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。     

Simultaneous ISAR imaging of group targets flying in formation

This paper proposes a novel inverse synthetic aperture radar(ISAR) imaging method based on second-order keystone transform(KT) and Sandglass transform for group targets flying in a formation with constant accelerated rectilinear motion in the same radar beam. First, range curvature and range walk of each sub-target among group targets are corrected by the second-order KT combined with the quadratic phase term compensation. After range alignment, the signals in each range frequency cell can be modelled as multiple chirp signals and then the Sandglass transform is utilized to cross-range imaging, which transforms the time–frequency distribution of the signals in each range frequency cell into beelines parallel to the slow time axis simultaneously. Finally, cross-range profiles of group targets in each range frequency cell are obtained via a projection of the perk of every scatterer in the two-dimensional accumulation plane onto the frequency axis. The advantage of the proposed method is that it can align range profiles of each sub-target simultaneously and image cross-range profiles directly without separating the returned signals, which simplifies the operation procedure. Simulation results are used to demonstrate the effectiveness of the proposed method.     

表面粗糙的复杂目标全极化ISAR图像快速仿真

为了获取基于模板图像的车辆、飞机等复杂目标识别所需的海量高质量逆合成孔径雷达(ISAR)图像,提出了表面粗糙的复杂目标全极化ISAR图像快速仿真方法。该方法预先对车辆和飞机等复杂目标表面粗糙程度进行分级定量描述,并以改进的射线弹跳法和等效边缘流法快速预估来自目标粗糙表面的镜面反射和多次反射贡献以及细分边缘的绕射贡献,经相干叠加获得目标的精确电磁散射数据,最后进行成像处理得到高质量全极化ISAR图像。标准体、飞机和车辆目标的仿真实验结果验证了该方法的准确性和有效性。     

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     

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.     

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     

CWLFM Radar for Ship Detection and Identification

Continuous wave lineal frequency modulated (CWLFM) radar presents some interesting advantages for coast surveillance and control as well as low probability of interception (LPI). This paper presents real results obtained with a radar prototype and processed with ISAR techniques. Also, results of an automatic ship identification system applied to simulated ISAR images are exposed. Moreover, radar behavior with unfavorable meteorological conditions is discussed     

Motion compensation for ISAR and noise effect

A method of motion compensation for inverse synthetic aperture radar (ISAR) is proposed. The techniques of interpolation, cross correlation, and estimation are used together. Essential to the method is the fact that avoiding cross-range image aliasing due to Doppler ambiguities requires range profiles to be generated at an adequate rate. The effect of noise on motion compensation is studied by means of simulation. The quality of the reconstructed image is used to evaluate the method     

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     

Computer Simulation of Synthetic Aperture Radar Images of Three-Dimensional Objects

A digital simulation of coherent synthetic aperture radar (SAR) images of three-dimensional objects is described. The simulation is intended to produce representative SAR images that would be suitable for image analysis and pattern recognition studies. The procedure involves a modeling of the object using a combination of three-dimensional quadratic shapes yielding a smooth surface representation. The radar images of these models are then computed using physical optics scattering theory. Finite resolution both in range and cross-range direction is incorporated via a theoretical analysis which results in a simple Fourier transform representation of an equivalent "offset" window filter. Examples of the computer simulation for both infinite resolution and blurred or finite resolution are given for a KC-135 aircraft model.     

Separation of target rigid body and micro-doppler effects in ISAR imaging

Micro-Doppler (m-D) effect is caused by moving parts of the radar target. It can cover rigid parts of a target and degrade the inverse synthetic aperture radar (ISAR) image. Separation of the patterns caused by stationary parts of the target from those caused by moving (rotating or vibrating) parts is the topic of this paper. Two techniques for separation of the rigid part from the rotating parts have been proposed. The first technique is based on time-frequency (TF) representation with sliding window and order statistics techniques. The first step in this technique is recognition of rigid parts in the range/cross-range plane. In the second step, reviewed TF representation and order statistics setup are employed to obtain signals caused by moving parts. The second technique can be applied in the case of very emphatic m-D effect. In the first step the rotating parts are recognized, based on the inverse Radon transform (RT). After masking these patterns, a radar image with the rigid body reflection can be obtained. The proposed methods are illustrated by examples     

Radar target classification of commercial aircraft

With the increased availability of coherent wideband radars there has been a renewed interest in radar target recognition. A large bandwidth gives high resolution in range which means target discrimination may be possible. Coherence makes cross-range resolution and radar images possible. Some of the problems of classifying high resolution range profiles (HRRPs) are examined and simple preprocessing techniques which may aid subsequent target classification are investigated. These techniques are applied to HRRP data acquired at a local airport using the Microwave Radar Division (MRD) mobile radar facility It is found that Boeing 727 and Boeing 737 aircraft can be reliably distinguished over a range of aspect angles. This augers well for future target classification studies using HRRPs     

基于稀疏表示的多雷达信号二维融合处理

多雷达信号融合通过对多视角和多频带雷达信号进行相干融合,可以提高图像的距离和方位向分辨率.为了克服基于谱估计的多雷达信号融合方法稳健性严重依赖于散射点个数估计精度和二维极点配对精度的问题,在深入研究逆合成孔径雷达(ISAR)信号的基础上,构造了多雷达信号二维融合的线性表示模型,将融合处理转化为一个信号表示问题;充分挖掘...     

Autofocusing of ISAR images based on entropy minimization

A novel autofocusing technique is developed for random translational motion compensation in inverse synthetic aperture radar (ISAR) imaging of objects. This technique is based on an entropy minimization principle and validated via a nonparametric estimation method. Images of a simulation and a real flying aircraft are used for illustration. Images of encouraging quality confirm the feasibility of autofocusing the radar images by just the requirement of minimizing the image entropy     

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     

Atomic Decomposition for Radar Applications

In this paper, we explore the promising capabilities of atomic decomposition (AD) for radar-related applications from a practical point of view. Some enhancements and new approaches are proposed herein, and their implementations are fully detailed. We apply the AD algorithms in two different environments, for signal detection where high sensitivity is the main requirement, and for inverse synthetic aperture radar (ISAR) imaging where focused images, target feature extraction, and computational burden are the fundamental concerns.     

Feature enhancement and ATR performance using nonquadratic optimization-based SAR imaging

We present an evaluation of the impact of a recently proposed synthetic aperture radar (SAR) imaging technique on feature enhancement and automatic target recognition (ATR) performance. This image formation technique is based on nonquadratic optimization, and the images it produces appear to exhibit enhanced features. We quantify such feature enhancement through a number of criteria. The findings of our analysis indicate that the new feature-enhanced SAR image formation method provides images with higher resolution of scatterers, and better separability of different regions as compared with conventional SAR images. We also provide an ATR-based evaluation. We run recognition experiments using conventional and feature-enhanced SAR images of military targets, with three different classifiers. The first classifier is template based. The second classifier makes a decision through a likelihood test, based on Gaussian models for reflectivities. The third classifier is based on extracted locations of the dominant target scatterers. The experimental results demonstrate that the new feature-enhanced SAR imaging method can improve the recognition performance, especially in scenarios involving reduced data quality or quantity.     

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。     

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