Method of moving target detection based on sub-image cancellation for single-antenna airborne synthetic aperture radar

The method of moving target detection based on subimage cancellation for single-antenna airborne SAR is presented.First the subimage is obtained through frequency processing is pointed out.The imaging difference of a stationary objects and moving object in the subimage based on the frequency division is analyzed from the fundamental principle.Then the developed method combines the shear averaging algorithm to focus on the moving target in the subimage,after the clutter suppression and the focusing position in each subimage is obtained. Next the observation model and the relative movement of the moving targets between the subimages estimate the moving targets.The theoretical analysis and simulation results demonstrate that the method is effective and can not only detect the moving targets,but also estimate their motion parameters precisely.

Micro-motion effect in inverse synthetic aperture radar imaging of ballistic mid-course targets

For ballistic mid-course targets,in addition to constant orbital motion,the target or any structure on the target undergoes micro-motion dynamics,such as spin,precession and tumbling.The micro-motion characteristics of the ballistic mid-course targets were discussed.The target motion model and inverse synthetic aperture radar(ISAR) imaging model for this kind of targets were built.Then,the influence of micro-motion on ISAR imaging based on the established imaging model was presented.The computer simulation to get mid-course target echoes from static darkroom electromagnetic scattering data based on the established target motion model was realized.The imaging results of computer simulation show the validity of ISAR imaging analysis for micro-motion targets.

Semisupervised heterogeneous ensemble for ship target discrimination in synthetic aperture radar images

Ship detection using synthetic aperture radar(SAR)plays an important role in marine applications.The existing methods are capable of quickly obtaining many candidate targets,but numerous non-ship objects may be wrongly detected in complex backgrounds.These non-ship false alarms can be excluded by training discriminators,and the desired accuracy is obtained with enough verified samples.However,the reliable verification of targets in large-scene SAR images still inevitably requires manual interpretation,which is difficult and time consuming.To address this issue,a semisupervised heterogeneous ensemble ship target discrimination method based on a tri-training scheme is proposed to take advantage of the plentiful candidate targets.Specifically,various features commonly used in SAR image target discrimination are extracted,and several acknowledged classification models and their classic variants are investigated.Multiple discriminators are constructed by dividing these features into different groups and pairing them with each model.Then,the performance of all the discriminators is tested,and better discriminators are selected for implementing the semisupervised training process.These strategies enhance the diversity and reliability of the discriminators,and their heterogeneous ensemble makes more correct judgments on candidate targets,which facilitates further positive training.Experimental results demonstrate that the proposed method outperforms traditional tritraining.

Application of improved equivalent edge currents in synthetic aperture radar imaging

Target modeling and scattering function calculating are important prerequisites and groundwork for the synthetic aperture radar(SAR) imaging simulation.According to the difficult problems that normal methods cannot calculate the scattering function of electrically large object under the condition to wideband,an effective method of improved equivalent edge currents is presented and applied to SAR imaging simulation for the first time.This method improves calculating velocity and has relatively high precision.The concrete steps of applying the method are given.By way of the simulation experiment,the effectiveness of the method is verified.

A Mo LC+Mo M-based G^0 distribution parameter estimation method with application to synthetic aperture radar target detection

The accuracy of background clutter model is a key factor which determines the performance of a constant false alarm rate(CFAR) target detection method. G0 distribution is one of the optimal statistic models in the synthetic aperture radar(SAR) image background clutter modeling and can accurately model various complex background clutters in the SAR images. But the application of the distribution is greatly limited by its disadvantages that the parameter estimation is complex and the local detection threshold is difficult to be obtained. In order to solve the above-mentioned problems, an synthetic aperture radar CFAR target detection method using the logarithmic cumulant(Mo LC) + method of moment(Mo M)-based G0 distribution clutter model is proposed. In the method, G0 distribution is used for modeling the background clutters, a new Mo LC+Mo M-based parameter estimation method coupled with a fast iterative algorithm is used for estimating the parameters of G0 distribution and an exquisite dichotomy method is used for obtaining the local detection threshold of CFAR detection, which greatly improves the computational efficiency, detection performance and environmental adaptability of CFAR detection. Experimental results show that the proposed SAR CFAR target detection method has good target detection performance in various complex background clutter environments.

