Search

Global navigation satellite system (GNSS) and interferometric synthetic aperture radar (InSAR) data are integrated to extract the 3-D surface deformations, which are of great significance for studying geological hazards. In this study, two major problems are focused on integration. For one thing, we propose an iterated almost unbiased estimation (IAUE) method to estimate the variance components of GNSS and InSAR for the case where the estimation of variance components of multisource data by traditional variance component estimation methods may be negative and inaccurate. For another, considering that heterogeneous data errors may lead to unstable 3-D solutions, we propose adding the Laplacian smoothness constraint (LSC) to the function model, which can smooth the solutions by minimizing the second derivative of the displacements. These two methods are abbreviated as IAUE-LSC. In the simulation experiment, the performance of traditional Helmert variance component estimation is first compared with IAUE. IAUE can not only converge more quickly, but also avoid negative variances. Furthermore, we find that the excessively large relative error ratio between GNSS and InSAR is an essential factor leading to the instability of the 3-D solutions. The IAUE-LSC method is immune to this instability and can obtain more stable results. In addition, the 2018 Hawaii case demonstrates that IAUE achieves improvements of 2.58, 2.77, and 7.69 cm in the east, north, and up directions relative to the traditional weighted least-squares method, while the combined IAUE-LSC achieves improvements of 2.29, 0.32, and 1.68 cm compared to the IAUE alone.

The rotation matching between synthetic aperture radar (SAR) and optical images is essential for their registration. In this article, we introduce a novel fast rotation matching method for SAR and optical images. In the method, the absolute directional derivative histograms (ADDHs) of SAR and optical images can be used to reflect the rotation difference between them, and then the rotation difference is removed by the cross correlation of the two images’ ADDHs. Subsequently, we generate the ADDHs by oriented Gaussian-Gamma-shaped operator. Then, the cross correlation based on fast Fourier transform is used to deal with the ADDHs of SAR and optical images in order to determine the rotation difference of the two images. The experiment results demonstrate that the proposed method can detect the rotation difference in various conditions and achieves rotation matching with high speed.

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.

The existing microwave remote sensors for ocean wave observation, such as SAR and spectrometer, have their respective specialties through different measuring mechanisms. However, every individual sensor shows obvious limitations when considering advanced wide-swath complete-elements ocean wave observation. This paper proposes an integrated microwave remote sensor for double-mode ocean wave observation, and designs the main system parameters and the joint time sequence. The double-mode integrated microwave remote sensor adopts a digital array antenna, but functions as a spectrometer and a SAR simultaneously through multiple beam forming technology. The proposed double-mode integrated microwave remote sensor not only realizes simultaneous, wide-swath, relatively complete-elements, and high-accuracy observation, but also reduces the cost, and compared to traditional single satellite multi-payload systems, it is more probable.

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.

The traditional low voltage ride through (LVRT) control method is mainly adjusted from the inside of the new energy field station. Generally, by improving the Crowbar circuit or optimizing the excitation control of the converter, the renewable energy can be operated without offline at a low voltage and reduce its reactive power absorption to the system. Based on the current LVRT status, this paper proposes a DFIG control strategy during LVRT, and introduces the sensitivity coefficient to calculate the influence factor of the wind farm on the faulty node in the regional network to optimize the reactive power distribution of the wind farm near the faulty node. This stable working state of DFIG during LVRT speeds up the recovery speed of the system after it breaks away from the fault. The simulation analysis on the Yunnan regional power grid verifies the feasibility and superiority of the theory, and provides a new idea for the control strategy of renewable energy during LVRT.

Inverse synthetic aperture radar (ISAR) imaging has been widely developed and applied in many applications, such as, radar target recognition, autopilot and seaport ship surveillance, etc. However, low signal-to-noise ratio (SNR) environments may impede conventional range profiles-based translational motion compensation (TMC), causing image degradation. In this paper, a novel method combining profiles and phase is proposed which utilizes two-dimensional (2-D) coherent accumulation to overcome the low SNR problem, even when the range profiles are submerged into noise. The method only requires Fast Fourier transform (FFT) and Hadamard multiplication operations which renders it suitable for real-time applications. Simulation results are provided to validate the performance of the proposed TMC method compared with the state-of-art TMC methods.

