PHASE AUTOFOCUSING ALGORITHM FOR COMPRESSED INVERSE SYNTHETIC APERTURE RADAR IMAGING

As same as the conventional inverse synthetic aperture radar（ISAR）, the compressed ISAR also requires the echo signal based motion compensation, which consists of the range alignment and the phase autofoeusing. A phase autofocusing algorithm for compressed ISAR imaging is presented. In the algorithm, phase autofocusing for the sparse ISAR echoes is accomplished using the eigenvector method. Experimental results validate the effectiveness of the algorithm.

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.

Distributed inverse synthetic aperture radar imaging of ship target with complex motion

For ship targets with complex motion,it is difficult for the traditional monostatic inverse synthetic aperture radar(ISAR)imaging to improve the cross-range resolution by increasing of accumulation time.In this paper,a distributed ISAR imaging algorithm is proposed to improve the cross-range resolution for the ship target.Multiple stations are used to observe the target in a short time,thereby the effect of incoherence caused by the complex motion of the ship can be reduced.The signal model of ship target with three-dimensional(3-D)rotation is constructed firstly.Then detailed analysis about the improvement of crossrange resolution is presented.Afterward,we propose the methods of parameters estimation to solve the problem of the overlap or gap,which will cause a loss of resolution and is necessary for subsequent processing.Besides,the compressed sensing(CS)method is applied to reconstruct the echoes with gaps.Finally,numerical simulations are presented to verify the effectiveness and the robustness of the proposed algorithm.

A COMPARISON OF SOME ELECTRONIC COUNTERMEASURES ON INVERSE SYNTHETIC APERTURE RADAR (ISAR)

Inverse Synthetic Aperture Radar (ISAR) is an important means for target classification, recognition, identification and many other military applications. A simulation model of ISAR system is established after analyzing the principle of ISAR imaging, and then several ECM (Electronic Counter Measurement) techniques are studied. Simulation experiments are done on the basis of such research. The experimental result of the research can be used for ECM equipment.

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.

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.

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.

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.

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.

Multi-static InISAR imaging for ships under sparse aperture

This paper concentrates on super-resolution imaging of the ship target under the sparse aperture situation.Firstly,a multi-static configuration is utilized to solve the coherent processing interval(CPI)problem caused by the slow-speed motion of ship targets.Then,we realize signal restoration and image reconstruction with the alternating direction method of multipliers(ADMM).Furthermore,we adopt the interferometric technique to produce the three-dimensional(3D)images of ship targets,namely interferometric inverse synthetic aperture radar(InISAR)imaging.Experiments based on the simulated data are utilized to verify the validity of the proposed method.

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.

False-target image synthesizer for countering ISAR via inverse dechirping

For real-time jamming signal generation in deceiving inverse synthetic aperture radar（ISAR）,the target characteristics modulation is always processed in the expensive field programmable gate array（FPGA）.Due to the large computational complexity of the traditional modulating operation,the size and structure of simulated false-target are limited.With regard to the principle of dechirping in range compression of linear frequency modulated（LFM） radar,a novel algorithm named ＂inverse dechirping＂ is proposed for target characteristics modulation.This algorithm only needs one complex multiplier in the FPGA to generate the jamming signal when the radar signal is intercepted,which can be obtained by multiplication of radar signal samplings and the equivalent dechirped target echo in the time domain.As the complex synthesis of dechirped target echo can be realized by cheap digital signal processor（DSP） within the interpulse time,the overall cost of the jamming equipment will be reduced and the false-target size will not be limited by the scale of FPGA.Numerical simulations are performed to verify the correctness and effectiveness of the proposed algorithm.

Entropy function optimization for radar imaging

The convergence performance of the minimum entropy auto-focusing（MEA） algorithm for inverse synthetic aperture radar（ISAR） imaging is analyzed by simulation. The results show that a local optimal solution problem exists in the MEA algorithm. The cost function of the MEA algorithm is not a downward-convex function of multidimensional phases to be compensated. Only when the initial values of the compensated phases are chosen to be near the global minimal point of the entropy function, the MEA algorithm can converge to a global optimal solution. To study the optimal solution problem of the MEA algorithm, a new scheme of entropy function optimization for radar imaging is presented. First, the initial values of the compensated phases are estimated by using the modified Doppler centroid tracking （DCT）algorithm. Since these values are obtained according to the maximum likelihood （ML） principle, the initial phases can be located near the optimal solution values. Then, a fast MEA algorithm is used for the local searching process and the global optimal solution can be obtained. The simulation results show that this scheme can realize the global optimization of the MEA algorithm and can avoid the selection and adjustment of parameters such as iteration step lengths, threshold values, etc.

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 interferometric 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.

CROSS-TRACK THREE APERTURES MILLIMETER WAVE SAR SIDE-LOOKING THREE-DIMENSIONAL IMAGING

The airborne cross-track three apertures MilliMeter Wave (MMW) Synthetic Aperture Radar (SAR) side-looking three-Dimensional (3D) imaging is investigated in this paper. Three apertures are distributed along the cross-track direction, and three virtual phase centers will be obtained through one-input and three-output. These three virtual phase centers form a sparse array which can be used to obtain the cross-track resolution. Because the cross-track array is short, the cross-track resolution is low. When the system works in side-looking mode, the cross-track resolution and height resolution will be coupling, and the low cross-track resolution will partly be transformed into the height uncertainty. The beam pattern of the real aperture is used as a weight to improve the Peak to SideLobe Ratio (PSLR) and Integrated SideLobe Ratio (ISLR) of the cross-track sparse array. In order to suppress the high cross-track sidelobes, a weighting preprocessing method is proposed. The 3D images of a point target and a simulation scene are achieved to verify the feasibility of the proposed method. And the imaging result of the real data obtained by the cross-track three-baseline MMW InSAR prototype is presented as a beneficial attempt.

