As one of the key performance indicators of SAR sensors, resolution, which is determined by the SAR signal bandwidth and plays a very important role in the interpretation of SAR images. The transformed images of high-resolution SAR images at different resolutions contain different layers of information, which can provide complementary resolvability for ship target extraction. In this paper, experiments and analyses are conducted on the effects of multi-resolution SAR images on the extraction accuracy of four parameters: length, width, principal axis angle and geometric center of ship targets. It is concluded that there is an influence on the geometric feature parameters of the ship targets of different resolution SAR images, and for a certain type of typical targets, there exists a critical resolution, which makes the extraction of the relevant parameters with the highest accuracy and the most stable performance.

In order to obtain the high resolution of two-dimensional azimuth and pitch direction, two-dimensional MIMO array is used for vehicle-mounted 4D millimeter wave radar. At present, two-dimensional MIMO millimeter wave radar arrays still have problems such as high sidelobe and grating lobe exceeding main lobe, which can not accurately identify target angle in detection process. Based on the current requirement of angle measurement, a design method of two-dimensional MIMO array is proposed. The array arrangement of low sidelobe and low grating lobe imaging effect is obtained by filtering the element spacing and restricting the distribution position of array elements. Finally, several different array configurations are discussed by simulation to prove the feasibility of the proposed method.

Performance of conventional algorithms for along-track baseline multichannel synthetic aperture radar (SAR), which deal with azimuth ambiguities, ground moving target indication (GMTI) or interference, degrades severely for hybrid-baseline multichannel SAR. Space-variant interferometric phase, due to terrain elevation and hybrid-baseline, destroys the consistency among Doppler spectrum, which is the foundation of these algorithms. An image-domain signal suppression method designed for hybrid-baseline multichannel SAR is presented in this letter. With prior knowledge about digital elevation model (DEM), the proposed method recognizes desired signal on each pixel stack and suppresses others by image-domain digital beamforming (DBF), which gives out a reconstructed image. Signal classification is achieved by pixel-wise direction of arrival (DOA) estimation in image domain. Error in DEM is also considered and analyzed, which guides the signal classification. Simulation with ambiguities and two types of interference are presented, verifying the proposed method.

Abstract—Auto-registration video synthetic aperture radar (ViSAR), which requires real time pixel index unifying and resolution matching, is of great significance due to its applicability in multi-aspect observation and continuous monitoring. The phase error induced by the wavefront planar assumption, however, varies with different ViSAR frames, which limits the size of auto-registration imaging scene. To enlarge the auto-registration imaging swath, a parameter-adjusting auto-registration overlapped subaperture algorithm (PAAR-OSA) is proposed in this paper. By collaboratively designing the subapertures within each frame and among different frames in the stabilized-scene coordinate and cooperatively compensating the phase error of all frames, auto-registration with larger imaging swath can be achieved. Both the point targets and distributed targets validation results verify the superiority of the proposed method compared with existing algorithms.

High-resolution wide-swath (HRWS) synthetic aperture radar (SAR) may benefit from reconstructing signals in the image domain, for taking local characteristics of the scene into account. An image-domain signal model for HRWS SAR to reconstruct nonambiguous images is presented in this article. This model makes the idea of controlling the regional reconstruction performance and taking the advantage of nonuniform scatter distribution possible. Resolution is also preserved perfectly by the proposed model despite whatever tradeoff is made between the azimuth-ambiguity-to-signal ratio (AASR) and the signal-to-noise ratio (SNR). The model is derived on backprojection (BP) images and can deal with different squint angles and beam steering strategies, thanks to the BP algorithm. Although the reconstruction is done pixel by pixel, the computational burden, which depends on beam steering and the specific constraints in reconstruction, may not severely increase. Two methods for Spotlight SAR and two methods for Stripmap SAR are also presented based on the proposed model to verify the model and demonstrate its potential. Simulations on both the point target and extended target with different squint angles are carried out to verify the proposed methods, which also verify the proposed model indirectly.

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.

This paper applies the overlapped subaperture algorithm (OSA) for geosynchronous (GEO) spaceborne/missile-borne bistatic SAR (GEO SMB-BISAR) imaging. Compared with the original bistatic SAR, GEO SMB-BISAR performs better in flexibility and security. The essence of the OSA is to perform the imaging process twice by azimuth subaperture division. The quadratic phase errors (QPE) induced by the planar wavefront assumption can be compensated by two steps imaging processing within and between subapertures. The OSA can expand a wider imaging swath than the polar format algorithm (PFA). Validation results demonstrate the validity of the OSA methodology.

