Synthetic aperture radar (SAR), with its all-weather and day/night capabilities, plays an important role in Earth observation. Traditionally, SAR satellites fly in low Earth orbits, which can result in fast Doppler accumulation but long revisiting intervals. Although increasing the number of satellites extends the observation coverage significantly, a complex constellation leads to unacceptable cost. The geosynchronous SAR system realizes sustained observations for a specific area; however, the long integral time results in the obvious defocusing of objects, even in micro-motion. To achieve a fast response and a short revisiting time with high accuracy and low costs, a constellation of imaging radar satellites called Constellation of Geostationary and Low Earth Orbit SAR (ConGaLSAR) is proposed in this letter; ConGaLSAR employs a novel transponding mode (MirrorSAR) to economically achieve efficient revisiting and phase/time synchronizations. In this system, the ground echoes are amplified by the low-orbit satellites and then retransmitted back to the illuminating system for sampling and downlinking. In view of the specific geometry of the system, the sensitivity, resolutions, and effective observing area are discussed and precisely defined. Based on the theoretical analyses, a typical case of ConGaLSAR, consisting of one geostationary orbit illuminator and 24 low-orbit transponders, can achieve a 92.4-min revisiting interval and 3-m resolution for the Pacific Ocean.

ConGalSAR is a novel SAR constellation that has an outstanding performance of revisit and economy. In the system, with the MirrorSAR technology, one geostationary illuminator and several economical low earth orbit transponders work together to achieve a short revisiting interval. Because of the huge difference in the distances of transmitting and receiving, the spatial weighting of the antenna patterns on the ground is quite different, which leads to the deterioration of ambiguity to signal ratio. The multiphase center and digital beamforming antennas can suppress the ambiguity energy; however, they are too expensive and heavy to be equipped on the dozens of transponding nanosatellites. In this article, a comprehensive ambiguity suppression method, including the reflector antenna design and signal processing, is proposed to reduce the ambiguity ratio, which well solves the ambiguity problem under the condition of the low manufacturing costs and lightweight transponders. In terms of the hardware design, the multifeed reflector antenna is applied to the transponder, in which the feeds receive an echo together. Based on this, the low sidelobes beamforming is achieved to well suppress the ambiguity. Meanwhile, the amplitude-modulated chirps are also used here aiming at the residual ambiguity in the large dynamic scene. Through spectral selection and extrapolation processing, range ambiguity energy is suppressed more while preserving the resolution. The digital simulations show that the comprehensive method can realize −20 dB ambiguity ratios at least, which conforms to the ambiguity-to-signal ratio design of ConGaLSAR.

Digital storage and transmission are common processes in modern synthetic aperture radar systems; thus, analog-to-digital converters are indispensable. Such processes can lead to two types of error: quantization (or granular) error and saturation (or clipping) error, which cause sampling noise, and radiometric and harmonic distortions in final images. Traditionally, reasonable choices of the gain and the number of quantization bits by the analog-to-digital converter based on the echo distribution can effectively reduce these errors. However, establishing the gain control repository of a synthetic aperture radar mission is a long process. In addition, if the dynamic range of the backscattering coefficient is extremely large or if unexpected strong targets appear in a scene, then harmonics occur in the echo, which turns the variable gain amplifier into chaos based on statistic and, inevitably, results in saturation in the raw data. Once raw data saturation occurs, the SAR system can conventionally adjust only the analog-to-digital converter in the next observation, thus reducing timeliness. Power loss compensation based on a statistical model and saturation (clipping) factor on a large-scale could compensate for the energy loss in images; however, detail interference, such as harmonic distortion, cannot be effectively suppressed, which will lead to false targets in the focused data. To address this particular problem, a novel anti-saturation method for large dynamic range scenes is proposed in this paper. The log-normal distribution is used in this article to describe dynamic range scenes with strong isolated targets, which mainly cause receiver saturation. Using the statistical distribution of complex scenes as a priori information, a maximum a posteriori estimation algorithm is proposed to simultaneously compensate for the saturated values in the raw data and retain the non-saturated values. Thus, the details of the weak background are well preserved, and the isolated strong targets with sparsity are reconstructed perfectly. With Monte Carlo simulation, the proposed method can improve the radiometric accuracy by 5 to 10 dB and effectively suppress the energy of false targets. Based on TerraSAR-X, ALOS-2, and Radarsat-1 synthetic aperture radar data, the effectiveness and robustness of the proposed method are also verified by simulations.

