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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) SAR. This paper presents an image-domain channel error estimation algorithm based on image subspace least square (ISPLS) method, and a post-imaging reconstruction algorithm for MACs SAR. The proposed method mainly consists of three parts: firstly, preprocessing and SAR imaging; secondly, the ISP-LSbased channel error estimation and calibration algorithm; thirdly, post-imaging 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 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 post-imaging 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.

Geosynchronous-earth-orbit (GEO) SAR provides excellent continuous observing capability and large swath. How-ever, the extremely long synthetic aperture time, the curved orbit and the nonplanar ground surface cause serious spatial variance in the GEO SAR signal. In this paper, a novel fast Cartesian Back Projection (BP) algorithm based on sub-aperture imaging on ground and multi-stage fusion is proposed for accurately and efficiently imaging of GEO SAR. The imaging grids are arranged on the ground surface to avoid the azimuth defocusing caused by flat-ground-approximation. Then, a new two-step spectrum compression method is derived to solve the spectrum aliasing of sub-aperture images. And a multi-stage image fusion method is adopted to combine all the sub-aperture images with high efficiency. The computational complexity and the approximation of the proposed algorithm are also discussed. Simulation results verify the effectiveness of the proposed algorithm.

In the existing time-domain autofocus algorithms, the azimuth deramping operation will change the azimuth-independent phase into the azimuth-dependent phase, which may greatly reduce the accuracy of autofocus processing in squint spotlight synthetic aperture radar (SAR). In contrast, the frequency-domain autofocus algorithms can avoid this problem because it does not involve the azimuth deramping operation. However, the existing frequency-domain autofocus algorithms are proposed based on the assumption of broadside mode, which cannot be directly applied to the squint mode. Therefore, this article extends the existing frequency-domain autofocus algorithm to the squint mode combined with the extended Omega-K (EOK) algorithm. Furthermore, a space division (SD) algorithm is embedded into the proposed algorithm as preprocessing, which can effectively compensate for the azimuth-dependent motion error. The simulation and real data are processed to verify the effectiveness of the algorithm.

High-resolution wide-swath (HRWS) multichannel synthetic aperture radar (SAR) system possesses a number of receiving channels along the azimuth direction, so it has the capacity of moving target indication and imaging. However, due to the radial velocity of the moving target, false targets occur in the focused image. By estimating the radial velocity and combining it with moving target imaging, false targets can be effectively suppressed. In this letter, a method of radial velocity estimation of a moving target is proposed based on the theory of subspace projection. This method does not need to estimate the real azimuth position of the moving target and can predict the processing time. Simulation and airborne measured data show the effectiveness of the proposed method.

Conventional beam-center approximation-based motion compensation (MOCO) algorithms fail to achieve an optimally focused image in the case of the high-resolution and high-frequency (HRHF) synthetic aperture radar (SAR) system. In this letter, a novel MOCO algorithm based on Doppler adjustment is developed with the ability to compensate the azimuth variant motion error. The change of the Doppler spectrum caused by the azimuth variant motion error is investigated and is eliminated by Doppler scaling. The proposed MOCO algorithm has dramatically improved precision when compared with the conventional MOCO methods in HRHF SAR imaging. Simulation experiments and extensive comparisons with other MOCO algorithms verify the effectiveness of the proposed algorithm.

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.

Since path curvature becomes severer for higher orbit synthetic aperture radar (SAR), the stripmap mode may not provide a reliable azimuth resolution under different look angles or at different positions. Beam steering is especially valuable herein for adjusting the azimuth resolution under different observation conditions by designing the antenna steering rate. Moreover, considering that the large range migration and center range variation in the squint mode may increase the echo length and reduce the achievable scene width, we proposed a novel 2-D beam steering (TDBS) method, which promises not only a required azimuth resolution but also a wide swath (or shortened echo length) at squint when cooperated with the variable interpulse time (VIPT) technique. The simulation results obtained under different look directions are shown to validate the effectiveness of the proposed beam controlling method.

Due to the constraint of minimum antenna area, azimuth ambiguity resolving is a challenging task in the ship focusing for single-channel synthetic aperture radar (SAR) mounted on high-speed maneuvering platforms. In order to accommodate the issues, a ship focusing algorithm based on azimuth ambiguity resolving is proposed in this paper. For ship SAR imaging with small-aperture data, the energies of different targets are separated in Doppler domain with different Doppler ambiguity numbers. Thus, the Doppler ambiguity number of a single target can be estimated by residual envelope inclination. Then, the target can be accurately focused and located at the correct position by the known Doppler ambiguity number. After the operation of each target is completed, the focusing SAR image of the whole scene can be obtained. Finally, simulation results are presented to validate the proposed algorithm.

