In satellite synthetic aperture positioning (SAP), the curvature of the Earth’s surface and the curved orbit lead to nonlinear and asymmetric instantaneous Doppler frequencies, especially when dealing with signals of very long durations. This phenomenon significantly affects the accuracy of center frequency estimation and radiating source positioning. This study presents an ultra-high-resolution positioning algorithm designed to process ultra-long-duration data collected by a single satellite. Initially, a method for estimating the zero-Doppler moment based on sub-aperture chirp rates is proposed to obtain an unbiased estimate of the radiation source’s center frequency. Subsequently, a nonlinear instantaneous Doppler compensation method is proposed, utilizing the estimated center frequency and chirp rates to enhance the coherence of the long-duration data. Furthermore, a long coherent positioning is suggested to generate an ultra-high-resolution positioning image. Ultimately, the efficacy of the proposed algorithm is validated through simulations and acquired data.

Spaceborne synthetic aperture radar (SAR) can operate at various modes, including stripmap mode, spotlight mode, sliding spotlight mode, and Terrain observation by progressive scans (TOPS) mode. These four imaging modes can be regarded as unified, differing in rotation-center ranges. To uniformly focus the data of these four imaging modes in real-time, this article proposes a real-time unified focusing algorithm (RT-UFA) for the multi-mode SAR via azimuth sub-aperture complex-valued image combining and scaling. The imaging processing can be performed while the data are being recorded. In the first stage of imaging, sub-aperture complex-valued images with relative low-resolution can be obtained by the cascade of the extended chirp scaling (ECS) and azimuth dechirp. Then, these complex-valued images are coherently combined by shifting the integer number of pixels, and thus the full-resolution image of all the recorded data can be obtained. The azimuth scaling and the pixels shifting in the RT-UFA are analyzed in detail. Simulation and SAR data results are presented to validate the analysis and RT-UFA.

Multiple azimuth channels (MACs) synthetic aperture radar (SAR) can theoretically achieve high azimuth resolution and wide swath (HRWS). Nevertheless, in practice, channel mismatch will lead to ghost or azimuth ambiguities, which will degrade the imaging quality. This article proposes a novel idea for estimating the channel mismatch of MACs SAR in the image domain. First, we found that the degree of freedom (DOF) of MACs signals doubles after signal reconstruction and imaging. As a result, when the channel number is not great enough, the subspace method for error estimation is unable to be implemented. To deal with this problem, we introduce a DOF compression method based on spectral filtering. This method can decrease the image-domain DOF. Finally, an image-domain subspace method is proposed to estimate the channel phase error, using the focused data and selecting the high SNR region of SAR images. The proposed method has advantages for the channel phase error estimation. Simulated space-borne MACs SAR data and real measured airborne SAR data are processed to demonstrate the effectiveness of the proposed method.

High resolution and wide-swath imaging always suffer channel errors of the multiple azimuth channels (MACs) synthesis aperture radar (SAR). This article presents an image-domain channel error estimation algorithm based on image subspace least square (ISP-LS) method and a postimaging reconstruction algorithm for MACs SAR. The proposed method mainly consists of three parts: first, preprocessing and SAR imaging; second, the ISP-LS-based channel error estimation and calibration algorithm; third, postimaging reconstruction and ambiguity suppression. The channel phase and baseline errors are joint-estimated based on image subspace after SAR imaging, providing advantages that the higher signal-to-noise ratio (SNR) regions SAR images and the subspace method can be used to achieve a more accurate estimate with a relatively low computational load. We also propose a postimaging reconstruction method for ambiguity suppression, which can realize imaging each channel data and then combining the multichannel SAR images. Simulated and acquired airborne SAR data are processed to demonstrate the effectiveness of the proposed method.

This article presents a fast back-projection (BP) algorithm based on subaperture (SA) image coherent combination in a downsampled Cartesian coordinate grid for high squint diving terrain observation by progressive scans (HSD-TOPS) synthetic aperture radar (SAR) ground plane imaging. A two-step spectrum compression (SC) method is proposed to coherently combine the aliasing SA images by exploiting the relationship between the wavenumber and the image frequency. The first-step SC is introduced to align the spectrum support region centers. The second-step SC effectively corrects the space-variant spectrum inclination. The proposed algorithm does not need interpolation in the process of image combination, which ensures the accuracy and the efficiency of the algorithm. Furthermore, the SC method is well-modified to suppress the sidelobes of the focused image. Simulation and measured data processing verify the effectiveness of the proposed method.

The small satellite SAR has received increasing attention due to its flexibility and low cost. But limited by the data transmission technology, real-time transmission of a large amount of raw data generated by the spaceborne spotlight SAR can hardly be achieved. Meanwhile, the azimuth bandwidth of the spotlight mode is larger than the PRF, resulting in aliasing of the azimuth spectrum. Based on these, this paper proposes a real-time scheme for small satellite SAR with spotlight mode. The method can solve the problem of data transmission and eliminate spectrum overlap in Doppler domain by means of sub-aperture processing. The modified range migration algorithm (RMA) is used to perform range compression and range cell migration compensation (RCMC) on sub-aperture data. Then dechirp in the azimuth time domain is applied to obtain the low-resolution complex image focused in the range time-azimuth frequency domain. Finally, all theected onto a grid image with azimuth interval matching the azimuth full-resolution to complete image fusion.

