Manoeuvring target motion parameter estimation for ISAR image fusion

In inverse synthetic aperture radar (ISAR) imaging applications, generating an image of a manoeuvring target is a challenge due to the tradeoff between the fine image resolution requirements and the temporal variability of the Doppler response. The time frequency transform (TFT) is a common method to solve this problem. Prior TFT-based research assumes that the ISAR observes the target from a single fixed aspect. Because of its manoeuvring characteristics, the target motion features are sometimes not extractable from the observing aspect, but become much more distinct from other aspects. ISAR image fusion is thus able to provide significant advantages, since multiple looks of the same target from different aspects will increase the available knowledge. After constructing the common projection plane and building up the physical connection between radars and the manoeuvring target, the parameters that describe the target motion are estimated for very short time duration within which the Doppler response can be assumed to be a constant. Simulation results confirm the effectiveness of the estimation procedure and thus the fusion method. The authors conclude that the ISAR system must be carefully configured in order to realise the full benefits of their image fusion technique for manoeuvring targets.     

线性调频步进信号雷达目标运动参数估计方法

针对目标运动对线性调频步进信号雷达成像的影响,提出一种基于时频分析的目标运动参数估计方法。对差频处理后的各簇回波信号进行快速傅里叶变换,利用变换后信号与子脉冲序列的线性调频关系,通过维格纳分布和Radon变换对目标不同时刻运动参数进行估计。结合二值数学形态学与图像边缘检测方法提高对多散射点目标运动参数估计的精度。在此基础上,针对目标可能出现的变速运动情况,利用最小二乘算法拟合整个成像时间内目标运动速度的变化,较好地实现对机动目标的运动参数估计。仿真实验验证了本文方法的有效性。     

Slope-based frame selection and scaling technique for ship ISAR imaging

The authors address the problem of optimum imaging time selection and angular motion estimation for ship ISAR or hybrid SAR/ISAR imaging. The aim is to select proper imaging times and to estimate ship angular motion in order to obtain high-quality top view or side view scaled images of the ship, suitable for processing by classification/identification procedures. For this purpose, a new technique is proposed, able to select the time instants better suited for top or side view image formation and to estimate the rotation motion for image scaling. The technique is based on a novel model of the phase/Doppler frequency of the generic ship scatterer and operates entirely in the range-Doppler image domain (as obtained via Fourier transform) by using the slopes of some extracted linear features, thus without requiring coherent processing. The performance of the complete ISAR technique is analysed in depth; the results of the application of the proposed technique to both simulated and live ISAR data prove the effectiveness of the proposed approach.     

ISAR imaging for three-dimensional rotation targets based on adaptive Chirplet decomposition

In this paper, a new algorithm of inverse synthetic aperture radar (ISAR) imaging for three-dimensional (3-D) rotation targets is presented. The characteristic of the received signal when the target has 3-D rotation is studied, and it is approximated as multi-component amplitude modulated and frequency modulated (AM–FM) signal. Then a new algorithm for the adaptive Chirplet decomposition is presented to analyze the AM–FM signal, and the high quality instantaneous ISAR images are obtained based on the Range-Instantaneous-Doppler (RID) algorithm. The results of simulated and real data demonstrate the effectiveness of the method proposed.     

New approach for ISAR imaging of ship target with 3D rotation

Inverse synthetic aperture radar (ISAR) imaging of ship target is very important in the national defense. The imaging condition for ship target is very complicated due to the complexity of the ship’s movement, and a three-dimensional (3D) rotation occurs for the ship with the oceanic waves. Furthermore, the multi-path effect can not be avoided in most circumstance. In general, the received signal for a 3D rotation ship target can be characterized as multi-component polynomial phase signals (PPS), and the parametric method can be used to obtain the instantaneous ISAR images. In this paper, the received signal is considered as multi-component cubic phase signal, and a new method for ISAR imaging of ship target with 3D rotation by the product high order bilinear matched-phase transform (PHBMT) is proposed. The instantaneous ISAR image is obtained, and the multi-path effect can be eliminated by separating the ISAR image in the range-instantaneous-Doppler domain. Results of real data validate the effectiveness of the new approach presented.     

