Quantitative SNR analysis for ISAR imaging using jointtime-frequency analysis-Short time Fourier transform

V.C. Chen recently presented an inverse synthetic aperture radar (ISAR) imaging technique using the joint time-frequency analysis (JTFA), which has been shown having a better performance for maneuvering targets over the conventional Fourier transform method. The main reason is because the frequencies of the radar returns of the maneuvering targets are time varying and a JTFA is a technique that is suitable for such signals, in particular a JTFA may concentrate a wideband signal, such as a chirp, while it spreads noise. We quantitatively study the signal-to-noise ratio (SNR) in the ISAR imaging using one of the typical JTFA techniques, namely the short time Fourier transform (STFT). We show that the SNR increases in the joint time-frequency (TF) domain over the one in the time or the frequency domain alone both theoretically and numerically. This quantitatively shows the advantage of the JTFA technique for the ISAR imaging     

ISAR非平稳目标成像时间和转速联合估计方法

针对逆合成孔径雷达(ISAR)非平稳目标成像,提出基于两特显点相位联合估计成像时间和转速的方法,并得到了转速与相位斜率差(PSD)的解析表达式.首先,基于两个特显点距离单元估计目标转动相位,根据不同时间段转动相位线性度(PLD)选择成像时间.其次,在适合成像的时间段,将成像时间等分成两段,分别提取两段时间内转动相位的斜...     

ISAR imaging of targets at low elevation angles

The problem of inverse synthetic aperture radar (ISAR) image reconstruction of targets at low elevation angle is considered. In this geometric condition the main causes affecting the reconstructed ISAR image are the multipath effect due to the reflection of the Earth's surface and the angular motions of the target produced by external action like wind, fast maneuvering, and sea waves as in the case of ships. The aim of this work is to analyze the effects that the multipath and the target angular motions jointly produce on the ISAR image. The results show that multipath generates some artifacts in the image whereas the target oscillations undergo a spatial-dependent blurring of the point spread function of the ISAR system. These theoretical results are validated by presenting some numerical examples relevant to aircrafts and ships in rectilinear or circular motion. A wide discussion on possible solutions of this problem is made in the conclusion     

Automatic recognition of ISAR ship images

Inverse synthetic aperture radar (ISAR) produces images of ships at sea which human operators can be trained to recognize. Because ISAR uses the ship's own varying angular motions (roll, pitch, and yaw) for cross-range resolution, the viewing aspect and cross-range scale factor are continually changing on time scales of a few seconds. This and other characteristics of ISAR imaging make the problem of automatic recognition of ISAR images quite distinct from the recognition of optical images. The nature of ISAR imaging of ships, and single-frame and multiple-frame techniques for segmentation, feature extraction, and classification are described. Results are shown which illustrate a capability for automatic recognition of ISAR ship imagery     

基于AR模型参数双谱估计的超分辨ISAR成像

利用双谱分析方法，用非高斯AR模型对雷达目标回波信号进行参数化双谱估计，并在此基础上对数据进行外推处理，然后对数据进行ISAR成像。仿真和实测数据实验表明，本文的处理方法比传统的ISAR成像分辨力有明显的提高，且运算量不大，满足ISAR的实时或者准实时成像要求。     

An efficient 3-D near-field ISAR algorithm

This paper presents a new three-dimensional (3-D) near-field inverse synthetic aperture radar (ISAR) imaging technique. A 3-D ISAR image can be obtained by processing coherently the backscattered fields as a function of the frequency and two rotation angles about axes which are mutually orthogonal. Most of the existing ISAR algorithms are based on the Fourier transform and as such can tolerate only small amounts of wavefront curvature. Wavefront curvature must be taken into account when imaging an object in the near-field. Near-field ISAR imaging of large objects using a direct Fourier inversion may result in images which are increasingly unfocused at points which are more distant from the center of rotation. An algorithm based on an azimuth convolution between a near-field focusing function and the frequency domain backscattered fields is discussed. This convolution is efficiently implemented by using fast Fourier transform (FFT) techniques. Furthermore, in order to further alleviate the computational load of the algorithm, the discrete Fourier transform (DFT) of the focusing function is evaluated by means of the stationary phase method. Experimental results show that this technique is precise and virtually impulse invariant     

基于拖曳式干扰机的ISAR微动散射波干扰方法

通过对微多普勒效应的研究,提出了一种新的逆合成孔径雷达（ISAR）散射波干扰方法。将拖曳式干扰机和ISAR接收机分别等效为双基ISAR的发射站和接收站,干扰机对截获的ISAR信号进行微动信息调制并转发至目标,由其散射至ISAR接收机产生散射波干扰效果。干扰信号经ISAR接收机处理后可在真实目标回波成像结果附近产生假目标,且在方位向形成干扰条带。实验结果表明：通过控制干扰机转发参数及微动调制参数可分别实现不同的压制干扰效果。由于拖曳式干扰机与目标距离较近,干扰信号可获得较大功率,且与真实目标回波相参,可获得ISAR二维脉冲压缩处理增益,与传统射频噪声压制干扰方法相比成本较小。     

