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。     

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     

基于修正离散Chirp-Fourier变换的高速目标ISAR距离像补偿

分析了高速运动目标的逆合成孔径雷达（ISAR）回波信号模型和高速运动对ISAR信号处理的影响。结果表明,高速运动特征会导致目标一维距离像的畸变和二维像的模糊。为此,提出了一种基于修正离散Chirp Fourier变换（MDCFT）的高速运动目标距离像补偿算法,采用MDCFT谱包络最小Shannon熵准则进行参数估计,可解决幅度最大准则下参数估计性能恶化的问题。仿真结果表明了该距离像补偿算法的有效性。     

Imaging of point scatterers from step-frequency ISAR data

A high-resolution method for imaging of point scatterers from step-frequency inverse synthetic-aperture radar (ISAR) data is presented. An analysis of the noise sensitivity of the method is provided to show the high performance of the method. Simulation results are given to show the robustness of the method against model errors     

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。     

Time-frequency approaches to ISAR imaging of maneuvering targetsand their limitations

Inverse synthetic aperture radar (ISAR) imaging of the noncooperative maneuvering target is a challenging task because of its time variant orientation and rotation velocity which cannot be measured accurately. This correspondence investigates the principles of ISAR imaging of maneuvering targets, and proposes an algorithm for application in situations where the maneuverability is not too severe and the Doppler variation of subechoes from scatterers can be approximated as a first-order polynomial. The imaging results obtained by using real data show the effectiveness of the new method     

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     

Use of genetic algorithms in ISAR imaging of targets with higher order motions

Genetic algorithms (GA) are proposed for inverse synthetic aperture radar (ISAR) imaging. GA is used for motion parameters search in place of exhaustive search in the adaptive joint time-frequency (AJTF) algorithm. While maintaining the same accuracy, GA has lower computational complexity, especially for targets with higher order motions.     

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。     

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     

基于脉冲交错的数字阵列雷达任务优化调度算法

针对数字阵列雷达搜索、跟踪和成像任务的资源调度问题,提出一种数字阵列雷达(DAR)任务的优化调度算法。该算法以脉冲交错技术为基础,在对目标搜索与跟踪的同时,利用基于压缩感知的稀疏孔径认知逆合成孔径雷达(ISAR)成像方法对部分精密跟踪目标成像,并采用观测时间动态调整策略以提高雷达系统的自适应能力。仿真结果表明,与传统雷达资源调度算法相比,该算法可以将成像任务考虑到优化调度模型中并合理分配资源,实现雷达多任务并行的调度,获得更高的资源利用率与期望的成像质量。     

Robust range alignment algorithm via Hough transform in an ISARimaging system

The inverse synthetic aperture radar (ISAR) algorithm for imaging objects moving in a straight line requires range alignment as a preprocessing step since scatterers migrate through the various range bins. The conventional correlation alignment method fails when applied in ground scenarios like an airport due to the clutter environment. A procedure using Hough Transform (HT) alignment is presented which overcomes this disadvantage and provides information for clutter elimination     

双基地角时变下的ISAR等效旋转中心估计

双基地逆合成孔径雷达（ISAR）距离-多普勒算法成像时，容易引起越分辨单元徙动问题，影响成像质量，为了抑制越分辨单元徙动，需要估计目标的等效旋转中心。本文针对双基地角时变下的ISAR等效旋转中心估计问题，提出了一种等效旋转中心估计算法。该算法首先将运动补偿后的一维距离像序列分为两组并分别成像，得到两幅图像；其次，假定某个距离单元为等效旋转中心位置，对两幅图像进行畸变校正，使得两幅图像只存在一个视角差，按视角差旋转其中的一幅图像，并与另一幅图像作相关，得到相关系数；然后，假定下一个距离单元为等效旋转中心位置，重复上述步骤，直至遍历结束，相关系数最大值对应的假定位置就是估计的等效旋转中心。最后进行了仿真对比实验，表明本文算法能够有效估计双基地角时变下的ISAR等效旋转中心位置。     

双基角时变下的空间目标BISAR自聚焦算法

以空间目标为研究对象,针对双基地逆合成孔径雷达(BISAR)成像中双基角变化及同步误差导致的二维ISAR像散焦问题,提出了基于粒子群优化(PSO)的非参数自聚焦算法。算法首先将回波中平动和转动及同步误差等因素导致的相位变化项统一建模,其次将二维图像对比度最大作为优化目标,利用PSO算法对所有高次项相位进行整体优化估计,然后对高阶相位项进行补偿,最后基于补偿后剩余的一阶线性相位项进行方位压缩得到目标的二维ISAR像。算法可解决参数相位误差估计法中因模型误差导致的聚焦精度下降问题,同时也降低了BISAR自聚焦算法的复杂度。通过与参数法自聚焦算法的性能进行对比仿真实验,验证了算法的有效性。     

A new algorithm for the formation of ISAR images

A new technique for implementing the enhanced image processing (EIP) algorithm for the formation of inverse synthetic aperture radar (ISAR) images is presented. The EIP algorithm is required when, during the formation of an image, scattering centers on a target move out of range and/or Doppler resolution cells. This phenomenon is common for high resolution imagery of practical-sized targets. The method presented is based entirely on the fast Fourier transform (FFT) and therefore does not require the interpolation schemes that are prevalent in the standard EIP implementation. A brief review of the theory of radar imaging is presented to establish the notation for the work. Following the presentation of the new algorithm, a simple example is given to demonstrate the effectiveness of the new technique. In addition work is presented that demonstrates the processing required to reduce the sidelobes in imagery generated by the EIP technique     

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。     

Time windowing for highly focused ISAR image reconstruction

In several applications long recorded live inverse synthetic aperture radar (ISAR) data are used to obtain one or more ISAR images. In order to reconstruct a well-focused ISAR image, a suitable selection of the echoes to be coherently processed must be provided. Such a selection can be made by defining a time window. We propose a technique for the automatic selection of the position and length of the time window that provides the ISAR image with the highest focus. The technique, namely the maximum contrast based automatic time window selection (MC-ATWS), is based on the definition of image contrast (IC). Due to the fact that the IC is a measure of the image focus, the time window is selected by maximizing the IC. The technique effectiveness is tested by using simulated and real data.     

Multi-aspect radar target recognition method based on scattering centers and HMMs classifiers

A hidden Markov model (HMM)-based method for recognizing aerial targets according to the sequential high-range-resolution (HRR) radar signature is presented. Its recognition features are the location information of scattering centers extracted from the HRR radar echoes by the relax algorithm. The HMM is used to characterize the spatio-temporal information of a target. Several HMMs are cascaded in a chain to model the variation in the target orientation and used as classifiers. Computer simulations with the inverse synthetic aperture radar (ISAR) data are given to demonstrate that for an open-set recognition, average class-recognition rates of 84.50% and 89.88% are achieved, respectively, under two given conditions.     

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