Compressive Sensing Inverse Synthetic Aperture Radar Imaging Based on Gini Index Regularization

In compressive sensing(CS) based inverse synthetic aperture radar(ISAR) imaging approaches, the quality of final image significantly depends on the number of measurements and the noise level. In this paper, we propose an improved version of CSbased method for inverse synthetic aperture radar(ISAR) imaging. Different from the traditional l1 norm based CS ISAR imaging method, our method explores the use of Gini index to measure the sparsity of ISAR images to improve the imaging quality. Instead of simultaneous perturbation stochastic approximation(SPSA), we use weighted l1 norm as the surrogate functional and successfully develop an iteratively re-weighted algorithm to reconstruct ISAR images from compressed echo samples. Experimental results show that our approach significantly reduces the number of measurements needed for exact reconstruction and effectively suppresses the noise. Both the peak sidelobe ratio(PSLR) and the reconstruction relative error(RE) indicate that the proposed method outperforms the l1 norm based method.

一种联合TDCM和PFA的空间目标大转角ISAR成像方法

空间目标态势感知是当前航天技术领域的研究热点,逆合成孔径雷达(Inverse Synthetic Aperture Radar, ISAR)是空间目标感知的一种有效手段。为了得到利于目标鉴别的高分辨二维ISAR图像,需要通过增大积累转角来提高方位向分辨率。但是,随着转角的增大,平动与转动之间的耦合增大,使得传统的先平动补偿、后利用转动成像的两步式成像方法不再适用。本文提出了一种结合时域信号共轭相乘(Time Domain Conjugate Multiplication, TDCM)处理与极坐标格式算法(Polar Format Algorithm, PFA)的成像算法,首先利用雷达回波的二维相干性,通过TDCM处理进行平动粗补偿,然后借助PFA的插值操作校正大转角引起的散射点越分辨单元走动(Motion Through Resolution Cell, MTRC)并估计目标相对转动参数。通过迭代处理,持续对平动和转动参数进行优化,提升运动补偿效果。仿真验证了所提成像算法的有效性,与传统算法相比,成像聚焦性更好。

Airborne sparse flight array SAR 3D imaging based on compressed sensing in frequency domain

In airborne array synthetic aperture radar(SAR), the three-dimensional(3D) imaging performance and cross-track resolution depends on the length of the equivalent array. In this paper, Barker sequence criterion is used for sparse flight sampling of airborne array SAR, in order to obtain high cross-track resolution in as few times of flights as possible. Under each flight, the imaging algorithm of back projection(BP) and the data extraction method based on modified uniformly redundant arrays(MURAs) are utilized to obtain complex 3D image pairs. To solve the side-lobe noise in images, the interferometry between each image pair is implemented, and compressed sensing(CS) reconstruction is adopted in the frequency domain. Furthermore, to restore the geometrical relationship between each flight, the phase information corresponding to negative MURA is compensated on each single-pass image reconstructed by CS. Finally,by coherent accumulation of each complex image, the high resolution in cross-track direction is obtained. Simulations and experiments in X-band verify the availability.

A fast decoupled ISAR high-resolution imaging method using structural sparse information under low SNR

Inverse synthetic aperture radar (ISAR) image can be represented and reconstructed by sparse recovery (SR) approaches. However, the existing SR algorithms, which are used for ISAR imaging, have suffered from high computational cost and poor imaging quality under a low signal to noise ratio (SNR) condition. This paper proposes a fast decoupled ISAR imaging method by exploiting the inherent structural sparse information of the targets. Firstly, the ISAR imaging problem is decoupled into two sub-problems. One is range direction imaging and the other is azimuth direction focusing. Secondly, an efficient two-stage SR method is proposed to obtain higher resolution range profiles by using jointly sparse information. Finally, the residual linear Bregman iteration via fast Fourier transforms (RLBI-FFT) is proposed to perform the azimuth focusing on low SNR efficiently. Theoretical analysis and simulation results show that the proposed method has better performence to efficiently implement higher-resolution ISAR imaging under the low SNR condition.

ISAR imaging based on improved phase retrieval algorithm

Traditional inverse synthetic aperture radar(ISAR)imaging methods for maneuvering targets have low resolution and poor capability of noise suppression. An ISAR imaging method of maneuvering targets based on phase retrieval is proposed,which can provide a high-resolution and focused map of the spatial distribution of scatterers on the target. According to theoretical derivation, the modulus of raw data from the maneuvering target is not affected by radial motion components for ISAR imaging system, so the phase retrieval algorithm can be used for ISAR imaging problems. However, the traditional phase retrieval algorithm will be not applicable to ISAR imaging under the condition of random noise. To solve this problem, an algorithm is put forward based on the range Doppler(RD) algorithm and oversampling smoothness(OSS) phase retrieval algorithm. The algorithm captures the target information in order to reduce the influence of the random phase on ISAR echoes, and then applies OSS for focusing imaging based on prior information of the RD algorithm. The simulated results demonstrate the validity of this algorithm, which cannot only obtain high resolution imaging for high speed maneuvering targets under the condition of random noise, but also substantially improve the success rate of the phase retrieval algorithm.