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     

Joint time-frequency transform for radar range-Doppler imaging

Conventional radar imaging uses the Fourier transform to retrieve Doppler information. However, due to the complex motion of a target, the Doppler frequency shifts are actually time-varying. By using the Fourier transform, the Doppler spectrum becomes smeared and the image is blurred. Without resorting to sophisticated motion compensation algorithms, the image blurring problem can be resolved with the joint time-frequency transform. High-resolution time-frequency transforms are investigated, and examples of applications to radar imaging of single and multiple targets with complex motion are given     

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.     

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     

Novel Approach for ISAR Image Cross-Range Scaling

Inverse synthetic aperture radar (ISAR) imaging systems produce electromagnetic images of targets in the range-Doppler domain. In order to rescale the image in a homogeneous range-cross range domain (meters by meters), the modulus of the target effective rotation vector must be known. Although in some cases it can be retrieved by means of ancillary data, in most cases the modulus of the target effective rotation vector must be estimated. A blind technique is proposed for estimating the modulus of the target effective rotation vector that exploits information carried by the chirp rate of scattering centres. A technique based on image segmentation, local polynomial Fourier transform (LPFT), and image contrast (IC) maximisation is used in order to extract the scattering centres and estimate their chirp rate. Simulated and real data analyses are provided to confirm the effectiveness of the proposed algorithm.     

利用分数阶Fourier域滤波的机载SAR多运动目标检测

 强度相差较大的多运动目标检测是机载合成孔径雷达 ( SAR)技术的一个重点和难点,传统的频域滤波和现代的时频分布方法都无法解决这个问题。首先分析了机载 SAR运动目标回波本质上为线性调频信号,据此提出一种基于分数阶 Fourier域滤波的运动目标检测新方法,并且应用逐次消去的思想有效地解决了强度相差较大的多目标检测问题。仿真的结果验证了算法的有效性。     

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...     

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FRFT的雷达信号chirp基稀疏特征提取 及分选

 特征分析是雷达信号分选识别的基础,利用稀疏分解思想对新体制雷达信号进行特征提取是一个新的研究方向。本文以分数阶Fourier变换的核函数作为稀疏分解的chirp基函数,将具有相近特征参数的chirp基函数构成基函数族用于稀疏分量提取,推导了在分数阶Fourier域基于匹配跟踪的chirp基函数族稀疏分解公式,然后利用chirp基稀疏分量的调频率和初始频率构成特征参数序列,将雷达信号脉冲分成5大类进行分选和识别,仿真分析验证了推导结果的有效性。结果表明对于具有线性或曲线时频特征的雷达信号在信噪比为-3 dB,采样频率为500 MHz,观测时间为2 μs,调频率不超过100 MHz/μs时,仍然具有95%的正确分选概率。     

基于周期FRFT的多分量LFMCW雷达信号分离

 多分量线性调频连续波(LFMCW)信号的截获和特征提取是雷达情报侦察的难点,为了实现对多分量LFMCW信号的快速检测和有效分离,提出了一种基于周期分数阶Fourier变换(PFRFT)的多分量LFMCW雷达信号分离新方法。首先介绍了PFRFT,分析了PFRFT和FRFT之间的关系,讨论了LFMCW信号的PFRFT特征。然后给出了一种离散PFRFT的计算方法,结合周期分数阶Fourier域(PFRFD)的窄带滤波和CLEAN算法实现了多分量LFMCW信号的分离。仿真结果表明:①PFRFT的计算效率较周期Wigner-Hough变换(PWHT)具有明显优势;②LFMCW信号分量在特定PFRFD中具有能量峰值,分离后能较好保留时频特征;③当两个LFMCW信号分量的功率相差较大时,适合在PFRFD分离,反之适合在时域分离;④当信噪比(SNR)为0 dB时,两个具有相同功率的LFMCW信号分量分离后,与初始信号分量的相关系数都达到了0.9以上。     

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.     

高斯非平稳机动目标波达角模型及跟踪

在实际的跟踪情况中,由于环境条件、目标反射截面等因素的变化,回波信号的功率会随时间变化,即不满足通常阵列信号处理中对高斯信号作平稳性的假设。针对复杂运动条件下高斯非平稳目标的跟踪问题,提出了一种新的机动目标波达角(DOA)模型。该模型全面地刻画了高斯非平稳机动目标的动态,并将目标的DOA和信号功率作为状态变量进行了联合考虑,同时运用虚拟阵列的表示方法构建了相应的观测方程。对于建立的新模型,最后采用无迹卡尔曼滤波(UKF)的框架完成了整个跟踪算法。分析和仿真结果表明,当高斯非平稳机动目标之间存在长时间相互接近的情况时,新方法仍然可以获得较好的跟踪性能。     

基于二维资源管理的多功能雷达任务调度算法

动态孔径分割技术为相控阵雷达针对不同任务灵活分配孔径资源提供了可能,而传统的资源调度方法仅基于单一孔径条件研究了时间资源的优化分配问题。针对雷达搜索、跟踪与成像任务的自适应调度问题,提出了一种基于时间-孔径二维资源管理的雷达资源调度算法。该算法建立了雷达孔径分割条件下的二维资源调度模型,确立了能量资源约束条件;利用基于压缩感知的稀疏孔径逆合成孔径雷达（ISAR）成像技术,使雷达在完成目标搜索和跟踪任务的同时实现对目标的成像;定义了调度算法性能的评价指标。在仿真实验中将该算法与另外2种算法进行对比,验证了所提算法在高度成功率、二维资源利用率与任务并行度这3种性能指标上具有优越性。     

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。     

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     

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。     

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     

Improved multi-target tracking in clutter by PDA smoothing

An algorithm is presented for the recursive tracking of multiple targets in cluttered environment by making use of the joint probabilistic data association fixed-lag smoothing (JPDAS) techniques. It is shown that a significant improvement in the accuracy of track estimation of both nonmaneuvering and maneuvering targets may be achieved by introducing a time lag of one or two sampling periods between the instants of estimation and latest measurement. Results of simulation experiments for a radar tracking problem that demonstrate the effects of fixed-lag smoothing are also presented     

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。     

基于Keystone变换和MDCFT的高机动弱目标检测与参数估计

 常规雷达对隐身、超声速和高机动目标存在回波信噪比不足、距离徙动和多普勒谱扩展问题。将Keystone变换和修正离散Chirp-Fourier变换(MDCFT)相结合,提出了一种新的雷达信号处理算法。该算法通过Keystone变换补偿距离徙动问题,利用MDCFT对多普勒谱严重扩展的目标回波进行相参积累,提高目标检测性能的同时完成了对目标参数的估计,且该算法在方位向欠采样时仍可适用。最后对算法运算量及性能进行了分析,通过仿真验证了该算法的有效性。