The signal of spaceborne low-frequency full-polarization synthetic aperture radar (full-pol SAR) contains abundant ionospheric information. Phased Array L-band Synthetic Aperture Radar (PALSAR) working in the L-band has been verified as an emerging ionospheric sounding technology. Aiming for a future P-band SAR system, this paper investigates the ability of the P-band SAR system in ionospheric one-dimensional and two-dimensional detection. First, considering different systematic error levels, the total electron content (TEC) retrieval in L/P-band is studied by using three typical full-pol SAR data sets based on a circular polarization algorithm. Second, the TEC data retrieved by SAR are fused with the ionosonde, and the joint retrieval of ionospheric electron density is performed. Results show that the P-band TEC retrieval is approximately twice as accurate as the L-band retrieval under the same conditions, and possesses excellent robustness. In addition, the TEC obtained by L/P-band SAR can be used to correct the electron density of the topside on the ionosonde. Results also show that compared with the topside correction accuracy of L-band SAR, that of the P-band SAR is improved by more than 20%. SAR has natural high-resolution characteristics and the P-band signal contains more obvious ionospheric information than the L-band signal. Therefore, future spaceborne P-band SAR has many advantages in two-dimensional fine ionospheric observation and one-dimensional electron density retrieval.

Sidelobe reduction is a very primary task for synthetic aperture radar (SAR) images. Various methods have been proposed for broadside SAR, which can suppress the sidelobes effectively while maintaining high image resolution at the same time. Alternatively, squint SAR, especially highly squint SAR, has emerged as an important tool that provides more mobility and flexibility and has become a focus of recent research studies. One of the research challenges for squint SAR is how to resolve the severe range-azimuth coupling of echo signals. Unlike broadside SAR images, the range and azimuth sidelobes of the squint SAR images no longer locate on the principal axes with high probability. Thus the spatially variant apodization (SVA) filters could hardly get all the sidelobe information, and hence the sidelobe reduction process is not optimal. In this paper, we present an improved algorithm called double spatially variant apodization (D-SVA) for better sidelobe suppression. Satisfactory sidelobe reduction results are achieved with the proposed algorithm by comparing the squint SAR images to the broadside SAR images. Simulation results also demonstrate the reliability and efficiency of the proposed method.

Faraday rotation (FR) is a serious problem for spaceborne polarization SAR (PolSAR) systems at L and P bands. One way to solve the problem is to estimate the FR from PolSAR data for further compensation. Therefore, precise estimation of FR from PolSAR data not only determines the compensation effect of polarimetric systems but also benefits the ionospheric sounding with high spatial resolution. Among the factors that affect the FR estimation, system noise is a non-neglectable factor. Although average filtering (AF) has been widely used in previous works for noise removing it depends on large window size, and therefore reduces the spatial resolution of FR estimation. In order to realize optimal noise suppression with minimized resolution loss, the total variation (TV) denoising method is applied in this paper. By testing the Advanced Land Observing Satellite (ALOS) Phased Array L-band Synthetic Aperture Radar (PALSAR) full-pol datasets, TV and AF are compared and validated. Results using synthetic and real data show that, after TV denoising, the FR can be recovered with high spatial resolution and the noise level in estimated FR is reduced more effectively than that after AF.

Accurate and efficient moving target imaging is an important challenge for targets recognition in current synthetic aperture radar (SAR) combined with a ground moving target indication (GMTI) system. As the key but unknown parameter, the Doppler rates are estimated conventionally by searching any possible values for moving targets imaging. However, this conventional estimation method suffers from low accuracy or low efficiency due to the searching procedure. Focusing on these, we present a method to efficiently image the moving targets without the Doppler rate by Doppler delayed interferometry, and the imaged localization, which is parameterized pseudo-localization, is used to estimate the Doppler rate. In order to improve the estimation accuracy, an improved method based on the Newton method of approximation is proposed by exploiting the unused amplitude information. Compared with the conventional methods, the proposed improved method capable of high accuracy and low computation complexity simultaneously can meet the accurate and efficient requirements in the practical applications. Comparison simulations and real data processing results demonstrate the effectiveness of the proposed methods.