星载sAR辐射定标误差分析及成像处理器增益计算

本文对星载SAR辐射定标的各项误差因素进行了分析,提出了计算辐射定标误差的公式,提供了分配星载SAR系统辐射定标误差的工具;对基于CS(Chirp Scaling)算法的成像处理器的增益计算公式进行了推导,并通过计算机仿真得到了验证;定量地分析了成像处理器增益计算误差对SAR系统辐射定标精度的影响。     

机载双站合成孔径雷达Chirp Scaling成像算法

该文在分析机载双站SAR回波模型的基础上,结合常规单站SAR的Chirp scaling成像算法思想,推导出了双站SAR的Chirp scaling成像算法。对双站SAR的Chirp scaling成像算法进行了误差分析。最后通过仿真验证了算法的有效性。     

机载高分辨滑动聚束SAR成像处理方法

针对机载滑动聚束合成孔径雷达(SAR)高分辨率成像问题,在提出采用参考信号进行系统通道误差校正和高分辨滑动聚束成像运动补偿方法的基础上,结合基带方位向变标(BAS)算法,给出一种机载高分辨率滑动聚束SAR成像方法。首先,在频域推导了基于参考信号对回波信号进行幅度校正和相位补偿的方法;然后基于斜视成像几何模型,推导了机载滑动聚束SAR平台运动参数与多普勒参数之间的关系,给出从多普勒估计参数中估计运动参数和补偿运动误差的方法。采用该成像处理方法,某型星载SAR机载试飞试验成功实现了滑动聚束模式高分辨率成像,验证了方法的有效性。      

亚马逊热带雨林星载SAR辐射定标算法

天线外定标是实现星载SAR天线方向图在轨测试的主要手段。天线方向图的准确测量,对星载SAR图像的应用具有重要作用。分布目标辐射定标在星载SAR天线方向图测试中受到广泛重视。亚马逊热带雨林的后向散射系数呈现大面积的均匀性和稳定性,故成为分布目标定标最主要的定标场。该文在分布目标定标原理的基础上,对基于亚马逊热带雨林的星载SAR天线方向图测量算法进行了研究,提出了采用K．Pearson统计量非参数假设检验的一致性处理算法,并采用Levenberg-Marquard算法（LM算法）估计俯仰向天线方向图模型参数。仿真数据验证了算法的可靠性和准确性。     

改进的机载阵列调频连续波合成孔径雷达前视成像方法

机载阵列前视合成孔径雷达(SAR)信号模型中忽略载机速度会影响成像。针对该问题,在调频连续波(FMCW)SAR信号模型中考虑了载机速度,分析了载机速度的影响和载机连续运动引入的多普勒频率偏移的特点,结合Frequency Scaling算法,研究了机载阵列FMCW SAR前视成像。成像仿真和性能参数分析表明:改进方法可精确实现载机运动条件下的FMCW SAR前视成像。     

机载前视SAR三维成像算法研究

该文以一种采用天线阵模式的机载前视合成孔径雷达(SAR)系统为对象,根据前视SAR的成像几何模型和回波信号特点,提出了一种适用于机载前视SAR的3维成像算法。该算法首先将各天线阵元接收一遍后的数据采用CS算法获得单幅SAR图像,然后将飞机飞行过程中获得的所有SAR图像中相同方位向对应的数据结合距离多普勒算法思想依次进行成像处理,最后获得3维像。模拟了X波段前视SAR点目标回波并进行了3维成像实验,对成像性能进行了分析。仿真结果验证了该算法的有效性。     

基于粒子群优化的极化SAR定标算法

极化合成孔径雷达(SAR)的精确定标对于极化数据的终端应用至关重要。提出了一种基于粒子群优化的极化SAR定标算法,由于在估计误差参数过程中没有作任何的近似,相比于经典的极化定标算法,该方法即使在串扰参数较高时仍能保持很高的精确度。为了验证算法的有效性,分别使用仿真数据和真实的机载极化SAR数据来模拟极化失真数据,并采用多种极化定标方法对失真数据进行校准,校准结果证明了所提方法对极化误差参数有着更加稳定精确的估计。     

低频SAR辐射校准

低频SAR天线通常具有极宽的方位向波束角，在辐射定标时，定标体RCS随雷达波入射角的变化不能够忽略，文中利用低频散射模型，得到定标体RCS随角度变化关系，结合条带式低频SAR的工作原理，给出辐射校准的方法，并进行仿真试验，验证了该方法的有效性。     

基于最小熵DCFT的双基地SAR多普勒参数估计

多普勒参数估计是SAR成像技术研究中的一项关键技术,多普勒参数估计精度将直接影响机载双基地SAR系统成像质量,为了实现对感兴趣目标区域有效地成像,需要对回波信号的参数进行准确估计。本文提出基于最小熵的离散调频傅里叶法(DCFT),该方法基于线性调频信号,可同时估计多普勒质心和多普勒斜率,并用RD算法对双基地SAR仿真数据成像,通过仿真验证了该方法的性能。     

匹配傅里叶变换的SAR多普勒参数估计

讨论了SAR的基本信号模型,针对这一模型提出了应用匹配傅里叶变换估计SAR多普勒参数的新方法。文中给出了理论分析和仿真,并用机载SAR回波实际数据进行了多普勒参数估计,根据估计的多普勒参数给出了成像结果,表明了该方法可对SAR数据进行盲处理估计出多普勒参数,且精度高。     

