Synthetic Aperture Radar (SAR) fundamentally relies on matched filtering to enhance resolution and peak signal-to-noise ratio (PSNR) in active microwave remote sensing. However, the band-limited nature of echoes introduces significant sidelobes for strong scatterers. Therefore, the spectral windowing is required to suppress sidelobes after the echo has been focused with the matched filter. However, the windowing operation destroys the consistency between the magnitude spectrums of the matched filter and the echo, resulting in the PSNR not reaching the optimum and degrading the system performance. In this paper, based on the classical Hamming window, a Hamming frequency modulation (HFM) signal and the optimal azimuth antenna length considering the antenna weighting are proposed so that the amplitude of the two-dimensional spectrum of the echo is approximately equal to the square root of the Hamming window in both directions. By designing the corresponding matched filter, the spectral weighting is completed during the focusing operation, and the degradation of SAR image quality caused by the traditional windowing operation is solved. Theoretical analysis and experimental results show that the output SNR can be improved by a maximum of 5 dB without increasing the transmit power or reducing the resolution, which significantly improves the system efficiency.

Signum Coded Synthetic Aperture Radar (SC-SAR), also known as the one-bit SAR, significantly reduces the system complexity and data processing throughput by retaining only the sign information of the echo signal. However, this introduces severe quantization distortion, which degrades the image signal-to-noise ratio (SNR) and generates a succession of false targets in sparse scenes. The theoretical analysis reveals that the SNR degradation is primarily caused by the phase harmonic distortion, while the false targets are brought about by the amplitude intermodulation distortion. To address these issues, a nonlinear frequency-modulated (NLFM) signal with a Hamming-windowed amplitude spectrum, termed Hamming Frequency Modulation (HFM), is proposed as the transmitted waveform. The matched filter for the HFM signal integrates the pulse compression and the low-sidelobe weighting, optimizing the output peak signal-to-noise ratio (PSNR) to suppress the quantization noise. Concurrently, its nonlinear frequency modulation disrupts the periodicity of the intermodulation distortion, attenuating the peak power of false targets. Experiments utilizing both ideal point targets and real SAR raw data demonstrate that the proposed HFM method suppresses the quantization noise and the false target energy by approximately 0.8 dB and 4.8 dB, respectively, compared to the conventional Linear Frequency Modulation (LFM) signal, thereby enhancing SC-SAR image quality significantly.

The spaceborne synthetic aperture radar (SAR) is affected by ionospheric scintillation, which will lead to the degradation of the imaging quality. Considering the strong spatial variation and random characteristics of scintillation phase error (SPE) along the orbit, a compensation method of ionospheric scintillation effect on spaceborne SAR based on the multilayered phase screen model is proposed in this paper. Multiple reliable Faraday rotation (FR) are obtained by dividing the image into blocks based on fully polarimetric SAR data. The image is compensated using the error phase of multiple phase screens, which is estimated through the overlap between SPEs. Simulating with the ALOS-2 data, we quantitatively analyze the effectiveness of the proposed method and verify its better compensation performance compared to the traditional schemes.

When the hypersonic vehicle travel through the atmosphere, its surface will be covered by the plasma sheath, which will affect the radar imaging seriously, such as the inverse synthetic aperture radar (ISAR) and synthetic aperture radar (SAR). The dispersion effect of the space-time varying plasma sheath brings different phase errors to the range signals, resulting in the complex defocusing of the radar image. In this article, the error model of the range signal with the space-time varying dispersion effect is established, and the quadratic phase error (QPE) is focused on analysis. Then, an adaptive compensation of range space-time varying dispersion based on autofocus is proposed for the hypersonic vehicles coated by plasma sheath. Simulating with the typical parameters, the affected range signal is well focused after compensation. Meanwhile, the imaging quality is quantitatively evaluated with the promotion of the resolution, the peak side lobe ratio (PSLR) and the integral side lobe ratio (ISLR) from 0.45 m to 0.13 m, −0.32 dB to −13.26 dB and 4.55 dB to −10.03 dB, which proves the effectiveness of the proposed compensation method.

A method of simulating SAR images affected by the ionospheric scintillation based on the multilayered phase screen model is proposed in this paper. The phase error and polarization deflection caused by scintillation are considered during simulation, which is effective in both single and fully polarimetric modes. It can be used to simulate the impact of scintillation on SAR images, as well as the error compensation algorithm of SAR scintillation effect. Simulation results show that the scheme can simulate the scintillation effect in different ionospheric environments. The performance and main error sources of the proposed modeling method are finally analyzed.

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.

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.

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.

Range and azimuth ambiguities are contradictory in SAR system, which restrict the improvements of resolution and swath in satellite platform. Multichannel needs big and complex antenna. And it is proved that orthogonal transmitting signals cannot suppress range ambiguity. Thus high resolution and wide swath system is still a challenge in SAR development. In this paper, we design a novel range ambiguity suppressing method with single channel, which transmits amplitude modulation chirp signals. Through frequency filtering, the ambiguity images can be separated. A minimum mean square error algorithm is then proposed to restore the resolution robustly. Experiment based on Radatsat-1 echo shows that the proposed method can reduce the range ambiguity by 20 dB. Using this method, single-channel system can extend the swath width twice.

