processing. The experiment’s results agree well with model-derived ocean current data, indicating that the Gaofen-3 SAR has the capability to accurately retrieve the ocean surface current field in the Kuroshio region and motivate further research by providing more data.

In synthetic aperture radar (SAR) ocean remote sensing, it is very difficult to estimate an accurate azimuth antenna pattern (AAP) from low-scattering SAR images without strong scattering targets. Therefore, an azimuth antenna pattern estimation method based on Doppler spectrum in SAR ocean images is proposed in this paper. In order to preserve the complete AAP information, an azimuth unweighted matched filter is used to re-image the SAR raw data in the proposed method. Then, the shape factor of AAP can be obtained by linear statistics of the relationship between Doppler center and edge frequency spectrum in Doppler spectrum of each distance gate. In addition, the impact of the uniformity and signal-to-noise ratio of SAR ocean images on the estimation results are also analyzed by simulation. Finally, the feasibility of proposed method is verified by data from ERS-2 (European remote sensing satellite (ERS) was the European Space Agency’s first Earth-observing satellite). Experimental results show that the AAP estimated by proposed method has a good estimation result.

In synthetic aperture radar (SAR) images, azimuth ambiguity is one of the important factors that affect image quality. Generally, the azimuth ambiguity-to-signal ratio (AASR) is a measure of the azimuth ambiguity of SAR images. For the low signal-to-noise ratio (SNR) ocean areas, it is difficult to accurately estimate the local AASR using traditional estimation algorithms. In order to solve this problem, a local AASR estimation method based on the Doppler power spectrum in SAR images is proposed in this paper by analyzing the composition of the local Doppler spectrum of SAR images. The method not only has higher estimation accuracy under low SNR, but also overcomes the limitations of traditional algorithms on SAR images when estimating AASR. The feasibility and accuracy of the proposed method are verified by simulation experiments and spaceborne SAR data.

Synthetic Aperture Radar (SAR) is widely applied to the field of ocean remote sensing. Clear SAR images are the basis for ocean information acquisitions, such as parameter retrieval of ocean waves and wind field inversion of the ocean surface. However, the SAR ocean images are usually blurred, which seriously affects the acquisition of ocean information. The reasons for the wave blurring in SAR images mainly include the following two aspects. One is that when SAR observes the ocean, the motion of ocean waves will have a greater impact on imaging quality. The other is that the ocean’s surface is seriously decorrelated within the integration time. In order to obtain clear SAR images of ocean waves, a SAR imaging algorithm of ocean waves based on the optimum subaperture is proposed, aiming at the above two aspects. The optimum focus setting of the ocean waves is calculated, drawing support from the azimuth phase velocity of the dominant wave. The optimum subaperture is further calculated according to the proposed new evaluation, namely, F. Finally, according to the optimum focus setting and the optimum subaperture, the dominant wave is refocused, and a clear SAR image of the dominant wave can be obtained. The proposed algorithm was applied to airborne L-band and P-band SAR data. Furthermore, the proposed algorithm was compared with present methods, and the results sufficiently demonstrated the effectiveness and superiority of the proposed algorithm.