ISAR成像实时处理系统设计

根据ISAR成像的特点研究并设计了ISAR实时成像处理系统,主要包括:信号处理模块的硬件采用分布式并行的设计方式;系统的数据通信采用串并转换及链路口和交换机相结合的方法;根据外场实验的参数和目标特征,选择适于ISAR实时成像的算法,并对算法的运算量进行了分析,在此基础上进行了实时处理在信号处理板卡上的任务分配。最后的试验结果和分析验证了该系统的有效性。     

A subspace rotation approach to signal parameter estimation

A new approach to Estimation of Signal Parameters by Rotational Invariance Techniques (ESPRIT) is described in the context of direction-of-arrival estimation, but is also applicable to other problems. The method relies on finding the underlying rotation between the common subspaces associated with an array of pairwise-matched and codirectional sensor doublets. ESPRIT has several remarkable advantages over earlier techniques such as MUSIC, and also provides asymptotically unbiased and efficient estimates.     

空间目标的ISAR跟踪

在对空间目标进行ISAR成像过程中,要求对目标进行精确跟踪.本文提出一种对空间远距离ISAR目标进行精密跟踪的方法,从而实现了采用宽带信号对目标进行同时跟踪与成像.结果表明,采用该方法能提高数据率,跟踪精度也达到了成像的要求.     

稀疏孔径和大转角下ISAR对目标转动的估计

逆合成孔径雷达（inverse synthetic aperture radar，ISAR）对非合作目标做成像时图像质量依赖于对目标运动参数的准确估计.针对在稀疏孔径和非均匀转动条件下现存的参数估计方法计算量过大或者方法适用条件不满足，提出了一种基于神经网络的参数估计方法.此方法以成像问题的模型知识指导数据的生成过程，然后训练通用的神经网络，最终实现将数据中隐含的知识转化为转动估计器.从仿真实验结果来看，所得到的网络对满足一定信噪比要求的回波数据可以提供较准确的估计，所得参数可以帮助成像算法提高聚焦效果，大量的样例表明网络可以部分学习到回波与转动之间的关系.     

Nonlinear parameter estimation via the genetic algorithm

A modified genetic algorithm is used to solve the parameter identification problem for linear and nonlinear IIR digital filters. Under suitable hypotheses, the estimation error is shown to converge in probability to zero. The scheme is also applied to feedforward and recurrent neural networks     

Complex ISAR imaging of maneuvering targets via the Capon estimator

An inverse synthetic aperture radar (ISAR) can be used to produce high-resolution images of moving targets of interest by utilizing the relative motion between the target and the radar and by transmitting signals with large bandwidth. Most ISAR imaging algorithms are based on the range-Doppler processing, which implies that the Doppler shifts remain constant during the coherent integration time. For maneuvering targets, the Doppler shifts are time varying. In this case, the algorithms will produce blurred images. We present herein an adaptive Capon (1969) spectral estimation algorithm for the complex ISAR image formation of maneuvering targets. It is an efficient recursive implementation of the well-known Capon complex spectral estimation algorithm by using FFT and simple matrix operations     

含旋转部件的ISAR目标分离式成像

随着雷达成像分辨能力的不断提升,转台模型所引起的二维距离走动已经影响到高分辨ISAR成像质量。同时,雷达目标物上部件的微动也变得不可忽略。因此,针对含旋转部件的目标的ISAR回波,本文提出了一种基于回波分离处理的精细化成像流程。该流程通过对目标物的刚体、部件回波进行分离,有序地对来自转台模型的二阶、一阶距离走动进行补偿,并获得旋转运动参数估计。其后,再对两种回波分别用与之相适的方法进行成像,完成对整个目标物图像的精细化处理。仿真和实测数据的处理结果验证了该流程的有效性。      

双站步进频率雷达运动目标ISAR成像

建立了双站ISAR运动目标的几何模型,给出了双站步进频率雷达运动目标的回波信号模型,讨论了目标运动对步进频率双站ISAR成像的影响;为补偿目标因等效径向速度引起合成距离像峰值的时移和能量发散,提出了用距离微分法估计目标的等效径向速度作粗补偿,然后用积累相关法作精补偿的成像方法;仿真结果验证了该方法的有效性。     

Simple material parameter estimation via terahertz time-domain spectroscopy

A simple and precise method based on fixed-point iteration is used to estimate dielectric parameters using terahertz time-domain spectroscopy (THz-TDS). The method converges and gives correct parameters when the sample thickness is greater than 200 /spl mu/m at a frequency of 0.1 THz or 20 /spl mu/m at a frequency of 1.0 THz. The technique in validated using measured terahertz data, obtained by probing a sample of high-resistivity silicon.     