When airborne radar platforms have a hypersonic speed, the Doppler bandwidth will be several hundred times of that from the low speed platforms. There are contradictions between pulse repeat frequency (PRF), Doppler ambiguity and range swath during the system parameters design. Azimuth multichannel technique is applied to make the PRF lower and can get a wide range swath. The equivalent phase center (EPC) under high squint (HS) mode is calculated. Then the Doppler spectrum is reconstructed by spatial filtering method with azimuth dependent channel compensation.

Based on a two-dimensional phase coding, a novel range ambiguity suppression technique is proposed in this paper. By transmitting two-dimensional phase coded signals, the two-dimensional spectrum of the range ambiguous signals will be shifted along both range and azimuth directions compared with that of desired signals. Then, part of the two-dimensional spectrum of the range ambiguous signals will be located outside the two-dimensional spectral support, which is known in priori, of the desired signals. Considering the range frequency and Doppler oversamplings, a filter corresponding to the two-dimensional spectral support of the desired signals is applied, which suppresses the range ambiguity. Simulation results of both point targets and distributed targets validate the effectiveness of the proposed method.

This paper presents a new method for estimating the baseline error of an azimuth multi-channel SAR antenna in the SAR image domain. In this paper, the expressions of the image domain of multi-channel SAR signals with azimuth baseline errors are derived. The covariance matrix of the image domain signals is obtained by using the joint pixel method. Finally, the least-squares method of image domain is deduced to estimate the azimuth baseline of multi-channel SAR error. Simulation experiments verify the effectiveness of the proposed method.

A long synthetic aperture passive localization method for two Frequency shift keying (2FSK) signal via azimuth chirp-rate contour is proposed in this paper. By introducing synthetic aperture radar (SAR) imaging technology into passive localization, Doppler frequency change rate of received signal, which is called as azimuth chirp-rate in this paper, is estimated by azimuth focusing. Then, a grid map is formed on the ground and azimuth chirp-rate of each point is calculated to get an azimuth chirp-rate contour map. In the contour map, signal emitter is located in an azimuth chirp-rate curve in which the azimuth chirp-rate value is equal to its estimate. The azimuth chirp-rate contour map of a ground area varies with position of sensor. Therefore, two different azimuth chirp-rate curves can be obtained through different periods of a trajectory and the intersection of the two curves gives estimate of the emitter location.

This chapter introduced the basic concepts of SAR and the principle of 2D target resolution. Obtaining high range resolution with wideband signal and high azimuth resolution with long synthetic array is the basis of the 2D high-resolution imaging. RDA is widely used in SAR imaging processing. Azimuth-translation invariance is the key of RDA. This chapter described the major processing step of RDA, including range compression, range migration correction and azimuth compression, and derives the signal expression of the key step. With the development of SAR imaging requirements, SAR has developed a variety of working modes. This chapter also introduced the working geometry of Stripmap mode, Spotlight mode, Sliding Spotlight mode, TOPS mode and Scan mode, established the unified signal model for multi-modes and analysed the signal property. In imaging processing for multi modes, a unified focusing algorithm based on FrFT is shown, which can simultaneously process Stripmap, Spotlight, Sliding Spotlight and TOPS SAR mode data. The focusing algorithm is parameterised into a rotation angle or a rotation factor, which is determined by the rotation centre distance. Real data of different modes can be well focused by using different and appropriate rotation angles.

A imaging passive localization method for wideband signal is proposed in this paper. By introducing synthetic aperture radar (SAR) imaging method, the location of the signal emitter is directly given in SAR image. The key of this method is to focus unknown wideband data in range and azimuth domain. To focus the data in range domain without signal parameter, a new pulse compress method is proposed by constructing reference signal from raw data. To focus the data in azimuth domain without knowing range, a range-searching azimuth focus method is proposed by constructing azimuth focus functions with different range. Simulation result validate the effectiveness of the proposed method.

