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.

Speckle is a significant problem in synthetic aperture radar (SAR) image processing, as it deteriorates the texture details and thus limits the precision of its high-accuracy applications. The impact of speckle on SAR images is related to their structural characteristics, which usually classify the images into homogeneous regions, heterogeneous regions, and extremely heterogeneous regions. In the latter two regions, structures such as edges and strong point targets generate a more complex speckle distribution which differs from that in homogeneous regions. Despeckling filters based on multiplicative models perform well in homogeneous regions but exhibit poor performance in the other two types of regions. To solve this problem, a collaborative optimization for SAR image despeckling with structure preservation is proposed in this article, which leverages the coupling between the despeckling module and the structure extraction module. Guided by structure information, the proposed method achieves better preservation of edges and texture details while removing speckle. Experimental results based on real SAR images demonstrate that the proposed method effectively enhances the despeckling performance in all three types of regions.

The azimuth multichannel synthetic aperture radar (SAR) technique can simultaneously achieve high resolution and wide swath, which is important for disaster management, sea and land traffic observation, and environmental monitoring. However, nonuniform sampling leads to multichannel imaging quality degradation such as serious ghost targets or deterioration of signal-to-noise ratio (SNR). In this article, a multichannel SAR imaging algorithm is proposed. The key is to perform spectral selection and extrapolation based on the time-frequency characteristics of multichannel signals under nonuniform sampling conditions to obtain subimages with different ghost distributions. By implementing subimage fusion, the final imaging result can be obtained. Simulations and satellite real data experiments are conducted to verify the effectiveness of the proposed algorithm. The imaging performances of the proposed algorithm in terms of ghost-to-real target ratio (GRTR), and SNR are investigated with respect to the pulse repetition frequency (PRF). Moreover, simulation results also demonstrate that the proposed algorithm exhibits a more robust and consistent overall performance than existing methods.

Bistatic geosynchronous synthetic aperture radar (GEO SAR) system with a stationary receiver is capable of continuous observation and frequent revisit over certain area, which can be applied in disaster monitoring. The mismatch between the true height and the assumed height of the imaging plane may result in azimuth defocusing. This paper exploit the azimuth defocusing effect to estimate the height of strong scatterers. By estimating and compensating the quadratic phase error, fine imaging results in the reference plane are obtained. The height can then be retrieved accurately combining the phase error and the imaging position in the imaging plane. Simulation based on point targets verifies the proposed method.

In microwave remote sensing applications, some areas need to be observed frequently. Compared with the historical observations, the current observation has a little new content. This means that the increment is sparse, making it possible for imaging with under sampled echoes. For the increment imaging, we first establish the linear observation model and the increment model, making it a two-variable optimization problem. Then, the block coordinate descent strategy is used to implement the increment imaging. To estimate the unknown phase matrix, we make the uniform quantification assumption, and an extended Lagrangian multiplier method is applied. For the sparse increment, Bayesian compressed sensing (BCS) is used. Two different resolution scenes are used to verify the feasibility of this algorithm. The performance under different signal-to-noise ratios (SNRs) and undersampling ratios has been discussed as well.

Multistatic geosynchronous synthetic aperture radar (GEO SAR) system, with a geosynchronous illuminator and two stationary receivers, can provide high-resolution images for certain area. The spatially variant gaps in the azimuth spectrum, however, may introduce artifacts into images, which degrade the image quality. To fill the spectrum gaps, a new imaging method using spectrum alignment and extrapolation is proposed in this letter. The spectrum of the scene is aligned based on spectrum shifting and range Doppler projection, and a complete azimuth spectrum is obtained by spectrum extrapolation and coherent summation. Simulation results of point targets and extended targets verify the efficacy of the proposed method.

For the azimuth multichannel synthetic aperture radar (SAR), nonuniform sampling is common since the pulse-repetition frequency cannot be selected arbitrarily, which leads to the contradiction between ambiguity and noise suppression in the azimuth signal reconstruction. This letter constructs a novel multichannel signal model by taking the coherence among different Doppler bins into account and proposes a minimum-energy-based multichannel reconstruction algorithm, which can obtain the unambiguous signal spectrum without increasing noise in the nonuniform sampling cases. By comparing the simulation results formed by digital beamforming (DBF), improved DBF (IDBF), and space-time adaptive processing (STAP) algorithms, the proposed algorithm shows better performance in balancing ambiguity and noise.

