Recent studies have shown that pseudo labels can contribute to unsupervised domain adaptation (UDA) for speaker verification. Inspired by the self-training strategies that use an existing classifier to label the unlabeled data for retraining, we propose a cluster-guided UDA framework that labels the target domain data by clustering and combines the labeled source domain data and pseudo-labeled target domain data to train a speaker embedding network. To improve the cluster quality, we train a speaker embedding network dedicated for clustering by minimizing the contrastive center loss. The goal is to reduce the distance between an embedding and its assigned cluster center while enlarging the distance between the embedding and the other cluster centers. Using VoxCeleb2 as the source domain and CN-Celeb1 as the target domain, we demonstrate that the proposed method can achieve an equal error rate (EER) of 8.10% on the CN-Celeb1 evaluation set without using any labels from the target domain. This result outperforms the supervised baseline by 39.6% and is the state-of-the-art UDA performance on this corpus.

According to the minimum antenna area constraint, synthetic aperture radar (SAR) systems require a low-pulse repetition frequency (PRF) to image the wide swaths in ocean surface monitoring scenarios. However, the low PRF that is lower than the Doppler bandwidth will cause azimuth ambiguities. This letter proposes a novel method of mitigating azimuth ambiguities when using an undersampled SAR system for ship detection over the open sea. In this letter, the concept of range subspectra is adopted to misregister the azimuth ambiguity signals. In addition, a change detection method that uses a principal component analysis and k-means clustering is adopted to detect differences in the azimuth ambiguities between two range subspectra images in which the azimuth ambiguities are misregistered. By compensating for the ambiguities in the corresponding image, the ambiguities can be mitigated. This method is only appropriate for bright targets over dark backgrounds in which residual energy loss occurs for useful signals. Both simulated and real data processing results have validated the effectiveness of the proposed method and show that it is feasible for maritime surveillance.

For the next generation of spaceborne synthetic aperture radar remote sensing satellites, high resolution and wide coverage are important goals. Digital beam-forming (DBF) with multichannels in elevation is a great and promising candidate to cover wide swaths. In this letter, we focus on onboard digital processing for DBF in elevation. It is generally believed that the onboard processing for DBF is challenging due to the limitations in flight-hardware availability, the heavy computational load, and the high resource occupation. In order to reduce the computational load of DBF, one novel processing scheme is proposed. This proposed scheme performs a modified time-variant weighting on a real intermediate frequency signal of each subchannel, and the weighted signals of all channels are summed to two real data streams. To obtain a correct DBF output, a modified quadrature demodulation process is presented. Then, the scheme is extended to apply FIR filters for overcoming pulse extension loss. Furthermore, improved time-variant weighting coefficients are derived to compensate the phase errors brought by the FIR filtering process. Compared with the present processing flow, the proposed scheme could significantly reduce the computational load and resource occupation.

The next generation of spaceborne synthetic aperture radar (SAR) remote sensing systems will emphasize on high-resolution and wide-coverage imaging. For these design goals, digital beamforming (DBF) in elevation is a promising candidate. DBF-SAR can provide global monitoring capacity for the continuous observation of a highly dynamic and rapidly changing world with high spatial resolution and short repeat intervals. A spaceborne experiment regarding a real complex scene and real spaceborne wave propagation channel effects remains a necessary step to complete the experimental verification of this advanced technique. Fortunately, the spaceborne-stationary bistatic configuration offers a potential chance to validate the advanced technique. The aforementioned experiment can be considered as a test bed for the development and implementation of DBF radar techniques applicable to Earth observation science and planetary measurements. The DBF experiment based on spaceborne-stationary bistatic configuration with TerraSAR-X as an illuminator has been successfully conducted in June 2013 by the Department of Space Microwave Remote Sensing System, Institute of Electronics, Chinese Academy of Sciences.

This paper addresses some important aspects for the spaceborne/stationary bistatic synthetic aperture radar (SAR) (SS-BiSAR) imaging with the transmitter, TerraSAR-X, operated in staring spotlight (ST) mode. With the large integration time reaching 7.5 s and the azimuth steering span reaching ± 2.2°, several significant effects occur, including troposphere delay, precision phase and time synchronization, the curved orbit effect, azimuth spectrum aliasing problem, and efficient frequency domain focusing algorithm. To circumvent the main effects, corresponding solutions are proposed, including a precise synchronization strategy with troposphere delay correction based on the direct signal from the transmitter and a modified and integrative bistatic polar format algorithm (PFA). This paper covers the theoretical development, implementation, and analysis of the SS-BiSAR PFA based on 2-D fast Gaussian gridding nonuniform fast Fourier transform with wavefront curvature correction. Furthermore, the high-resolution ST-mode SS-BiSAR image processed by the proposed algorithm is acquired, and the differences of scattering behaviors between monostatic and bistatic SAR images are analyzed in detail.