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

The rapidly increasing demand on high-resolution ISAR images causes ISAR imaging to become more sensitive to errors. This leads to the invalidation of plane wave assumption and causes geometric distortion and defocus of the traditional imaging algorithms. To address this problem, a new algorithm for near-field ISAR imaging is proposed which focuses the image in two-dimensional (2-D) time-domain without distortion. To that end, a sub-aperture-based method is first applied to restore the invariance in azimuth (IIA). By fixing the rotational angle in a sub-aperture to a constant value, we proceed to compensate for the position-dependent error in the sub-aperture wavenumber domain for full image restoration. The range cell migration correction (RCMC) is performed by Stolt interpolation in the wavenumber domain. Finally, the final image is obtained by a 2-D inverse Fourier transform. Simulated and real data processing results validates the effectiveness of the proposed algorithm.

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.

Ghost targets occur when moving targets are processed as stationary scene in the high-resolution and wide-swath azimuth multichannel SAR system, so moving targets require special treatment. Combining the subspace theory with the system, this paper proposes a clutter suppression method and a moving target radial velocity estimation method. The proposed clutter suppression method does not need pre-processing and it preforms better than the spacetime adaptive processing when the moving target component occupies a large proportion in the received data. And the proposed velocity estimation method has lower time complexity than the method based on the minimum entropy, so it is appropriate for the time sensitive applications. The processing of the airborne measured data verifies the effectiveness of the methods.

High squint multichannel (HSMC) synthetic aperture radar (SAR) mounted on high speed maneuvering platforms is an available mode to achieve wide swath imaging. However, the traditional multichannel reconstruction methods are not suitable because of range-dependent and time-variant steering vector caused by the nonlinear trajectory. To address the issue, a novel unambiguous signal reconstruction algorithm is proposed in this paper. According to the geometry model, the properties of range-dependent and time-variant steering vector are analyzed. Then, a range-dependent and time-variant inter-channel phase compensation method is proposed to correct the space time spectrum, and the constant steering vector is obtained. Before the reconstruction, the range walk correction (RWC) is performed to remove the mismatch between the reconstruction filters and the squinted signal. Furthermore, a modified spatial domain filter is proposed to reconstruct the unambiguous Doppler spectrum. Finally, simulation results are presented to validate the proposed approach.

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.

The curved trajectory and long synthetic aperture time of medium-earth-orbit (MEO) synthetic aperture radar (SAR) lead to a two-dimensional spatial variation in the signals. Traditional methods treat the range and azimuth variations separately, and usually suffer from high computational complexities. We investigate the Doppler rate distribution across a large scene, and exploit an optimal imaging coordinate system, in which the MEO SAR signals satisfy the azimuth-shift-invariant property. The additional processing of the azimuth spatial variation in MEO SAR imaging algorithms can be avoided, and the efficiency of the image formation processor can be improved. Finally, processing of simulated stripmap-mode data with 2-m resolution can validate the proposed algorithm.

ISAR 2D imaging is obtained by projecting the 3D structure target onto a 2D imaging plane. The angle between the imaging plane and the target spinning axis has a great influence on the projection result. Generally, this angle is neglected, which results in the target imaging has smaller size than the real target. This is not conducive to the further application of target detection and target recognition. In a short observation time, this angle cannot be estimated by monostatic radar. In order to solve such a problem, this letter proposes a method using bistatic radar to estimate the angle and accomplish accurate calibration. First, bistatic ISAR model and bistatic echo signal of spinning target are modeled. Then combining monostatic and bistatic 2D imaging, the angle can be calculated based on several prominent scatterers. Recalibration is performed based on this angle. Finally, the effectiveness of the proposed method is verified by different simulation experiments.

Because of computing and storage limitation of one satellite, it is difficult to process large amounts of data of spaceborne synthetic aperture radars. A new method for networked satellites data processing based on intersatellite cloud computing system (ICCS) using a “stage-by-stage” CS algorithm is proposed in this paper, which is built with FPGA chips as the computing kernel of the system. Different from the traditional CS algorithm processing, the system divides data processing into three stages. The computing tasks are reasonably allocated to different data processing units (i.e. satellites) in each stage. The method effectively saves computing and storage resources of satellites, improves the utilization rate of a single satellite, and shortens the data processing time. GF-3 satellite SAR raw data is processed by the system, with the performance of the method verified.

Intelligentization is the trend of the development of SAR system. On the basis of cognitive radar, the concept of intelligent SAR system is discussed from the perspective of application and development of SAR system. Starting from the source of optimization of target information extraction, the architecture of Networked Intelligent SAR system and single system intelligent SAR are presented, and the key technologies involved are analyzed.

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.