Geosynchronous synthetic aperture radar (GEO SAR) system has the ability of observing targets for several hours in a large field of view. Complex and irregular rotating motion of the ship on sea in long aperture time makes it difficult to focus. To accomplish the imaging of maneuvering ships, a novel imaging algorithm is proposed in this article. A spatial filter constructed by convolutional neural network (CNN) is utilized to extract the time–frequency features. Combined with local generalized Radon–Fourier transform (GRFT) and phase gradient autofocus (PGA), the extraction accuracy further increases. Validation results based on simulation experiment, airborne experiment, and wave pool experiment show that the proposed algorithm achieves good imaging performance.

Sidelobe suppression is a basic but important task for synthetic aperture radar (SAR) images, since the existing sidelobes can reduce the image quality and complicate image interpretation. The main task of sidelobe suppression is to suppress the sidelobes effectively while maintaining high image resolution and the mainlobe's energy. However, the most effective method, robust spatially variant apodization (RSVA), still faces the problem of energy loss on cluttered targets caused by phase factors. This letter proposes an SAR sidelobe suppression method based on the convolutional neural network (CNN) to compensate for the energy loss in RSVA. The experiments on the SAR images show better performance on both sidelobe suppression evaluation metrics and signal-to-noise ratio (SNR) preservation compared with conventional methods.

Quasi geostationary orbit (GSO) synthetic aperture radar (SAR) has the superiority of continuous wide view Earth observation. High resolution is achieved at the cost of long integration time. In this paper we propose a new imaging method for quasi GSO SAR constellation. By implementing spectrum gap filling, the azimuth resolution corresponding to the gapped synthetic aperture covered by the constellation is reached. Simulation results validate the proposed method.

Long integration time of GEOSAR makes it difficult to deal with the maneuvering target due to the complex relative motion between radar and target. This paper addresses the motion parameters estimation problem of high speed maneuvering target in GEOSAR where translation motion and rotating motion are considered. A method based on Keystone transform, Fractional Fourier Transform (FrFT) are introduced to estimate and compensate the translational motion and extract micro motion feature. The effectiveness of the method is validated by simulation results.

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. In this paper, a novel steering strategy to maximize Nesigma0 for GEO SAR is proposed when the beam illuminates outside the earth surface. The new geometry and the gradient method are applied to demonstrate the method. The ability to stare imaging in geosynchronous orbit SAR is analyzed and verified by using the back projection (BP) algorithm to simulate the imaging principle. Nesigma0 under the new method improved 1dB comparing with the original image.

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.

The Compressive Reflector Antenna (CRA) has the ability to span dynamic pseudo-random phase wave-front in space, which can be used to modulate the echo in phase, replacing the traditional Doppler style. That means radiometric observing imaging have the opportunity to be implemented in geostationary orbit, a kind of special geosynchronous orbit. For the extremely low SNR in this geometry, we propose using matched filter to improve the SNR and make the constructing more precision. In imaging aspect, we use the Back Projection and Compressed Sensing techniques to imaging at each range gate. Resampling operation is applied to eliminate the influence from the matched filtering. And some necessary simulations have been done to verify the rationality of observing system and imaging algorithm.

Geostationary orbit (GSO) synthetic aperture radar (SAR) constellation has the advantage of continuous Earth observation and can achieve high azimuth resolution. In this paper we propose an imaging method for GSO SAR constellation. By implementing data fusion, the azimuth resolution corresponding to the synthetic aperture covered by the constellation is achieved. Simulation results verify the effectiveness of 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.

An innovative method applied for suppression sidelobe in synthetic aperture radar (SAR) images is presented in this paper. The basic idea is to decompose the chirp signal into the unrelated chaos frequency modulation (CFM) signals uniformly in CFM space and add up their pulse compression results. As various CFM signal has different ideal thumbtack autocorrelation function, the energy from the sidelobe of the above-mentioned adding result is kept in a low level when compared with that from mainlobe. Our method can suppress the sidelobe to -40dB and hardly deteriorate resolution simultaneously. The corresponding performances are verified in the simulation experiments.

In order to solve the parameters estimation problem caused by the moving target with the micro motion in the GEOSAR model, a technique based on time-frequency distribution and least squares estimation is introduced. The model of micro-motion part can be seen as a narrow band stochastic process, which is close to the reality of the motion. The method is used to estimate the parameters of the translation which is coupled with the micro motion. Simulation results indicate that the method can estimate the Doppler parameters of translation part efficiently.

Synthetic Aperture Radar (SAR) has been developing from single-working mode to multi-working model. And the antenna pattern becomes hundreds and thousands, which causes a huge burden on radiometric calibration. Using antenna models to replace the measured antenna patterns in radiometric calibration can greatly simplify the calibration duties. This paper tries to find the relationship between antenna model accuracy and radiometric calibration accuracy. Based on the antenna structure and active phased array theory, antenna model with reasonable error can be simulated, and a kind of antenna model accuracy closed mathematics expression can be achieved. Using antenna model with error in radiometric calibration campaign, and statistical the calibration accuracy in different antenna model accuracy, the relationship between the two can be derived. The relationship is linear, coinciding to analysis result.