SAR Moving Target Detection and Imaging Based on WVH Transform

目的针对合成孔径雷达（ＳＡＲ）的运动目标检测和成像提出了一种通用、完整的ＷｉｇｎｅｒＶｉｌｅＨｏｕｇｈ变换（ＷＶＨＴ）．方法基于线积分，将ＷＶＤ和Ｈｏｕｇｈ变换结合起来，推导出ＷＶＨ变换，并利用计算机仿真的ＳＡＲ回波数据对该新ＷＶＨ变换作了验证．结果与结论计算机仿真结果证明了该变换的正确性和有效性．和传统的ＷＶＤＨＴ方法相比，这种基于ＷＶＨＴ的ＳＡＲ运动目标检测和成像的新方法，可以将多目标回波的ｃｈｉｒｐ信号从时间域直接转换到参数域，同时完成了ＷＶＤＨＴ方法中的交叉项抑制和运动参数的估计，进而对多目标成像，简化了处理过程．这种新ＷＶＨ变换还可以应用于其它场合的ｃｈｉｒｐ信号检测中．

Design of synthetic aperture radar low-intercept radio frequency stealth

Not confined to a certain point,such as waveform,this paper systematically studies the low-intercept radio frequency(RF)stealth design of synthetic aperture radar(SAR)from the system level.The study is carried out from two levels.In the first level,the maximum low-intercept range equation of the conventional SAR system is deduced firstly,and then the maximum low-intercept range equation of the multiple-input multiple-output SAR system is deduced.In the second level,the waveform design and imaging method of the low-intercept RF SAR system are given and verified by simulation.Finally,the main technical characteristics of the lowintercept RF stealth SAR system are given to guide the design of low-intercept RF stealth SAR system.

A modified OMP method for multi-orbit three dimensional ISAR imaging of the space target

The conventional two dimensional(2D)inverse synthetic aperture radar(ISAR)imaging fails to provide the targets'three dimensional(3D)information.In this paper,a 3D ISAR imaging method for the space target is proposed based on mutliorbit observation data and an improved orthogonal matching pursuit(OMP)algorithm.Firstly,the 3D scattered field data is converted into a set of 2D matrix by stacking slices of the 3D data along the elevation direction dimension.Then,an improved OMP algorithm is applied to recover the space target's amplitude information via the 2D matrix data.Finally,scattering centers can be reconstructed with specific three dimensional locations.Numerical simulations are provided to demonstrate the effectiveness and superiority of the proposed 3D imaging method.

STUDY ON THE SIGNATURE OF GROUND MOVING TARGET FOR AIRBORNE SQUINT SAR IMAGING

Compared with the side-looking Synthetic Aperture Radar (SAR), the flexible beampointing of squint SAR makes great application value. This paper derives the image signature of the ground moving target after the processing of Range-Doppler (RD) algorithm, the SAR signatures of ground moving targets are analyzed, including the geometry correction, the offsets and defocusing in both range and azimuth direction. Finally, computer simulation results validate its effectiveness. The research results are especially significant for moving targets detection and parameters estimation in squint mode SAR.

Super-resolution reconstruction of synthetic-aperture radar image using adaptive-threshold singular value decomposition technique

A super-resolution reconstruction approach of radar image using an adaptive-threshold singular value decomposition (SVD) technique was presented,and its performance was analyzed,compared and assessed detailedly.First,radar imaging model and super-resolution reconstruction mechanism were outlined.Then,the adaptive-threshold SVD super-resolution algorithm,and its two key aspects,namely the determination method of point spread function (PSF) matrix T and the selection scheme of singular value threshold,were presented.Finally,the super-resolution algorithm was demonstrated successfully using the measured synthetic-aperture radar (SAR) images,and a Monte Carlo assessment was carried out to evaluate the performance of the algorithm by using the input/output signal-to-noise ratio (SNR).Five versions of SVD algorithms,namely 1) using all singular values,2) using the top 80% singular values,3) using the top 50% singular values,4) using the top 20% singular values and 5) using singular values s such that s2≥max(s2)/rinSNR were tested.The experimental results indicate that when the singular value threshold is set as smax/(rinSNR)1/2,the super-resolution algorithm provides a good compromise between too much noise and too much bias and has good reconstruction results.