Because of the unprediction of the scene scattering characteristic and the finite quantization bits, saturated data always exists. Saturation phenomenon leads to a non-linear distortion and interferes to the recognition of the target so that it affects the image quality. Especially when the scene scattering characteristic largely varies, it can generate false targets and degrade signal-to-noise ratio (SNR). Compressed sensing (CS), a non-linear reconstructed algorithm, is that samples in sub-Nyquist rate is used to recover the sparse signal with few non-zero elements. This paper proposes the recovery method based on the nonlinear characteristic of CS to recover the saturated part of the raw data to the unsaturation state and ensure the unsaturated parts maintain the original state. Simulation results validate the proposed method.

Azimuth ambiguity may introduce false targets into synthetic aperture radar images, particularly likely in inshore and oceanic observation. To suppress the azimuth ambiguities for any acquisition mode, a new model is developed to describe the impact of spatially variant azimuth antenna pattern weighting on azimuth ambiguities. By accurately estimating the ratio of ambiguous to main zone energy based on the model, the proposed algorithm selects the subspectra with less ambiguous disturbance, and adopts extrapolation with weighted energy measure to obtain a full spectrum. Due to spectral selection and extrapolation, the novel algorithm achieves superior performance in azimuth ambiguity suppression and resolution preservation, which is compared with the classical algorithm, and validated by applying TerraSAR-X and RADARSAT-2 images.

The geosynchronous synthetic aperture radar (GEO SAR) can achieve staring observation for a long period, either to monitor the target area continuously or to improve the resolution due to its ultrahigh orbit. Taking into account of the state of art of antenna, a novel beam steering strategy of united control of satellite attitude and antenna beam is proposed and derived to implement staring at target area based on the characteristics of GEO SAR staring imaging. Besides, the visibility for a ground target is analyzed based on the basic methodology of staring observation. The feasibility of the proposed method is analyzed and verified by simulating a ground target imaging in different orbit positions.

The integration aperture time of Geosynchronous synthetic aperture radar (GEO SAR) is much longer than that of LEO SAR. Compared with LEO SAR, of which TEC is assumed to be constant, the time-varying ionospheric effects on GEO SAR imaging can't be ignored, and GEO SAR has the advantages of shorter repeat period and wider swath. Due to the wide swath of GEO SAR, it is necessary to take the effects of ionospheric temporal variance at different targets in a large scene into consideration. The letter analyzes the time-varying ionospheric effects on GEO SAR imaging. Finally, the USTEC data is used to analyze the time-varying effects at whole orbit of GEO SAR, and explore whether the effects are consistent at different targets in a large scene. Simulation results show GEO SAR azimuth imaging performance becomes deteriorated and defocused, and the effects are different at different positions in a large scene.

An innovative algorithm to suppress the strong azimuth ambiguity in single-look complex (SLC) synthetic aperture radar (SAR) images is presented. The basic idea is to construct a subspace with low ambiguous power and project the original image to the aforementioned subspace to suppress the azimuth ambiguity by the minimum mean square error estimation (MMSE). Compared with most traditional approaches, the proposed one is suitable for any distributed scene and any acquisition mode. Moreover, the proposed approach seems to keep the resolution in a reasonable level and not rely on the system parameters extremely. Raw data from the TerraSAR-X have been used to validate the effect of the azimuth ambiguity suppression by using the new approach.

In this paper, a novel multi-baseline phase unwrapping approach is proposed based on maximum likelihood estimation (MLE) method. Topography phase gradient is acquired by fusing multi-baseline InSAR data. It is convenient to obtain unwrapped phase by using gradient integral. Since search interval is critical for the uniqueness and accuracy of solution, low-precision digital elevation model (DEM) is imported to improve the estimation interval. Simulations corroborate the validity of maximum likelihood unwrapped phase estimation method proposed in our work.

In space-borne azimuth multi-channel SAR, the antenna phase center spacing should be measured precisely to obtain the reconstruction filters. In this paper, a data-based onboard estimation method of antenna phase center spacing in spaceborne multi-channel SAR system is proposed. Firstly, the principle of data-based onboard estimation is presented, then the estimation method in details is described step-by-step. Finally, simulations are carried out, with two influence factors, SCR and focusing accuracy, to demonstrate the validity of the proposed estimation method.

A novel SAR imaging approach has been exposed in this paper. It is based on CS theory which aims at getting low sidelobes image with Shannon-Nyquist samplings. Deviated from classical CS-imaging methods in large squint mode, this new method does RCMC on the echo first through nonlinear chirp scaling, and then carries out CS compression in both range and azimuth. This approach depresses the mistakes of RCMC brought by CS algorithm, and relieves the calculating pressures.

The traditional radar system needs large bandwidth, and the increasing number of channels brings huge amount of data. These data can easily overflow the memory of the sensor or the bandwidth of the signal which transferred to the ground station. In order to solve this problem, a new method of acquiring Synthetic Aperture Radar (SAR) raw data and compressing pulse which based on the theory of Compressive Sensing (CS) theory are presented. In this method, CS SAR imaging is affected by noise, sampling rate and the sparsity of signal. Furthermore, Donoho-Tanner phase transition diagram is applied to show the performance of CS pulse compression. Engineers can intuitively find the scene and the sampling rate which is suitable for using compressed sensing synthetic aperture radar pulse compression.