Insufficient data of SAR target recognition task leads to low accuracy and poor generalization of model and the SAR imaging mechanism leads to the insignificant difference between ship targets, which make recognition difficult. To overcome the above problems, we propose a SAR maritime method using siamese networks for model pre-training. Siamese network produce sample pairs to ease training sample insufficiency, and output difference of sample pairs to help model learning heterogeneous difference. Then, transfer the pre-training parameters of feature exaction layer to an end-to-end model. Finally, the end-to-end convolutional neural network is obtained by fine-tuning the parameters with supervised information. Experimental results show that the SAR maritime target recognition method based on siamese network training can effectively improve the recognition accuracy under the training condition of a small number of samples.

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.

Most of the interferometric synthetic aperture radars (InSARs) operate in zero-squint or low-squint geometry. A spatial phase ramp in focused squint SAR images leads to a higher demand for coregistration, which limits the application of InSAR. This letter investigates InSAR processing with a high squint angle. The spatial phase ramp is here directly used for the construction of the digital elevation model (DEM). The method based on back projection algorithm (BPA) is analyzed first. Then the form of the interferometric phase for BPA is derived with the existence of squint, proved to share the same form as conventional InSARs. The restriction that relates to coherence is also discussed. A processing flow without coregistration is finally presented. Simulated two-channel SAR data validates the proposed method.

Video synthetic aperture radar (ViSAR) is gaining increasing attention in the remote sensing area due to its advantages in continuous observation compared with conventional synthetic aperture radar (SAR). Generally, the polar format algorithm (PFA) is utilized to generate the ViSAR frames considering both processing efficiency and imaging quality. However, the changes in squint angles for different ViSAR frames will cause variations in target positions when the classic fixed-parameter PFA is utilized. Hence, an image registration step is typically needed, which greatly increases the computational load. Meanwhile, the azimuth resolution also deteriorates rapidly for the ViSAR frames as the squint angle becomes larger. In order to solve the aforementioned problems, a parameter-adjusting autoregistration PFA (PAAR-PFA) is proposed for the ViSAR. By adjusting system parameters, such as carrier frequency, pulsewidth, and sampling frequency, according to the azimuth sampling positions, PAAR-PFA can achieve autoregistration for ViSAR frames without range interpolation and geometric correction in fixed-parameter PFA, which significantly improves the processing efficiency. At the same time, since the azimuth sampling number of frame data is adjusted with the squint angle, the variation range of the azimuth resolution under different squint angles is considerably reduced. Point target and extended target simulations confirm the feasibility of the proposed algorithm.

Interferometric Synthetic aperture radar (InSAR) aided inertial navigation system (INS) is developed to introduce terrain elevation into registration, which gives out accumulated error of INS. Unwrapped InSAR interferogram plays a key role in previous InSAR/INS frameworks, while airborne and side-looking assumptions are usually made. However, phase unwrapping is time-consuming and high squint geometry with nonlinear trajectory is common for applications with InSAR/INS. In this article, a novel wrapped InSAR interferogram based positioning method for high-speed maneuverable platform is proposed. A novel back-projection based InSAR (BP-InSAR) signal model for slightly curved diving trajectory with high squint angle is firstly presented. Then process which generates phase gradient template from given DEM is presented, considering both the estimated and measured trajectories. Error analysis is also made to discuss the performance of the proposed method in single dual-channel observation. Finally, a sequential maximum likelihood estimator based on error analysis is implemented to deal with the remained uncertainty in single observation. Numerical experiments verify the proposed method and fully demonstrate the performance of it with curved trajectory and random errors in both position and attitude.