The yaw steering may be ineffective to compensate for the large Doppler centroid in geosynchronous SAR (Geo-SAR) in many cases. Therefore, the available studies are concentrated on the 2-D beam-steering, rather than the yaw steering. However, the range and azimuth may be severely coupled without any beam-steering or with the 2-D beam-steering. Fortunately, we found that the yaw steering could overcome this serious problem, and can bring several benefits in terms of the performance improvement of the system. In this paper, we first illustrate the benefits of the yaw steering, and then provide two aspects of the system design with the incorporation of demonstrating the benefits of the yaw steering. The demonstrated three main benefits of the yaw steering are: 1) makes the 2-D side-lobes nearly orthogonal, and improves the imagery quality; 2) largely reduces the synthetic aperture time, and decreases the computation burden of imaging processing; and 3) substantially mitigates the azimuth-variation of raw data, and simplifies the imaging processing.

Synthetic Aperture Ladar (SAL) is a combination of synthetic aperture and lidar. At present, sub-aperture stitching with PGA algorithm is used to realize SAL imaging. However, this algorithm has a low rate of data utilization, resulting in a worse image SNR and resolution. For solving this problem, a method of sub-aperture phase error stitching for full aperture airborne SAL data processing based on azimuth deramp is proposed in this paper. The data is divided into a sequence of sub-apertures and the standard Standard Minimum Entropy Autofocus (MEA) is used to estimate the phase error of each sub-aperture. Then all the phase errors of the sub-apertures are stitched to obtain the full-aperture phase error. After the compensation of the full-aperture phase error, the full-aperture image is obtained by deramp. Compared with the SAL image obtained by sub-aperture algorithm, the method we proposed can offer better resolution and SNR. Finally, the imaging results of airborne SAL real data verify the effectiveness of the proposed algorithm.

For high-resolution wide-swath synthetic aperture radar imaging algorithms, signal reconstruction is a key step. The steering vector plays an important role in signal reconstruction, which can be constructed by the ambiguity components. The information of the ambiguity components, e.g., number and index, is usually regarded to be constant and known. However, we find that the information of ambiguity components is always a piecewise function of the baseband frequency. This means that the steering vector cannot be preconstructed accurately and it will negatively affect the signal reconstruction. This paper presents an improved signal reconstruction method based on the Doppler spectrum estimation. The proposed method can estimate the variant ambiguity components to form the steering vector exactly by the Capon estimation. As a result, the method is able to restore the Doppler spectrum entirely and performs well on the noise reduction. Moreover, the baseband Doppler centroid and antenna pattern can be obtained in the proposed method. Simulated data and airborne raw data are processed to validate the algorithm.

The ultralong synthetic aperture time and a very large scene cause severe 2-D spatial variation in geosynchronous synthetic aperture radar. The range variation was corrected using the range cell migration equalization and the modified chirp scaling function. The azimuth variation correction with the singular value decomposition and the azimuth nonlinear scaling was studied. The validity of the proposed imaging algorithm has been assessed. Satisfactory results were obtained in the removal of the azimuth variation, and the focusing of point targets from a synthetic aperture up to 1000 s and a scene of 150 km (azimuth) $\times$ 130 km (range).

To meet the demand for large area environment monitoring during short synthetic aperture time, this paper proposes an imaging algorithm for high squint beam steering (HS-BS) SAR platforms with constant acceleration. To achieve a good performance and high efficiency, the baseband azimuth scaling (BAS) method cannot be directly applied for the azimuth focusing. The signal is calculated based on high squint concentric circle (HS-CC) range model. The conventional derotation operation is modified by nonlinear phase and range-dependent derotation. Then the space-variant (SV) Doppler chirp rate is corrected by BAS method without sub-aperture processing.

Synthetic aperture radar (SAR) imaging is usually performed along a straight path. In practice, variations from the ideal caused by maneuvers with acceleration are inevitable. The main problem is the complex signal processing, particularly in the highly squinted spotlight mode. In this paper, acceleration model is analyzed in more details. Impacts are obtained how the acceleration influences the Doppler parameters and space-variant terms, including the SAR resolution and azimuth bandwidth. According to the special signal properties of the acceleration case, an approximation of the range history is made to avoid using the method of series reversion (MSR) to obtain an accurate spectrum. Based on the high-accurate spectrum, a spotlight algorithm with a modified two-step approach is given. Simulation results show the effectiveness of the modified algorithm.