A novel oil spill detection method from synthetic aperture radar imageries via a bidimensional empirical mode decomposition

Oil spills pose a major threat to ocean ecosystems and their health. Synthetic aperture radar(SAR) sensors can detect oil spills on the sea surface. These oil spills appear as dark spots in SAR images. However, dark formations can be caused by a number of phenomena. It is aimed to distinguishing oil spills or look-alike objects. A novel method based on a bidimensional empirical mode decomposition is proposed. The selected dark formations are first decomposed into several bidimensional intrinsic mode functions and the residue. Subsequently, 64 dimension feature sets are calculated using the Hilbert spectral analysis and five new features are extracted with a relief algorithm. Mahalanobis distances are then used for classification. Three data sets containing oil spills or look-alikes are used to test the accuracy rate of the method. The accuracy rate is more than 90%. The experimental results demonstrate that the novel method can detect oil spills validly and accurately.

A PARAMETER ESTIMATION FOR DETECTION AND IMAGING OF MOVING TARGETS WITH SAR BY WVD

Based on a joint time-frequency two dimensional processing, this paper proposes a method for the detection and imaging of moving targets SAR by using Wigner-Ville Distribution (WVD). It is a parameter estimation method to generate a high resolution image. The problem of WVD in dealing with multi-point targets and extended targets are also discussed. The computer simulation results illustrate its availability.

Inverse synthetic aperture radar range profile compensation of plasma-sheath-enveloped reentry object

The scattering points in a plasma sheath characterized with coupled velocities can cause pulse compression mismatching,which results in displacement and energy diffusion in the onedimension range profile.To solve this problem,we deduce the echo model of the plasma-sheathenveloped reentry object.By estimating the coupled velocities,we propose a compensation method to correct the defocus of an inverse synthetic aperture radar(ISAR)image in range dimension to improve the quality of the ISAR images.The simulation results suggest that the echoes from different regions of the surface of the reentry object have various coupling velocities,and the higher the coupled velocity,the more serious the displacement and energy diffusion in the range dimension.Our proposed method can correct the range dimension aberration.Two measurement metrics were used to evaluate the improvement of the compensation method.

SAR Imaging of Moving Target Based on Quadratic Phase Function

In this paper, a novel signal processing technique hasbeen developed to refocus moving targets image from their smeared responses in the Synthetic Aperture Radar (SAR) image according to the characteristics of the received signals for moving targets. Quadratic Phase Function is introduced to the parameters estimation for moving target echo and SAR imaging. Our method is available even under a low SNR environment and acquiring an exact SAR image of moving targets. The simulated results demonstrated the validity of the algorithm proposed.

ISAR autofocus imaging algorithm for maneuvering targets based on deep learning and keystone transform

The issue of small-angle maneuvering targets inverse synthetic aperture radar(ISAR)imaging has been successfully addressed by popular motion compensation algorithms.However,when the target’s rotational velocity is sufficiently high during the dwell time of the radar,such compensation algorithms cannot obtain a high quality image.This paper proposes an ISAR imaging algorithm based on keystone transform and deep learning algorithm.The keystone transform is used to coarsely compensate for the target’s rotational motion and translational motion,and the deep learning algorithm is used to achieve a super-resolution image.The uniformly distributed point target data are used as the data set of the training u-net network.In addition,this method does not require estimating the motion parameters of the target,which simplifies the algorithm steps.Finally,several experiments are performed to demonstrate the effectiveness of the proposed algorithm.

Approach for ISAR imaging of near-field targets based on coordinate conversion and image interpolation

Inverse synthetic aperture radar(ISAR)imaging of near-field targets is potentially useful in some specific applications,which makes it very important to efficiently produce highquality image of the near-field target.In this paper,the simplified target model with uniform linear motion is applied to the near-field target imaging,which overcomes the complexity of the traditional near-field imaging algorithm.According to this signal model,the method based on coordinate conversion and image interpolation combined with the range-Doppler(R-D)algorithm is proposed to correct the near-field distortion problem.Compared with the back-projection(BP)algorithm,the proposed method produces better focused ISAR images of the near-field target,and decreases the computation complexity significantly.Experimental results of the simulated data have demonstrated the effectiveness and robustness of the proposed method.