In very high resolution spaceborne-squinted sliding spotlight synthetic aperture radar, the traditional imaging algorithms based on the equivalent squint range model (ESRM) cannot be applied, because the ESRM model is inaccurate in this case. For this problem, this paper proposes a squint equivalent acceleration range model to precisely take into account the spaceborne-squinted curved orbit. Then a full-aperture squint-imaging algorithm is proposed based on this new range model, which can handle the azimuth variation of the equivalent velocity and the range variation of the 2-D frequency spectrum. The results of the simulation validate the effectiveness of new range model and imaging algorithm.

Signal bandwidth and integration time are two significant parameters of a geosynchronous synthetic aperture radar (SAR) sensor. They directly determine the resolution characteristic of SAR imagery. Because their contributions to the ground impulse response width (IRW) curve (consists of −3-dB resolutions in every direction) are severely coupled, an analytical extraction method of the ground IRW curve is studied to analyze the coupling characteristic. Due to the coupling, the IRW curve is generally spatially variant and, thus, can degrade the quality of SAR imagery. To minimize the variation, the two parameters are optimized. However, the optimized signal bandwidth is found to be satellite position varied, which complicates the system design. To solve this problem, a parameter optimization model is built to obtain one optimal signal bandwidth as well as to decrease the variation.

In spaceborne synthetic aperture radar, the sliding spotlight mode can acquire high resolution and large azimuth scene size simultaneously. However, when the resolution is very high and the azimuth scene size is large, the traditional hyperbolic range model (HRM) is inaccurate and the variation of the equivalent velocity in azimuth dimension cannot be ignored. Thus, the traditional imaging algorithms based on HRM are no longer available. For this problem, this paper proposes an equivalent acceleration range model, which can precisely take into account the spaceborne curved orbit. Then, velocity scaling algorithm based on this new range model is proposed to meet the needs of very high resolution and large azimuth scene size. The results of the simulation validate the effectiveness of the new range model and the imaging algorithm.

Due to the effects of the earth's rotation and the satellite's elliptical orbit, the Doppler centroid varies along the orbit in geosynchronous earth orbit synthetic aperture radar (GEO SAR). With an ultrahigh orbit height, the beam may illuminate outside the earth surface with a rotation angle large than 9 degrees. Therefore, the usual attitude steering methods to minimize the Doppler centroid in low earth orbit SAR (LEO SAR) may not be suitable for GEO SAR. Considering the above two effects of GEO SAR and the beam illuminating restriction, a beam determination method to minimize Doppler centroid in GEO SAR is proposed in this paper. Guaranteeing that the beam not illuminate outside the earth surface, the proposed method can drastically decrease the Doppler centroid and the equivalent squint angle.

Airborne SAR imaging processing needs to estimate motion error to compensate non-ideal trajectory. In this paper, a subaperture imaging scheme for wide azimuth beam airborne SAR systems is proposed. First, the motion error is estimated from the subaperture data and the modified range migration algorithm is applied to obtain the coarse focused image, whose azimuth resolution corresponds to the subaperture Doppler bandwidth. The subaperture image is then projected into a fine grid image, whose coordinates is defined by the imaging geometry. As the subaperture data stream is coming, the azimuth resolution of the grid image will become higher and higher. Finally, the fine image with the azimuth resolution corresponding to the full aperture data can be obtained. Since the motion error estimation is based on the sub-aperture data, the imaging processing is suitable for real-time SAR imaging.

For the squinted terrain observation by progressive scans (TOPS) imaging mode, three problems need to be considered: azimuth spectrum aliasing, serious range-azimuth coupling, and azimuth time aliasing after range cell migration correction (RCMC). For these problems, a subaperture imaging algorithm based on the modified range migration algorithm (RMA) combined with spectral analysis (SPECAN) is proposed in this letter. Echo data are properly divided into subapertues so that the 2-D spectrum of each subaperture without aliasing can be obtained; then, the modified RMA is used to perform RCMC; finally, the signal is focused in the Doppler domain by SPECAN and deramping after subaperture recombination. Both simulated and real SAR data in the squinted TOPS mode are used to validate the proposed algorithm.

A space-variant chirp scaling algorithm based on the range cell migration (RCM) equalization and azimuth subband synthesis has been studied to process simulated geosynchronous synthetic aperture radar (GEO-SAR) data. The acceptable order of terms in polynomials for the slant range models in the RCM correction and phase error compensation, division of subband, and suppression of grating lobes of the subbands was investigated. Qualitatively and quantitatively, the method was able to focus simulated GEO-SAR signals well. Finally, the constraint on the spatial extent of azimuth and range dimensions using the algorithm was assessed.

Many imaging algorithms for different modes, such as, stripmap synthetic aperture radar (SAR), spotlight SAR, sliding spotlight SAR, and terrain observation by progressive scans (TOPS) SAR, of SAR have been studied. This paper is to obtain a unified focusing algorithm (UFA) for these SAR modes based on fractional Fourier transform. By defining the rotation-center range, the stripmap SAR and spotlight SAR can be treated as special cases of sliding spotlight SAR or TOPS SAR. Then, a parameterized focusing algorithm determined by the rotation-center range is presented. Data of each mode can be focused by utilizing UFA and selecting parameters or rotation angles. Some application aspects of UFA are also analyzed. Simulation and real data results are presented to validate the analysis and the proposed method.