In recent years, impressive performance of deep learning technology has been recognized in synthetic aperture radar (SAR) automatic target recognition (ATR). Since a large amount of annotated data are required in this technique, it poses a trenchant challenge to the issue of obtaining a high recognition rate through less labeled data. To overcome this problem, inspired by the contrastive learning, we proposed a novel framework named batch instance discrimination and feature clustering (BIDFC). In this framework, different from that of the objective of general contrastive learning methods, embedding distance between samples should be moderate because of the high similarity between samples in the SAR images. Consequently, our flexible framework is equipped with adjustable distance between embedding, which we term as weakly contrastive learning. Technically, instance labels are assigned to the unlabeled data in per batch, and random augmentation and training are performedfewtimes on these augmented data. Meanwhile, a novel dynamic-weighted variance loss (DWV loss) function is also posed to cluster the embedding of enhanced versions for each sample. The experimental results on the moving and stationary target acquisition and recognition (MSTAR) database indicate a 91.25% classification accuracy of our method fine-tuned on only 3.13% training data. Even though a linear evaluation is performed on the same training data, the accuracy can still reach 90.13%. We also verified the effectiveness of BIDFC in OpenSarShip database, indicating that our method can be generalized to other data sets. Our code is available at:https://github.com/Wenlve-Zhou/BIDFC-master.

Due to the complexity and inaccuracy of the force model of low earth orbit(LEO) satellite, the ephemeris data is not accurate enough for translation compensation, which will cause the residual translation component error, then leading to the dissatisfaction of the range and azimuth resolution for imaging. To face the problem above, the secondary correction of translational component is carried out by updating the ephemeris data fitted by the ephemeris data calculated by orbit two lines elements(TLE) and center slant which is estimated with the real echo data of the space station through correlation method, after a coarse correction-the registration of ephemeris data and echo data-and then the Inverse synthetic aperture radar(ISAR) image of the space station is obtained by combining the polar format algorithm(PFA), providing the foundation for monitoring, identification and tracking of space targets. The imaging results prove the validity of the method, which can be referred to in the imaging of LEO satellite and the real data processing based on ephemeris data.

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.

This paper studies positioning issue in navigation using InSAR concept. A novel method based on wrapped interferometric phase registration, which differs from common InSAR based navigation method, is proposed. This method may be useful when navigating throw hills or areas with low SAR image characteristics but rich terrain elevation features. Accurate DEM data is needed to generate ideal interferometric phase template for registration. Three dimensional positioning is achieved by estimating vertical bias and horizontal bias in order. The proposed method works well under different squint angle. Simulations are carried out to verify the method. Precision of the method under different squint angle is also exhibited in simulations.

The spatial localization of interference source is a critical procedure in Radio frequency interference (RFI) suppression. It is not suitable to use traditional multi-station interference localization methods in most synthetic aperture radar (SAR) systems. This paper proposes a novel method of single RFI localization based on conjugate cross-correlation of dual-channel SAR signals. First, interference detection technology is applied to check whether echo signal is interfered. Then, conjugate cross-correlation is performed on SAR signals, and the distance difference between interference source and receiving channels is calculated. Finally, spatial localization equations of interference source are established, and optimization algorithm is applied to solve the coordinates of interference source. The results of simulation experiments illustrate the effectiveness of the proposed method.

The classical linear frequency modulated waveform (LFMW) for synthetic aperture radar (SAR) can achieve a high range resolution and a superior signal-to-noise ratio (SNR) for point targets. Therefore, numerous researches got increasingly passionate about increasing resolution and SNR, rather than information acquisition of LFMW. This paper quantitatively analyzes and evaluates target information acquisition ability of LFMW, which is conducive to target perception. Firstly, a factor contributing to information acquisition of LFMW, is obtained under the discretized signal model. Secondly, a connection between LFMW and eigenvectors of target feature matrix is derived through the discrete Fourier bases, thus the information acquisition of LFWM is presented. Finally, the numerical simulations are made for the stochastic extended targets information acquisition of LFMW, and the results are employed to verify the theory analysis.

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.

Suppression technology of barrage jamming is an important approach to ensure the normal operation of the synthetic aperture radar (SAR) system. The detection and classification of jamming is a necessary procedure in this technology. Unsuitable thresholds set in the traditional methods may reduce the detection accuracy. In order to avoid it, this paper proposes a new method of barrage jamming detection and classification for SAR based on convolutional neural network (CNN). The signal model is constructed based on the statistical characteristics of the SAR echo signal. Based on this, a data set containing echo signals and interference signals is generated by simulation. Finally, the convolution neural network VGG16 is used to detect whether the signals in the dataset is contaminated by barrage jamming and identify the type of the interference. The experiment result illustrates that the VGG16 network trained by the frequency domain signals can effectively detect and classify the jamming signals.

