Doppler Centroid Analysis (DCA) technique is one of the major techniques that do permit a direct retrieval of ocean surface velocity from synthetic aperture radar (SAR) data. However, azimuth ambiguities in the SAR images severely restrict the capability of DCA technique to obtain accurate ocean surface Doppler velocities. Therefore, it is necessary to investigate how the azimuth ambiguities impact the Doppler velocity estimation performance and to evaluate how significant the impact is. In this paper, a model for ocean surface Doppler velocity estimation affected by azimuth ambiguities is developed resorting to jointly circular Gaussian processes, and its statistic is derived. The impact of azimuth ambiguities on Doppler velocity estimation performance in terms of Doppler centroid estimation bias and the standard deviation of Doppler centroid estimates is analyzed. The theoretical results are validated through simulation and Doppler velocities retrieved from Chinese Gaofen-3 (GF-3) SAR Doppler centroid estimates affected by azimuth ambiguities. This study will help researchers better understand the impact of azimuth ambiguities on Doppler velocity estimation, and will provide a theoretical reference for subsequent research on how to reduce the impact of azimuth ambiguities more effectively.

Synthetic aperture radar (SAR) is widely used in the field of ocean remote sensing. However, SAR images are usually affected by sea spikes, which appear as strong echo and azimuth defocus characteristics. The texture features of ocean waves in SAR images are submerged by sea spikes, making them weak or even invisible. This seriously affects the further applications of SAR technology in ocean remote sensing. To address this issue, an airborne SAR imaging algorithm for ocean waves oriented to sea spike suppression is proposed in this paper. The non-stationary characteristics of sea spikes are taken into account in the proposed algorithm. The SAR echo data is transformed into the time–frequency domain by short-time Fourier transform (STFT). And the echo signals of sea spikes are suppressed in the time–frequency domain. Then, the ocean waves are imaged in focus by applying focus settings. In order to verify the effectiveness of the proposed algorithm, airborne SAR data was processed using the proposed algorithm, including SAR data with completely invisible waves and other data with weakly visible waves under sea spike influence. Through analyzing the ocean wave spectrum and imaging quality, it is confirmed that the proposed algorithm can significantly suppress sea spikes and improve the texture features of ocean waves in SAR images.