A novel synthetic aperture radar (SAR) constellation called Constellation of Geostationary and Low Earth Orbit SAR (ConGaLSAR), including one geostationary illuminator and several low Earth orbit CubeSat transponders, was previously proposed with outstanding revisiting. The MirrorSAR technology used in transponder significantly simplifies the satellite; however, it brings complexity to the imaging geometry, resulting in failures of the traditional bistatic imaging method. The introduction of probe signals achieves accurate measurement of the additional transponding distance. In this article, a three-step imaging method is proposed to realize accurate imaging processing aiming at the transponding mechanism and wide swath observation: 1) linear time variation for range cell migration grid correction; 2) second range compression for the additional squint angle introduced in the previous step; and 3) range cell migration correction in the range-Doppler domain for nonuniform cell grid caused by bistatic SAR (BiSAR). Digital simulations and real BiSAR data experiments are conducted to verify the effectiveness and accuracy of the algorithm. Moreover, the influence of the elevation is analyzed, confirming its excellent tolerance of elevation errors under the condition of a 3-m resolution and a 40-km swath width, which conforms to the system design of ConGaLSAR.

Radar sounding plays an irreplaceable role in polar ice sheets research. Over the past 60 years, vehicle-borne and airborne systems have provided large amounts of topographic data on ice sheets. However, due to the limitations of atrocious weather in the polar regions and the platform operating distance, a large blind zone of observations still remains. Spaceborne radar systems can realize efficient observations of the Earth's surface due to the wide swath of satellites and the penetration of clouds and rain by microwaves. However, existing remote sensing satellites still cannot observe ice beds, which are subject to severe radio attenuation and complex signal propagation in ice. In this article, a spaceborne multistatic radar sounding system named the BingSat-Tomographic Observation of Polar Ice Sheets (TOPISs) is proposed to achieve high resolution and stereoscopic observation. Over the polar regions, the satellite formation design via passive CubeSats with dipole antennas forms a large cross-track baseline. Based on that, cross-track resolution improvement, ice attenuation compensation, and surface clutter suppression are realized simultaneously. Single-input and multiple-output mode and MirrorSAR technology are employed to reduce the manufacturing cost and realize synchronization. With a high transmitting power and antenna gain, BingSat-TOPIS can penetrate several kilometers of ice sheets.

The L-band geosynchronous synthetic aperture radar (GEO-SAR) has been widely praised for its advantages of short revisit time, wide coverage and stable backscattering information acquisition. However, due to the ultra-long integrated time, the echo will be affected by the time-variant background ionosphere, leading in particular to defocusing in the azimuth direction. Existing compensation methods suitable for low Earth orbit SAR (LEO-SAR) are based on the SAR image or the semi-focused image at the ionospheric phase screen, assuming that the ionosphere is time-frozen for a short integrated period; thus, accurate reconstruction of the time-variant characteristics for the ionosphere in GEO-SAR cannot be achieved. In this paper, a compensation method of background ionospheric effects on L-band GEO-SAR with fully polarimetric data is proposed. Considering the continuous variation of the ionosphere within the synthetic aperture, a decompression processing is proposed to reconstruct the echo by recovering the temporal sampling according to the imaging geometry. By virtue of the Faraday rotation angle, the time-variant total electron content (TEC) is accurately estimated with the reconstructed echo. Based on the established error model, the ionospheric effects are well compensated with the estimated TEC. Simulations with the real SAR data from ALOS-2 and the measured time-variant TEC from USTEC validate the effectiveness and performance of the proposed method. The impacts from thermal noise and polarimetric calibration error are also quantitatively analyzed. From this, the error thresholds are given to guarantee compensation accuracy, namely 18.96 dB for SNR, −15.63 dB for crosstalk and −1.02 dB to 0.31 dB for the amplitude of the channel imbalance, and the argument of the channel imbalance is suggested to be maintained as close to zero as possible.