This paper first introduces an accurate inverse synthetic aperture radar echo model for the fast moving targets. In this model, the target's motion during the time periods of the pulse transmitting, propagating and receiving have been taken into account, and some problems, which have been ignored in the `stop-go' model, may occur, for example, the varied ambiguity numbers and the drifted frequency centre. These problems will cause many difficulties in obtaining a high resolution range profile (HRRP) synthesis. To deal with these problems, a stepped frequency synthetic preprocessing (SFSP) algorithm is presented. The key of the proposed algorithm is synthetic preprocessing, including Doppler ambiguity suppression, echo coherence restoration and frequency centre correction, respectively. By completing the preprocessing, the HRRP can be achieved by a bandwidth synthesis and a well-focused image can be obtained by a keystone transform and an azimuth process, respectively. The simulation results validate the proposed SFSP algorithm by comparing it with the algorithm in the existing extended `stop-go' model.

The linear range walk yields a significant range-azimuth coupling effect in a highly squinted synthetic aperture radar (SAR). Although the linear range walk correction (LRWC) technique can effectively mitigate such coupling effect, it causes azimuth variation in the resulting signal and, as such, the so-called “azimuth-shift invariance” property becomes invalid. In order to eliminate the azimuth variation, a new spectrum processing approach based on azimuth resampling is proposed in this paper. After performing the LRWC, the azimuth resampling is carried out in the 2-D frequency domain and transforms the signal spectrum to be equivalent to that of a broadside SAR. For squinted beamsteering SAR (BS-SAR), e.g., spotlight SAR, sliding spotlight SAR, and Terrain Observation by Progressive Scans SAR, the azimuth resampling is combined with the azimuth signal reconstruction algorithm. As a result, both the azimuth variation, which is induced by the LRWC, and the aliasing, which is caused by antenna beam steering, can be avoided. Therefore, after the azimuth resampling, the squinted SAR data can be focused by exploiting a conventional broadside SAR imaging algorithm. An analysis of the motion error for airborne SAR data processing is also provided. Simulation and real data results show the effectiveness of the proposed algorithm.

During the data acquisition of a squint terrain observation by progressive scan (TOPS) synthetic aperture radar (SAR), the steering of the antenna main beam increases the azimuth bandwidth and results in the azimuth signal aliasing in the Doppler domain. Besides, the range curvature and the Doppler frequency modulation (FM) rates after linear range walk correction are azimuth-variant for squint TOPS SAR. These problems may cause some difficulties for the SAR data processing. To deal with the problems, a new imaging algorithm for the squint TOPS SAR is introduced in this paper. After linear range walk correction, the azimuth preprocessing is implemented to achieve the two-dimensional frequency spectrum without aliasing. Then, utilizing a modified chirp scaling algorithm, we complete the range cell migration correction (RCMC) and range compression to the TOPS SAR data without subaperture. Finally, the frequency nonlinear chirp scaling (FNCS) is proposed to correct the variation of the FM rates and the azimuth signal is focused in the Doppler domain via the spectral analysis (SPECAN) method. Both simulation and real data results show the effectiveness of the proposed algorithm.

Multiple-input multiple-output SAR (MIMO-SAR) can transmit multiple waveforms and separate the radar echoes, which enables it to work in several modes simultaneously such as spotlight, sliding spotlight and strip-map modes. However, most of the existing waveforms are not well orthogonal, which cannot separate the echo completely and thus degrade the performance of MIMO-SAR applications. To solve this problem, a novel digital beam-forming (DBF) method for multi-modes MIMO-SAR based on APC waveforms is proposed in this paper. Due to the Doppler shift effect of the APC waveforms, the spectrum of overlapped echoes change with azimuth angles. Therefore, the digital beam-forming (DBF) in azimuth can be used to separate the echoes well. Finally, simulations of both point target and distributed target are conducted to validate the effectiveness of the proposed method.

Terrain Observation by Progressive Scans (TOPS) synthetic aperture radar (SAR) and spotlight SAR are advanced SAR imaging modes for wide range swath and high resolution. In order to obtain a wider range coverage, azimuth multichannel is introduced in the literature. Since the azimuth bandwidth of beam steering SAR (BS-SAR; spotlight SAR, sliding spotlight SAR, or TOPS SAR) is much greater than that of a stripmap SAR, a signal reconstruction algorithm used for multichannel stripmap SAR may not be effective for multichannel BS-SAR. In this paper, a multichannel full-aperture azimuth processing algorithm is proposed for a BS-SAR. The key of this algorithm lies in the beam and the azimuth bandwidth compressions of multichannel signals in the Doppler-array and slow time-angle planes, respectively. Through compression processing, the beamwidth and the azimuth bandwidth are smaller than the available angle and equivalent pulse repeating frequency , respectively. Then, an improved post-Doppler STAP method is proposed to recover a 2-D spectrum. With the recovered signal, further processing can be utilized to focus the multichannel signal. Simulation and real data results show the effectiveness of the proposed algorithm.