The application of the spaceborne stripmap range sweep synthetic aperture radar (SS-RSSAR) is limited by its fixed azimuth beam pointing. In this paper a more advanced spaceborne azimuth-range sweep synthetic aperture radar (ARSSAR) is proposed to illuminate the region of interest (ROI) by simultaneously sweeping the beam in range and in azimuth. In this case, more balances of the azimuth resolution and the azimuth swath can be flexibly realized. The basic data acquisition problem for the spaceborne ARSSAR is analyzed from two aspects: firstly, an optimized beam illumination strategy is achieved by minimizing the width of the echoes from the ROI-strip; secondly, a continuous varying pulse interval (CVPI) method is suggested to avoid the transmission blockage and maximize the allowable width of the ROI-strip. The presented approach is evaluated by the simulations.

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.

Among high-squint high-resolution (HSHR) synthetic aperture radar imaging algorithms, nonlinear chirp scaling algorithm (NLCSA) and its extensions, such as extended NLCSA (ENLCSA), have a common drawback in that they all neglect the spatial variations of linear range migration (LRM) and Doppler centroid, and thus, only targets in a specific central slant range plane can be strictly focused. In this letter, we show that by using a new NLCSA, targets can be focused in the ground plane under HSHR conditions. Based on a more accurate 2-D spectrum, the new NLCSA outperforms the ENLCSA by introducing a new range–Doppler domain interpolation to correct residual range migration and a new perturbation function to remove the dependence of Doppler phase on azimuth. The coefficients of the new perturbation function are numerically calculated and then smoothed by polynomial fitting. Though the outputs of the numerical calculation are somewhat unstable at the current stage, it has been demonstrated to perform better than the algorithms neglecting the spatial variations of LRM and Doppler centroid, such as the ENLCSA, by point target simulations.

This letter theoretically extends and applies the overlapped subaperture algorithm (OSA) for the challenging spotlight synthetic aperture radar (SAR) imaging in a quasi-forward-looking (QFL) geometry. A parameter-adjusting framework, in which the radar parameters relate closely to the geometry, is employed to mitigate the spatial signal coupling. By innovatively fitting the phase error induced by the planar wavefront assumption directly to the wavenumbers, both the linear and quadratic phase errors, which determine the geometrical distortion and the defocusing effects, respectively, can be accurately expressed and then corrected. When compared with the parameter-adjusting polar format algorithm proposed by the authors in previous work, the OSA is superior in contributing to an expanded imaging swath. The validity of the OSA methodology is demonstrated by the simulation of a Ka-band SAR working in the QFL diving mode with an extreme 85° squint angle.

The spaceborne stripmap range sweep synthetic aperture radar (SS-RSSAR) is a new concept spaceborne SAR system that images the region of interest (ROI) with ROI-orientated strips, which, unlike the traditional spaceborne SAR, are allowed to be not parallel with the satellite orbit. The SS-RSSAR imaging is a challenging problem because echoes of a wide region have strong spatial varieties, especially in high-squint geometries, and are hard to be focused by a single swath. The traditional imaging algorithms could solve this problem by cost-ineffectively dividing an ROI into many subswaths for separate processing. In this paper, a new wide nonlinear chirp scaling (W-NLCS) algorithm is proposed to efficiently image the SS-RSSAR data in a single swath. Comparing with the traditional nonlinear chirp scaling algorithm, the W-NLCS algorithm is superior in three major aspects: the nonlinear bulk range migration compensation (RMC), the interpolation-based residual RMC, and the modified azimuth frequency perturbation. Specifically, the interpolation for the residual RMC, the most significant step in achieving the wide-swath imaging performance, is made innovatively in the time domain. The derivation of the W-NLCS algorithm, as well as the performance analyses of the W-NLCS algorithm in aspects of the azimuth resolution, accuracy, and complexity, are all provided. The presented approach is evaluated by the point target simulations.

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.

The polar format algorithm (PFA) is a classic algorithm for processing spotlight synthetic aperture radar (SAR) data and is extensively used in practical applications nowadays, mainly because its well performance in processing highly squinted data. Based on the chirp Z-Transform (CZT), PFA can be implemented accurately without any interpolation in the broadside case; however, for the squint mode case, since the input data are not uniformly distributed with same sampling intervals, the CZT algorithm requests interpolation in the azimuth dimension to obtain the uniform sample spacing, which leads to phase and amplitude error. To improve the processing accuracy under the squint mode, a CZT-based continuous varying PRF PFA is introduced. It achieves uniformly scaled grid along azimuth direction in wavenumber domain; as a result, interpolation in both range and azimuth dimensions can be avoided.