基于双旋转单偶极子阵列的谱参数估计方法

提出了一种基于双旋转单偶极子阵列的联合谱参数估计算法.通过旋转阵元及修正极化多重信号分类(multiple signal classification, MUSIC)算法中谱函数的导向矢量, 便能实现用两阵元进行多目标测向, 回避了传统算法中要求信号源个数小于阵元数的问题.仿真结果表明:在小快拍数、低信噪比的影响下, 该算法在测向性能上优于阵元数为6的极化空间谱估计算法, 且所用通道数少, 可降低成本.该算法所述的单偶极子阵列可用任意极化敏感天线单元或组合进行构造, 可移植性较强.     

ADAPTIVE ALGORITHM FOR CONSISTENTMA PARAMETER ESTIMATION VIATHIRD ORDER CUMULANT

This paper addresses the problem of adaptive,consistent parameter estimation for a MA model from the 3rd order cumulant of the system output. The proposed adaptive algorithm is derived by using the new linear equation system (J. K. Tugnait, 1990), which is proved to have unique solution,and hence guarantees the consistence of the MA parameters. Simulation results are provided to show the performance of the new algorithm.     

Target position estimation in radar and sonar, and generalized ambiguity analysis for maximum likelihood parameter estimation

Target position estimation in radar and sonar means joint estimation of range and angle in the presence of noise and clutter. The global behavior of a maximum likelihood (ML) position estimator, and the clutter suppression capability of the system, can be written in terms of a range-angle ambiguity function. This function depends upon signal waveform and array configuration, i.e., upon both temporal and spatial characteristics of the system. Ambiguity and variance bound analysis indicates that system bandwidth can often be traded for array size, and direction-dependent signals can be used to obtain better angle resolution without increasing the size of the array. Wide-band direction-dependent signals (temporal diversity) can be traded for large real or synthetic arrays (spatial diversity). This tradeoff is apparently exploited by some animal echolocation systems. The above insights are obtained mostly from the properties of the range-angle ambiguity function. In general, an appropriate ambiguity function should be very useful for the design and evaluation of any ML parameter estimator. System identification methods and radio navigation systems, for example, can be optimized by minimizing the volume of a multiparameter ambiguity function.     

基于二次统计CFAR处理的目标径向尺寸估计

利用雷达高分辨距离像(high resolution range profile,HRRP)实现对目标径向尺寸估计,可为目标分类识别提供重要特征判据.实际中常采用双向恒虚警(constant false alarm rate,CFAR)门限法进行目标信号支撑区和噪声区的鉴别,低信噪比条件下现有方法尺寸估计精度较低,且当...     

High-speed Target ISAR Imaging via Compressed Sensing Based on Sparsity in Fractional Fourier Domain

Compressed sensing （CS） provides great potential to reduce radar sampling rate while improve the imaging performance. In this paper, the application of CS to ISAR imaging of hlgh-speed space targets is introduced. Firstly, based on the analysis of the echo model of highspeed targets, we elucidate that the dechirped high-speed target echo is of sparsity in fractional Fourier domain. Then the Analog-to-information conversion （AIC） is used to take compressive measurements, following which the radar image can be recovered via nonlinear optimization. In particular, considering the non-cooperative characteristic of targets, an optimization search algorithm based on sparsity of the reconstructed range profiles is presented, so as to find the optimal transform order of fractional Fourier transform. Experiment results from both simulated data and measured data show the validity and superiority of the proposed imaging method.     

一种复杂运动目标的ISAR成像算法

在对复杂运动目标进行逆合成孔径雷达成像时,由于转动矢量随时间而变化,回波信号中会引入一个与散射点位置有关的相位误差,无法用通常的相位补偿方法进行校正,应用距离-多普勒算法获得的ISAR(Inverse Synthetic Aperture Radar)像会变得模糊.本文分析了目标转动矢量变化使得ISAR像模糊的内在原因,给出了目标三维转动状态下的ISAR信号形式,并基于散射点信号的特点提出了一种复杂运动目标的ISAR成像算法.该算法不仅适用于转动矢量方向不变的非均匀转动目标,而且对于转动矢量方向缓慢变化的目标,算法仍然能够有效地提高ISAR成像的质量.仿真试验结果表明了该算法的有效性.