Imaging algorithm of multi-ship motion target based on compressed sensing

An imaging algorithm based on compressed sensing(CS) for the multi-ship motion target is presented. In order to reduce the quantity of data transmission in searching the ships on a large sea area, both range and azimuth of the moving ship targets are converted into sparse representation under certain signal basis. The signal reconstruction algorithm based on CS at a distant calculation station, and the Keystone and fractional Fourier transform(FRFT) algorithm are used to compensate range migration and obtain Doppler frequency. When the sea ships satisfy the sparsity, the algorithm can obtain higher resolution in both range and azimuth than the conventional imaging algorithm. Some simulations are performed to verify the reliability and stability.

New method of time-frequency representation for ISAR imaging of ship targets

Inverse synthetic aperture radar (ISAR) imaging of ship targets is very important in the national defense. For the high maneuverability of ship targets, the Doppler frequency shift of the received signal is time-varying, which will degrade the ISAR image quality for the traditional range-Doppler (RD) algorithm. In this paper, the received signal in a range bin is characterized as the multi-component polynomial phase signal (PPS) after the motion compensation, and a new approach of time-frequency representation, generalized polynomial Wigner-Ville distribution (GPWVD), is proposed for the azimuth focusing. The GPWVD is based on the exponential matched-phase (EMP) principle. Compared with the conventional polynomial Wigner-Ville distribution (PWVD), the EMP principle transfers the non-integer lag coefficients of the PWVD to the position of the exponential of the signal, and the interpolation can be avoided completely. For the GPWVD, the cross-terms between multi-component signals can be reduced by decomposing the GPWVD into the convolution of Wigner-Ville distribution (WVD) and the spectrum of phase adjust functions. The GPWVD is used in the ISAR imaging of ship targets, and the high quality instantaneous ISAR images can be obtained. Simulation results and measurement data demonstrate the effectiveness of the proposed new method.

Autofocus technique for ISAR imaging of uniformly rotating targets based on the ExCoV method

The inverse synthetic aperture radar(ISAR) imaging can be converted into a sparse reconstruction problem and solved by the l_1-norm minimization algorithm. The basis matrix in sparse ISAR imaging is usually characterized by the unknown rotation rate of a moving target, thus the rotation rate and the sparse signal should be jointly estimated. Especially due to the imperfect coarse motion compensation, we consider the phase error correction problem in the context of the sparse signal reconstruction. To address this issue, we propose an iterative reweighted method,which jointly estimates the rotation rate, corrects the phase error and reconstructs a high resolution ISAR image. The proposed method gives a gradual and interweaved iterative process to refine the unknown parameters to achieve the best sparse representation for the ISAR signals. Particularly, in ISAR image reconstruction,the l_1-norm minimization algorithm is sensitive to user parameters.Setting these user parameters are not trivial and the reconstruction performance depends significantly on their choices. Then, we consider an expansion-compression variance-component(ExCoV) based method, which is automatic and demands no prior knowledge about signal-sparsity or measurement-noise levels. Both numerical and electromagnetic data experiments are implemented to show the effectiveness of the proposed method. It is shown that the proposed method can estimate the rotation rate and correct the phase errors simultaneously, and its superior performance is proved in terms of high resolution ISAR image.

IMAGING AND MTI PROCESSING BASED ON DUAL-FREQUENCIES DUAL-APERTURES SPACEBORNE SAR

Based on dual-frequencies dual-apertures spaceborne SAR (Synthetic Aperture Radar), a new SAR system with four receiving channels and two operation modes is presented in this paper. SAR imaging and Moving Target Indication (MTI) are studied in this system. High resolution imaging with wide swath is implemented by the Mode I, and MTI is completed by the Mode II. High azimuth resolution is achieved by the Displaced Phase Center (DPC) multibeam technique. And the Coherent Accumulation (CA) method, which combines dual channels data of different carrier frequency, is used to enhance the range resolution. For the data of different carrier frequency, the two aperture inter- ferometric processing is executed to implement clutter cancellation, respectively. And the couple of clutter suppressed data are employed to implement Dual Carrier Frequency Conjugate Processing (DCFCP), then both slow and fast moving targets detection can be completed, followed by moving target imaging. The simulation results show the validity of the signal processing method of this new SAR system.