One of the most important properties in geosynchronous synthetic aperture radar (GEO-SAR) is the resolution in the ground range plane, whose relationship with resolution in the slant range plane is complicated, which results in evaluation difficulties. This paper proposes a method of evaluation of the ground resolution using geometric correction, while transforming the GEO-SAR images from the slant range plane to the ground range plane. Simulation results verify the effectiveness of the proposed method.

Speckle noise is an inherent problem in synthetic aperture radar (SAR) images. Recently, non-local (NL) means performs well in speckle reduction. However, there exist two issues in traditional NL means. Speckle noise and strong targets would affect the correctness, thus resulting in over smoothing and speckles unchanged. In this paper, an improved algorithm combined with wavelet transform and adaptive NL means is proposed. First, linear minimum mean-square error (LMMSE) filtering in undecimated wavelet domain is operated and we get a “clean” image. Second, we eliminate the influence of strong targets adaptively when similarity is derived. At last, under the help of similarity, original image rather than the “clean” image is filtered. Proposed method performs better in both speckle reduction and strong targets preserving compared with the traditional method.

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.

Atmospheric refraction in the troposphere causes the propagation speed of electromagnetic signals to be less than the light speed. This creates a difference between the actual propagation path delay and the distance of the geometrical straight-line path, i.e, a quantity known as the tropospheric delay. As classical imaging algorithms for spaceborne synthetic aperture radar (SAR) do not take the tropospheric delay into account, imaging filters are designed based on the assumption of rectilinear propagation with the light speed. Therefore, a residual phase exists in imaging results, which affects focusing quality under the condition of high resolution. In order to compensate for the impact of tropospheric delay on focusing performance, this paper modifies the spaceborne SAR echo model and then proposes an imaging compensation algorithm. The key to this algorithm is to fit a range delay coefficient based on the European Geostationary Navigation Overlay Service model of zenith delay and Niell mapping function, which projects the zenith delay onto the looking direction. After range compensation, classical imaging, and azimuth compensation, which compose the proposed algorithm, the processed results are well focused.

Squinted multi-channel SAR is a available mode to achieve the high-resolution and wide-swath, because it is more flexible than broadside SAR. However, the traditional processing algorithm of broadside multi-channel mode is not suitable for squinted multi-channel mode, because the high squint angle will lead the reconstruction to fail. In this paper, a modified reconstruction method adapted to squinted multichannel SAR signal is proposed. The large central Doppler frequency of the squinted Doppler spectrum is taking into account, and the reconstruction method is modified accordingly. Meanwhile, the range walk correction is performed before the reconstruction to remove the mismatch between the reconstruction filters and the squinted signal with large range cell migration. Furthermore, the processing algorithm based on the wave-number algorithm framework with range walk correction is proposed. Finally, computer simulation results are presented to demonstrate the validity of the proposed algorithm.

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.

Synthetic Aperture Radar (SAR) echo simulation is an effective tool of the radar system design, which enables us to validate imaging algorithms and evaluate the performance of SAR systems before actual use. The increasing demand of higher SAR resolution makes the SAR simulation more and more complicated. The traditional simulation methods are not precise enough so that a new simulation method applicable to most complicated targets is needed. This paper demonstrates a novel simulation method based on the theory of electromagnetic scattering which simulates the received echo data through taking use of the backscattered electric field. Our simulation method can be used to simulate a complicated target in SAR simulation. This method opens a door to conducting SAR echo simulation with theory of signal and system and the electromagnetic scattering taken into consideration, though a few improvements are needed to increase the performance of the SAR simulation.

Spaceborne synthetic aperture radar (SAR) has been proved highly significant for remote sensing of the Earth. The image quality is constrained by the system design and the image processing technology, azimuth ambiguity is one of the most important factors. We know the pulse repetition frequency (PRF) determine the sampling rate of the azimuth, but the spectrum of the azimuth is non-bandlimited, it is hard to find a suitable solution with the conventional approach. A new method is proposed based on PRF micro-variation to suppress the azimuth ambiguity for spaceborne SAR, which changes the sampling mode and makes the azimuth signal no longer uniform in frequency domain. At last it can improve the image quality and make the ambiguity energy disperses randomly. In this paper, the basic theory of azimuth signal sampling is reviewed, and the reason of azimuth ambiguity is also introduced in detail. Through analysis we discover the PRF micro-variation has a scope, finally, some simulation results demonstrate this method is effective and feasible.

