Spaceborne low-frequency synthetic aperture radar with high resolution will be affected by ionospheric dispersion, which introduces a quadratic range phase error, leading to range defocusing. The dependence of the performance of contrast optimization (CO) autofocus and multilook registration (MLR) autofocus for dispersion compensation on the signal-to-clutter ratio (SCR) is analyzed. For SCR > 20 dB, two autofocus algorithms have similar performances, and CO is a little better. For SCR < 20 dB, CO, and MLR performance will be affected by initial quadratic phase error (QPE) and clutter size, respectively. When the initial QPE is less than 530°, and clutter size is at least 100 resolution cells, CO performance will be better than MLR. Taking 45° QPE as the threshold for accurate focusing, in the case of the single point object, the threshold SCR for CO to be effective is approximately between 12.5 and 18 dB, corresponding to initial QPE between 0° and 800°. For MLR, the threshold SCR is approximately between 17.5 and 18.5 dB, corresponding to clutter size between 100 and 500 resolution cells. For the case of multiple point objects, the threshold SCR values of both algorithms will decrease. Simulations based on scenes derived from PALSAR2 data demonstrate the effectiveness of the CO and MLR autofocus algorithm.

Speckle noise is an inherent problem of synthetic aperture radar (SAR) images, which not only seriously affects the acquisition of SAR image information, but also greatly reduces the efficiency of image segmentation and feature classification. Therefore, research on how to effectively suppress speckle noise while preserving SAR image content information as much as possible has received increasing attention. Based on the non-local idea of SAR image block-matching three-dimensional (SAR-BM3D) algorithm and the concept of sparse representation, a novel SAR image despeckling algorithm is proposed. The new algorithm uses K-means singular value decomposition (K-SVD) to learn the dictionary to distinguish valid information and speckle noise and constructs a block filter based on K-SVD for despeckling, so as to avoid strong point diffusion problem in SAR-BM3D and achieve better speckle noise suppression with stronger adaptability. The experimental results on real SAR images show that the proposed algorithm achieves better comprehensive effect of speckle noise suppression in terms of evaluation indicators and information preservation of SAR images compared with several existing algorithms.

Compared to low Earth orbit (LEO) synthetic aperture radar (SAR), geosynchronous (GEO) SAR has a larger coverage and shorter revisit period. However, due to its longer integration time it will be affected by ionospheric time-variant total electron content (TEC), which introduces a phase error into the SAR azimuth signal. Using U.S. total electron content (USTEC) data, TEC variation with time on GEO SAR track is analyzed. It is shown that quadratic phase error caused by time-variant TEC is main effect on image focusing compared to higher order errors. Therefore, contrast optimization autofocus (COA) algorithm can be used for compensation. The key steps of COA are given. Simulations based on scenes derived from PALSAR2 data demonstrate the effectiveness of COA.

Spaceborne P-band full-polarimetric wideband synthetic aperture radar (SAR) will be affected by ionospheric phase dispersion and polarimetric dispersion. An improved contrast optimization autofocus (COA) method using four polarization channel data is proposed to compensate for both phase dispersion and polarimetric dispersion. The basis and steps of the method are given. Its performance is analysed by typical target simulation under clutter background and compared with traditional COA method for single channel. The residual quadratic phase error (QPE) of single channel compensated by traditional method may exceed 45° focusing threshold, while the proposed method can reduce the error to less than 10°. Due to the lack of spaceborne P-band SAR data, we simulate the effect of ionosphere on P-band SAR based on ALOS2 PALSAR2 data and verify the proposed method. The simulation result shows the proposed method is effective and superior to traditional method.

Bistatic synthetic aperture radar (SAR) is a new type of SAR system which is capable of achieving multi‐angle target detection and flexible configuration. For spaceborne bistatic SAR, when operating at low frequencies, it is susceptible to the ionosphere. The ionospheric Faraday rotation effect will cause a rotation of polarisation plane of electromagnetic waves, leading to amplitude and phase errors between different polarisation channels of SAR. This effect can be compensated by estimating the Faraday rotation angle. Currently, Faraday rotation angle estimation methods for spaceborne SAR are all applicable to monostatic SAR. However, due to the different signal propagation paths between bistatic SAR and monostatic SAR, the Faraday rotation angle estimation method differs for bistatic SAR. This paper proposes a Faraday rotation angle estimation method for bistatic spaceborne SAR, which is applicable to the alternating bistatic mode. The effectiveness of the method is verified through simulation experiments and the performance of the method is analysed. Under different signal‐to‐noise ratios (SNR) and filtering window sizes, the estimation error range is 0.02°‐0.26°.