一种弹道导弹多目标时频分析ISAR成像算法及仿真

在研究多目标ISAR成像回波信号的基础上,提出了一种基于谱图重排的时频分析ISAR成像算法,针对同一距离单元内不同径向速度和不同微动状态两种情况的弹道导弹多目标ISAR成像问题进行了新算法的仿真研究。仿真结果表明,这种成像方法具有优良的时频聚焦性能,证明了该方法的有效性。     

双基地角时变下的ISAR稀疏孔径自聚焦成像

针对双基地角时变下的逆合成孔径雷达（ISAR）成像分辨率低以及稀疏孔径存在相位误差引起图像散焦等问题,提出了一种基于贝叶斯压缩感知（BCS）的双基地ISAR稀疏孔径自聚焦高分辨成像算法。在平动补偿后回波数据的基础上,首先构造补偿相位将由双基地角时变引起的多普勒偏移补偿掉,然后构造随双基地角变化的稀疏基矩阵,建立基于压缩感知的双基地ISAR稀疏孔径观测模型,并将相位误差作为ISAR成像的模型误差,接着假设目标图像各像元服从Laplace先验、噪声统计特性服从Gaussian分布,利用贝叶斯推理进行"分布式"迭代求解,在高分辨成像的同时实现了相位自聚焦,仿真结果验证了算法的有效性和优越性。     

High resolution reconstruction of ISAR images

A 2-D high-resolution spectral analysis algorithm with application to an inverse synthetic aperture radar (ISAR) imaging, is presented. This algorithm is based on two-dimensional linear prediction using autoregressive (AR) coefficients. Stability is guaranteed by AR process pole adjustment. An ISAR target is modeled for a complex scatterer geometry. Computer simulation results are provided for the high-resolution reconstruction of ISAR images     

Imaging of target with complicated motion using ISAR system based on IPHAF-TVA

The technique of imaging a target with a complicated motion using an Inverse Synthetic Aperture Radar (ISAR) system is an effective tool in the field of radar signal processing. After the translational compensation, the received signal reflected from the target can take the form of a multi-component Polynomial Phase Signal (m-PPS), and the high quality ISAR image can be provided via the combination between the estimated parameters of the m-PPS and the Range Instantaneous-Doppler technique (RID). For a target with a high maneuvrability, the occurrence of scatterers Migration Through Resolution Cell (MTRC), caused by the rotational movement could be appearing. That is why the variation in the amplitude of the echo during the time of observation cannot be neglected. The purpose of this study is the parameters estimation of the m-PPS signal with order three in the case of the Time Varying Amplitude (TVA). The Improved-version of the Product High-order Ambiguity Function (IPHAF) with TVA is proposed to improve the quality of the ISAR image compared with traditional techniques based on a constant amplitude; the experimental outcomes confirm that the new IPHAF-TVA method presented in this study is an effective technique to make the ISAR image very clear.     

Precision tracking algorithms for ISAR imaging

The simultaneous imaging and tracking of a moving target is one of the most difficult problems in inverse synthetic aperture radar (ISAR) signal processing. The problem is addressed here using a two-antenna imaging radar. The target range shift is sensed with an exponentially averaged envelope correlation algorithm while the angle change is measured with a differential phase shift algorithm. The three state Kalman filters are used in range and azimuth dimensions to provide both a filtered estimate and a one-sample-ahead prediction for the purpose of target tracking. The filtered range shift provides an accurate information for range bin alignment, and the target angle change provides the angular positions of the synthetic array elements. Therefore, the ISAR imaging simply becomes processing of a circular-arc aperture. The algorithms are verified both by computer simulations and also with experimental data processing     

基于虚拟慢时间的双基地ISAR成像算法

针对双基地角时变引起的逆合孔径雷达（ISAR）图像畸变和散焦问题，提出了一种基于虚拟慢时间的成像算法。首先，分析了双基地角时变对ISAR成像的影响机理。然后，基于图像对比度最大准则估计等效旋转中心位置，完成初次相位补偿。最后，通过虚拟慢时间构建基于非均匀虚拟采样的补偿系数矩阵，并通过方位向非均匀傅里叶变换得到目标的ISAR像。算法基于图像对比度最大准则解决等效旋转中心位置估计问题，通过虚拟慢时间消除转动相位项的高次项影响，利用非均匀傅里叶变换解决随机虚拟采样的谱估计问题。理论分析和仿真结果验证了算法的有效性和鲁棒性。     