Block adaptive quantization (BAQ) is widely utilized for reducing downlink data rate of spaceborne synthetic aperture radar (SAR). The mutual information upper bond of BAQ compressed data is proposed by means of establishing a mathematical mapping relationship between output signal entropy and input signal saturation degree, using information theoretical analysis method. Threshold saturation degree of input signal for BAQ to be effective are also obtained. Simulation SAR raw data are used to verify the correctness of the mapping relationship.

This paper analyzes an innovative geographically referenced (GR) stripmap mode for the airborne synthetic aperture radar (SAR). In the GR stripmap SAR, the antenna beam illuminates orthogonally with the ground strip, which is not parallel to the SAR trajectory. Benefiting from the GR stripmap mode, the effective observation swath can be enlarged comparing to what can be realized by the traditional stripmap SAR. A modified nonlinear chirp scaling (MNLCS) method is suggested for the GR stripmap SAR imaging. It can solve the problem caused by scatterers' non-uniform Doppler history that disables most traditional imaging algorithms for the GR stripmap SAR. The MNLCS algorithm consists of three main steps. First, a bulk range migration compensation procedure eliminates the linear range migration (range walk). Second, an azimuth perturbation filter unifies the Doppler frequency modulation rate for each range cell. Lastly, a modified chirp scaling processing finishes the data focusing. Performance of the MNLCS algorithm was analyzed, followed by a series of computer simulation results, which validated the MNLCS for the GR stripmap SAR imaging.

This paper investigates the joint use of SAR image and optical image for stereo positioning. To obtain the 3D information of target in the real scene, the geometric relationship between optical radar and SAR are initially established. Then, two angle equations of optical data and a slant range equation of SAR data are jointly utilized to derive the 3D coordinate of target. To further analyze the impact of uncertain measurer errors such as range measurement, orbit, and angle measurement on the novel location model, the partial derivatives of resultant elevation are mainly discussed. Finally, computer simulations are provided to show the error range of the proposed method according to different measurer errors.

The polar format algorithm (PFA) is a wavenumber domain imaging method for spotlight synthetic aperture radar (SAR). The classic fixed-parameter PFA employs interpolation technique for data correction. However, such an operation will induce heavy computational load and cause degradation in computation precision. To optimize image formation processing performance, this study presents a novel parameter-adjusting PFA, which can implement SAR image formation at an extremely highly squint angle with obviously improved computation efficiency and imaging precision. In the parameter-adjusting PFA, radar parameters, such as center frequency, chirp rate, pulse duration, sampling rate, and pulse repeat frequency (PRF), vary for each azimuth sampling position. Due to the parameter adjusting strategy, the echoed signal can be acquired directly in keystone format with uniformly distributed azimuth intervals. In this case, range interpolation, which is necessary in the fixed-parameter PFA to convert data from polar format to keystone format, can be eliminated. Chirp z-transform (CZT) can be employed to focus SAR data along the azimuth direction. Compared with truncated sinc-interpolation, CZT was found to perform better in inducing less phase and amplitude errors in data processing. When residual video phase (RVP) compensation was accomplished for dechirped signal, the processing steps of the parameter-adjusting PFA were simplified as azimuth CZTs and range inverse fast Fourier transforms (IFFT). Lastly, computer simulation of multiple point targets validated the presented approach.

The interpolation-based Polar Format Algorithm (PFA) can be used in bistatic Synthetic Aperture Radar (SAR) image processing while suffering from heavy interpolation computation load and complicated space-dependent resolution. To decrease computation load, this paper presents a nonlinear trajectory-based PFA, in which sensors are designed to fly on conical surface to avoid range interpolation. Due to this conical bistatic geometry, two advantages can be achieved. First, part of computation load can be converted to navigation system and processing speed can be improved. Second, a space-independent range resolution can be approached. A following multi-scatter simulation validates the presented approach.

Spaceborne Synthetic Aperture Radar (SAR) interferometry is a powerful tool for measuring ground movements by exploiting phase difference of SAR images taken at different time. It has been successfully used in studying earth processes such as volcano deformation, tectonic deformation, and land subsidence but rarely applied in landslides. In this paper we aim to monitor the Berkeley Hills landslides by applying advanced interferometry method, Persistent Scatterer Interferometry (PSI) to both Stripmap and Spotlight TerraSAR-X data and compare the results with previous ERS and Radarsat data results.