Traditional quality evaluation of Synthetic Aperture Radar (SAR) Image is mainly based on the objective indicators of point target and surface target. However, it lacks subjective knowledge of human visual. To overcome this shortcoming in traditional image evaluation method, an innovative method by employing the human visual system (HVS) without reference image has been proposed to evaluate SAR image quality in this paper. Due to the comparability of the biological characteristics in human eyes with discrete wavelet transform (DWT), a subjective image quality evaluation model is set up. The effectiveness of the approach was validated by the computer simulations using the real airborne SAR images, as well as it shows high accordance with the actual image quality. The novel quality evaluation algorithm will provide the foundation in the future field of SAR subjective evaluation.

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.

This paper introduces the concept of waveform diversity into the design of ultra-wide swath, high resolution SAR system. The range ambiguity is suppressed due to waveform orthogonality. The blind zones are eliminated by adopting varied pulse repetition frequency (PRF). Digital beam forming (DBF) in elevation ensures effective illumination of the target scenario. The swath width is therefore enlarged whereas the image degradation is negligible. Compared with traditional SAR systems, range ambiguity-to-signal ratio (RASR) is lower by transmitting orthogonal waveforms and azimuth ambiguity-to-signal ratio (AASR) is decreased because of varied PRF. The basic principles are advanced and the characteristics of the new system architecture are investigated. A preliminary design of an example system is presented at last.

High resolution and wide swath have always been critical criteria for SAR systems and consistently pursued. This paper investigates the utilization of pulse repetition frequency (PRF) variation in two situations: very high resolution and ultra-wide swath. It is demonstrated that by adopting varied PRF, in the former case, which corresponds to Spotlight and Sliding Spotlight modes, a much larger range cell migration(RCM) is tolerated and higher resolution is thus guaranteed, while in the latter case blind ranges are eliminated and wider swath are imaged without conspicuous degradation. The principles of PRF variation of both cases are proposed. It is shown the benefits of PRF variation include higher resolution, wider swath width and decreased azimuth ambiguity-to-signal ratio(AASR) and higher data efficiency.

Spotlight synthetic aperture radar (SAR) can obtain high resolution SAR image but the observation area is restricted. This paper presents a new imaging mode named jumping spotlight SAR to achieve high resolution and wide swath simultaneously. In jumping spotlight mode, high resolution SAR image is acquired by antenna beams steering, and meanwhile the wide observation swath is realized through antenna beams scanning in range and azimuth directions. The imaging theory of jumping spotlight SAR is given based on the data acquisition geometry and some of the imaging difficulties are analyzed. Then the design principle of the antenna beams scanning order is proposed in this imaging mode. Simulation results show that the scanning order design rule can simplify the processing of squint spotlight imaging.

As the existing technology is not ideal, saturation of radar receiver is inevitable. Receiver saturation will reconstruct the original echo signal and cause the target strength distortion and false targets. This paper established a nonlinear mathematical model of simplified saturation. The signal phase and amplitude errors are obtained by using quadrature demodulation. Then we analyzed the effects of these errors on image formation and verified conclusions by simulation.

Geosynchronous orbit synthetic aperture radar (GEO-SAR) has a good application prospect for its shorter repeat period and a wider swath compared to low Earth orbit SAR. Doppler characteristic of the echo is analyzed. The Doppler history varies frequently in space and approximates a high order signal. A back projection algorithm for high resolution GEO-SAR based on satellite-ground geometry model is preliminarily proposed. Steps of the algorithm are given. The simulation results indicate the algorithm can achieve high resolution image formation in large scene. The azimuth resolution is less than 2m.

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.

Traditional radar utilizes Shannon-Nyquist theorem for high bandwidth signal sampling, which induces the complicated system. Compressive sensing (CS) indicates that the compressible signal using a few measurements can be reconstructed by solving a convex optimization problem. Thus, the huge amount of data according to high Shannon-Nyquist rate is significantly reduced by compressive sensing. Parallel frequency radar theoretically cannot degrade the resolution compared with a traditional radar system and effectively reduces the sampling rate. In this paper, we focus on the data processing of the novel radar system. Basing on a sufficient structure, an algorithm of target scene reconstruction in pursuance of compressive sensing applied to the novel radar is proposed. Several simulations demonstrate the feasibility and the superiority of parallel frequency radar via compressive sensing.

Range migration of space borne SAR at large squint angle is much greater than the side-looking SAR, and longer echo receiving window is needed. Thus, the traditional beam position design method is invalid. In this paper, the method of drawing zebra map is improved by taking the range migration into consideration. The maximum and the minimum slant ranges during the synthetic time are derived. This paper also analyses the relation between the effective swath width and the range beam width at large squint angle. Simulation for X-SAR system proves that a given azimuth resolution limits the squint angle. STK and echo simulation are used to verify the validity of the improved beam position design method.