机动目标的逆合成孔径雷达成像

 逆合成孔径雷达(ISAR)和合成孔径雷达 (SAR)都是利用目标 (场景)与雷达的相对运动,提高横向分辨率,实现对目标 (场景 )的成像。SAR的运动方是雷达平台,可控制作平稳飞行,且用仪器测校其偏离误差;ISAR的运动方通常是非合作目标,运动不受控制,且难以精确测量。当目标作机动飞行时,以目标作固定基准,雷达等效地在空间形成流形复杂的逆合成孔径 (阵列 ),对这种情况下成像的问题进行了系统的研究。     

线性调频步进雷达ISAR信号特性及成像

文章在建立了线性调频步进ISAR回波信号模型的基础上,对线性调频步进雷达ISAR信号特性进行了详细的分析,指出了由径向速度和转动速度所引起的耦合项、一次项和二次项对距离合成高分辨和方位聚焦的影响;给出了线性调频步进雷达ISAR成像的详细步骤,并用仿真论证了文章分析的可靠性。     

Robust autofocus algorithm for ISAR imaging of moving targets

A robust autofocus approach, referred to as AUTOCLEAN (AUTOfocus via CLEAN), is proposed for the motion compensation in ISAR (inverse synthetic aperture radar) imaging of moving targets. It is a parametric algorithm based on a very flexible data model which takes into account arbitrary range migration and arbitrary phase errors across the synthetic aperture that may be induced by unwanted radial motion of the target as well as propagation or system instability. AUTOCLEAN can be classified as a multiple scatterer algorithm (MSA), but it differs considerably from other existing MSAs in several aspects: (1) Dominant scatterers are selected automatically in the 2D image domain; (2) scatterers may not be well isolated or very dominant; (3) phase and RCS information from each selected scatterer are combined in an optimal way; (4) the troublesome phase unwrapping step is avoided. AUTOCLEAN is computationally efficient and involves only a sequence of FFTs. Another good feature associated with AUTOCLEAN is that its performance can be progressively improved by assuming a larger number of dominant scatterers for the target. Numerical and experimental results have shown that AUTOCLEAN is a very robust autofocus tool for ISAR imaging     

方位维逆合成孔径雷达(ISAR)运动补偿成象中的预加处理

在方位维逆合成孔径雷达（ISAR）运动补偿成象中,为了获得方位维的高分辨力,需要处理的数据量很大。预加处理首先对原始数据进行频移和滤波,然后由滤波后的数据进行抽取,从而大大压缩了所需处理的数据,减小了运动补偿和成象的计算量,提高了成象处理速度。电磁仿真数据和外场实测数据的处理结果验证了预加处理的有效性。     

一次相消技术在雷达成像中的应用

一次相消技术是一种经典的固定点目标对消方法。本文讨论了在ISAR成像处理过程中利用一次相消技术来剔除地杂波,分析了在成像处理中的杂波相消方法,并在最后的计算机仿真中,验证了该方法的有效性,分别比较了两种成像方式、两种地杂波分布的成像结果。     

基于稀疏分解的空间目标双基地ISAR自聚焦算法

空间目标双基地逆合成孔径雷达（ISAR）成像中,双基地角时变会造成二维图像的散焦。针对此问题,在三大同步理想可实现的条件下,以平稳空间目标为研究对象,分析了空间目标双基地ISAR成像原理,研究了双基地角时变对二维图像散焦的影响机理,提出了利用稀疏分解实现高精度自聚焦的算法。首先,将半双基地角的余弦进行泰勒展开;其次,结合目标的平动及转动条件,将成像相位项用多项式建模;然后,利用稀疏分解算法估计多项式的二次项系数,据此构建补偿项完成相位补偿。算法利用L-曲线准则选取正则参数,基于目标尺寸的先验信息构建冗余基的高分辨因子,利用推广的正则化欠定系统聚焦求解（FOCUSS）算法实现稀疏表示系数的估计,在恰当选取词典分辨率的条件下,算法可实现二次相位项的精确补偿,仿真实验验证了算法性能优于常用的非参数化自聚焦算法。     

High resolution 3D “snapshot” ISAR imaging and featureextraction

We have developed a new formulation for three dimensional (3D) radar imaging of inverse synthetic aperture radar (ISAR) data based on recent developments in high resolution spectral estimation theory. Typically for non real-time applications, image formation is a two step process consisting of motion determination and image generation. The technique presented focuses on this latter process, and assumes the motion of the target is known. The new technique offers several advantages over conventional techniques which are based on the correlation imaging function. In particular, the technique provides for a direct 3D estimate (versus back projection to a 3D target grid matrix) of the locations of the dominant scattering centers using only a minimum set of independent 2D range-Doppler ISAR “snapshots” of the target. Because of the snapshot nature of the technique, it is particularly applicable to 3D imaging of sectors of sparse-angle data, for which the sidelobes of the correlation imaging integral become high. Furthermore, the technique provides for an estimate of amplitude and phase of each scattering center as a function of aspect angle to the target, for those aspect angles which encompass the set of 2D range-Doppler snapshots. Results illustrating the technique developed are presented for both simulated and static range data