Block-based processing has shown promise to reduce computation complexity and storage space for image Compressed Sensing. In this paper, a new architecture for SAR images is proposed, as an improvement for traditional Block Compressed Sensing of natural images. The proposed scheme adopts the basic structure of existing Block Compressed Sensing, and studies the character of SAR images. Based on the difference of statistical property among sub blocks, the proposed scheme can adaptively select the number of measurements that needed to take for every sub blocks. Different from equality measurement, adaptive sampling can sufficiently capture the diversity between sub blocks and keep their properties well. Several numeral experiments also demonstrate that the proposed approach outperforms the existing scheme, achieving comparable reconstruction quality via fewer measurements.

This paper improved polar format algorithm (PFA) based on nonuniform azimuth sampling for squint spotlight synthetic aperture radar (SAR) imaging. The range resampling for chirped signal is carried out by chirp z transform (CZT). The novel nonuniform azimuth sampling during the echo data collection enables the utilizing of CZT in azimuth resampling. According to the data collection geometry, the precise expression of phase error induced by wavefront curvature is deduced, and then the overlapped subaperture approach (OSA) is adopted to correct the geometric distortion and defocus arising from the effect of wavefront curvature. Simulation results confirm the validity of the presented approach.

Triple-Channel SAR system can detect moving target, and estimate its range velocity. However, the problems of blind velocity and velocity ambiguity still exit. To resolve these problems, Triple-Channel Multi-Input Multi-Output SAR (Triple-Channel MIMO-SAR) system, with a displaced phase center antenna (DPCA) and interferometry method based on matched Fourier Transform (MFT), is proposed in this paper, which could combine detection and estimation results of different working frequencies and obtain accurate Doppler frequency modulated rate estimation. Using this method, we can not only detect moving target and estimate its range velocity, but also resolve the problems of blind velocity and velocity ambiguity and get accurate azimuth velocity estimation. The effectiveness of this approach is validated by the computer simulation results.

Large, slow moving landslides in the Berkeley Hills cause many damage and pose a potential threat to public safety due to the close proximity of the Hayward Fault. We have been using Differential SAR interferometry (DInSAR) and time-series analysis of SAR data to resolve the rates of the landslide motion. In this paper, we aim to interpret the new satellite TerraSAR-X data in this small landslides area. We have acquired both Stripmap data and Spotlight data. Standard InSAR method as well as Persistent Scatterer InSAR is utilized in the processing.

Terahertz(THz)radiation, which occupies a relatively unexplored portion of the electromagnetic spectrum between mid-infrared and microwave bands, offers innovative sensing and imaging technologies that can provide information unavailable through conventional methods such as microwave and X-ray techniques. Spectroscopy in the terahertz frequency range has demonstrated unique identification of both pure and military-grade explosives. Explosive and illicit drug materials have characteristic THz spectra, a fuzzy neural network for classifying explosives and illicit drugs based on different THz spectra was designed. The designed Classifier can make hard decision and soft decision for identifying 9 patterns of explosives and illicit drugs at the accuracy of 89%, The highly successful result of the experiments, coupled with availability of practical THz systems which operate outside the laboratory environment, indicate that THz technologies are promising for the identification of explosives and illicit drugs.

This paper analyzes the synchronization of a bistatic synthetic aperture radar (SAR) system based upon a geostationary transmitter and small "receive-only" SAR systems mounted on airplanes or unmanned aerial vehicles (UAVs), namely GEO Spaceborne-Airborne Bistatic SAR. This paper will analyze and present our solution of the space synchronization, time synchronization, frequency synchronization and phase synchronization for the GEO Spaceborne-Airborne bistatic SAR respectively. It will first introduce the GEO Spaceborne-Airborne bistatic SAR system and geometry model briefly. Then possible solutions of the system synchronization will be discussed. It will introduce the synchronization scheme based on the direct path between the transmitter and receiver. It uses synchronization modules to realize the time and frequency synchronization. A mathematical model considering the time and frequency synchronization error is given and a phase error analysis is performed. Range and azimuth compressions of a single target are implemented by simulations.