In the synthetic aperture radar (SAR) system with low pulse repetition frequency (PRF) sampling, it is difficult for the motion parameters estimation of the moving targets, because of the Doppler spectrum ambiguity and Doppler centroid frequency ambiguity of the echo signals. Considering that moving targets are sparsely distributed in the observed scene, their positions and velocities can be reconstructed by using the compressed sensing (CS) technique. In this paper, the range-walk correction are implemented by the Keystone transform and the sparse range-walk correction (SRWC), then the CS technique is proposed to reconstruct motion parameters by processing the azimuth signals of the moving targets. Experiments using the simulated and real data are performed, and the results confirm the validity of the proposed method.

Since synthetic aperture technology was employed in radar signal processing, the information capability of radar has greatly been enhanced. A lot of imaging algorithms have also been developed. However, the high-resolution imaging for highly squinted synthetic aperture radar data is still a difficult issue due to large range migration and strong range dependence on the secondary range compression term that is relatively large and cubic with high focusing sensibilities for high resolution. To accommodate for this problem, the "squint-minimization" operation and azimuth nonlinear chirp scaling (CS) (ANCS) operation are studied in this paper. On the basis of these operations, we propose new imaging algorithms and analyze the characteristic of highly squinted data and the difficulty in focusing these data as well as discussing the principle of ANCS. We also introduce a new CS algorithm, and numerical examples show that the proposed algorithm is able to achieve 0.1 m of resolution under a squint angle as large as 70°s.

According to the characteristics of narrow-band radar echoes from spinning targets, this paper applies the complex-valued back-projection method to image formation. Since it accumulates the sinusoidal phase of spinning scatterers effectively, this method can obtain high resolution imaging. The resolution and required radar pulse repetition frequency (PRF) of this method are deduced. For imaging of fast spinning targets, however, spurious peaks appear due to azimuth down sampling with a low PRF. Therefore, a signal model of azimuth down-sampled echoes is created according to the compressed sensing (CS) theory. Then an imaging method based on orthogonal matching pursuit (OMP) is proposed according to the sparsity nature of ISAR echoes. Finally, the effectiveness of the proposed methods is demonstrated using simulated data.

The image scene is limited by the small size of the spot, which is linked with the short wavelength of the laser in synthetic aperture ladar (SAL). The common wide-scene imaging mode in synthetic aperture radar, i.e., the terrain observation by progressive scans imaging mode, is extended and applied in SAL. A suitable imaging algorithm is also proposed according to the characteristics of the signal. First, the azimuth prefiltering based on the spectrum analysis is adopted to eliminate the azimuth spectrum aliasing caused by the steering of the antenna beam. Then, the improved frequency scaling algorithm is applied to complete the range compression and range cell migration correction. Meanwhile, the Doppler frequency shift induced by the continuous moving of the platform is compensated. Finally, the azimuth compression is completed in the Doppler domain, and the SAL image without ambiguity is obtained with the application of the dechirp technique. Simulation results provide the evidence on the effectiveness of the proposed method.

As an emerging technique to obtain remotely sensed data, geosynchronous synthetic aperture radar (GEOSAR) is still at the infant stage for the development of the basic theory although some prediction indicates that the first GEOSAR satellite would be in orbit around 2020. Before the launching, a series of challenges in GEOSAR must be addressed and the feasible solutions should be carried out. Thus, systematic analyses of challenges and solutions in GEOSAR are proposed here. In this paper, the GEOSAR has been studied through analyses of bi-static imaging geometry, signal model, Doppler characteristics, Doppler bandwidth and synthetic aperture time, and resolution evaluation of the GEOSAR imagery, in which both challenges and solutions are included.

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.

In order to resolve the range and azimuth ambiguity in MIMO-SAR imaging, this paper proposed a joint two-dimensional ambiguity resolving method based on space-time filtering, which according to the ambiguity in different subscene is relative to different nearest echo range, and different azimuth time is relative to different instantaneous incidence angle, to make two-dimensional space-time steering vector for resolving ambiguity of the echo, which also can finish the imaging processing at the same time. Simulation results validate the proposed processing approach for the MIMO-SAR system.