Simulation technique becomes increasingly important with the development of Synthetic Aperture Radar (SAR). It can be applied for many purposes such as testing different imaging algorithms and validating different SAR system design parameters[1]. For improving the precision of simulator determination of the location (mainly refers to latitude) of satellite which illuminates the fixed scene center is reconsidered in this paper. As attitude of satellite strongly affects Doppler parameters, determination of attitude is also discussed for simulated system approaching real system. Although attitude determination based on Doppler centroid was studied in many articles[2][3], this paper utilizes the information about the footprint shape of beam, and develops the equations relating yaw, pitch and especially roll to slant range and Doppler shift of echo data. We can get the attitude of satellite by solving these equations. Then for validating and evaluating the simulated system, this paper describes a novel approach which involves imaging combination of real and simulated echo data. Doppler parameters adopted in imaging algorithm before and after combining are identical. Effect of focalizing simulated echo data indicates whether the simulated system is acceptable, and relative error of geometric distortion which appears in the SAR image reflects the approaching degree of simulated system to real system. Test was conducted by generating simulated data for RADARSAT-1, the result shows the precision of location and attitude determination and validation of this evaluation approach.

This paper starts on the flow of moving target detection in dual channel DPCA system. Firstly the output power density spectrum of moving target and noise in DPCA system is analyzed, and the output SNR is obtained. Then the effect of synthetic aperture time of moving target's echo and azimuth antenna pattern on output SNR in DPCA is discussed in detail. Based on this effect, the paper deduces the expression which describes the variation of output SNR against synthetic aperture time in Dual-Channel DPCA system, where azimuth pattern is Sinc function, and the synthetic aperture time for optimizing the ability of detecting the moving target is obtained. Further more, this method of acquiring the aperture time can be applied for other antenna patterns. It is testified by processed result of simulated data that the relationship between output SNR and synthetic aperture time fits the above conclusion in Dual-Channel DPCA system.

Multi-channel interference elimination technology for Small-Satellites-Borne Distributed Synthetic Aperture Radar (SSBD-SAR) system is discussed in this paper. On the basis of analyzing the spacial difference of jamming signals and the SAR echo signals, we apply the multi-channel interference elimination technology to the SSBD-SAR system. The simulation results testify that this technique can effectively eliminate the jamming signals from the fixed jammer in the SAR observation scenario.

Configuration error for airborne formation flying InSAR was studied. The aircraft interval changes are the most important error. Interval decreasing is taken as an example. Phase changes with baseline changes were derived in formula. The simulation result of plane interval changes is given out. A pentahedron on flat ground is set to show influence of the configuration error. Correct phase compensation is the key technology to get accurate interferogram. So azimuth slope eliminating was adopted. Two control points were arranged in observing area to compensate the phase error introduced by configuration error. This algorithm can improve the DEM precision for whole area. The pentahedron terrain is employed to verify compensation algorithm. The simulation terrain and compensation results prove that the algorithm is effective and efficient.

Because the stability of plane platform is not good, airborne SAR can not acquire the precise orbit parallelism and velocity as spaceborne SAR. Motion error problem for airborne formation flying InSAR is analyzed here. The plane interval changes (across track baseline changes) can be discussed in three situations: interval increasing, interval decreasing, interval changing according to sine curve. Phase changes with baseline changes are deduced quantiticationally. The simulation result of plane interval changes is given out. It can be concluded that across track baseline changes lead to azimuth slope. The digital relation between across-track baseline error and phase error, height error is concluded by simulation experiment result. The paper presents the method of azimuth slope elimination. Azimuth slope eliminating is adopted in simulation terrain. Two control points are set in topographic area to compensate the phase error of baseline changes. This algorithm can improve the DEM precision for whole area. Even if the plane track is curve, the method in this paper can still compensate most of the motion error.

Noise in SAR interferogram brings much trouble in phase unwrapping. It will also influence the accuracy of digital elevation models. Based on realization of complex mean filtering, pivoting mean filtering, pivoting median filtering three noise reduction algorithms, their computations are analyzed and the effect of noise reduction is given out. In order to get the most optimized balance between computation and effect of noise reduction, a new noise reduction idea - second-time or multiple combined noise reduction is proposed. The algorithm can comprehend the merits of several noise reduction methods. It can preserve edge information well and decrease phase noise dramatically at the cost of adding a little computation. Based on computer simulation, certain terrain is set and the effect of noise reduction of new method is verified. The variance of before and after combined noise reduction is given out. The effect of three-time or more combined noise reduction is not obvious because noise has been reduced by second-time noise reduction. We do not recommend 4 or more-time combined noise reduction for its large computation. ERS-frac12 real data are also used to verify the validity of the new algorithm