Ambiguity resolution for permanent scatterer interferometry

In the permanent scatterer technique of synthetic aperture radar interferometry, there is a need for an efficient and reliable nonlinear parameter inversion algorithm that includes estimation of the phase cycle ambiguities. Present techniques make use of a direct search of the solution space, treating the observations as deterministic and equally weighted, and which do not yield an exact solution. Moreover, they do not describe the quality of the estimated parameters. Here, we use the integer least squares estimator, which has the highest probability of correct integer estimation for problems with a multivariate normal distribution. With this estimator, the propagated variance-covariance matrix of the estimated parameters can be obtained. We have adapted the LAMBDA method, part of an integer least squares estimator developed for the ambiguity resolution of carrier phase observations in global positioning systems, to the problem of permanent scatterers. Key elements of the proposed method are the introduction of pseudo-observations to regularize the system of equations, decorrelation of the ambiguities for an efficient estimation, and the combination of a bootstrap estimator with an integer least squares search to obtain the final integer estimates. The performance of the proposed algorithm is demonstrated using simulated and real data.     

基于雷达散射特性的高分辨率SAR图像自动目标识别

高分辨率SAR的迅速发展为自动目标识别提供了可能,为了克服存储海量模板带来的计算复杂性,发展基于模型的目标识别现已成为新的国际研究热点.先由目标的真实三维模型依据电磁波散射理论计算雷达散射截面(RCS),利用宽带合成孔径技术得出目标散射特性的空间分辨率图像,进而基于模拟图像实现目标的CFAR检测.最后利用我国机载高分辨率SAR图像对该方法进行实验,验证了本文提出的基于雷达散射特性目标识别的有效性.     

Reflectivity estimation for multibaseline interferometric radar imaging of layover extended sources

In recent years, there has been great interest in exploiting the advanced multibaseline operation of synthetic aperture radar interferometry (InSAR) for solving layover effects from complex orography, which can degrade both SAR and InSAR imagery of terrain radar reflectivity and height. In this work, the problem of retrieving radar reflectivity of layover areas is addressed. It is formulated as the problem of estimating a multicomponent sinusoidal signal corrupted by multiplicative complex correlated noise and additive white Gaussian noise. Application of nonparametric [e.g., Capon, amplitude and phase estimation filter (APES)], parametric [least squares, modern parametric RELAXation spectral estimator (RELAX)], and hybrid spectral estimators for amplitude estimation is investigated for a multilook scenario. In particular, the multilook extensions of RELAX and APES are applied to the interferometric problem. Performance analysis is investigated through a Cramer-Rao lower bound calculation and Monte Carlo simulation. The method of least squares, coupled with Capon's approach to spatial frequency estimation, multilook APES, and multilook RELAX turn out to provide accurate reflectivity estimates for undistorted multibaseline image formation of layover areas.     

机载超高分辨率 SAR 内定标技术研究

首先,研究了合成孔径雷达的内定标工作原理,分析了发射定标实测信号;然后,给出了误差补偿前后的一维距离图像性能指标,提出了利用发射定标数据作为参考函数进行实际数据成像处理的方法;最后,成功应用于机载试飞中,获得了高质量合成孔径雷达图像,并证明了该方法的有效性。     

Moving target feature extraction for airborne high-range resolutionphased-array radar

We study the feature extraction of moving targets in the presence of temporally and spatially correlated ground clutter for airborne high-range resolution (HRR) phased-array radar. To avoid the range migration problems that occur in HRR radar data, we first divide the HRR range profiles into low-range resolution (LRR) segments. Since each LRR segment contains a sequence of HRR range bins, no information is lost due to the division, and hence, no loss of resolution occurs. We show how to use a vector auto-regressive (VAR) filtering technique to suppress the ground clutter, Then, a parameter estimation algorithm is proposed for target feature extraction. From the VAR-filtered data, the target Doppler frequency and the spatial signature vectors are first estimated by using a maximum likelihood (ML) method. The target phase history and direction-of-arrival (DOA) (or the array steering vector for an unknown array manifold) are then estimated from the spatial signature vectors by minimizing a weighted least squares (WLS) cost function. The target radar cross section (RCS)-related complex amplitude and range-related frequency of each target scatterer are then extracted from the estimated target phase history by using RELAX, which is a relaxation-based high-resolution feature extraction algorithm. Numerical results are provided to demonstrate the performance of the proposed algorithm     

面向条带SAR的多孔径图像偏移自聚焦算法

本文提出了一种能够用于机载条带式合成孔径雷达（SAR）运动误差估计的多孔径图像偏移自聚焦算法。首先,将条带SAR数据分割为有重叠的估计子块,各个子块又分为具有重叠场景的多个子孔径,并通过后向投影算法在距离多普勒域构建子孔径图像;然后,对各个子孔径图像进行互相关处理,在分析影响互相关函数的因素的基础上,给出了求解各子图像之间的重叠场景相对偏移的方法;最后,给出了子块内的误差估计方法与子块间的误差拼接方法。对实际数据的处理结果表明,所提算法能够精确且鲁棒地估计机载条带SAR的运动误差。     

共形阵列天线振动条件下稳健的DOA估计及位置误差校正

共形阵列天线比传统的线阵和面阵具有更优良的空气动力学性能、更宽的波束扫描范围、更小的雷达散射截面积和更大的阵列天线孔径等优势。然而共形天线载体受到飞行惯性和空气动力负载的相互作用很容易发生共形表面的变形和单元位置的扰动。更为重要的是平台的机械振动通常还会导致单元位置扰动的时变性,严重影响了共形天线的分辨测向性能。因而针对此类载体共形天线设计稳健的DOA估计算法和位置误差校正算法十分必要和有意义。本文提出了一种共形天线振动条件下的稳健DOA估计和位置误差校正算法。在给出共形线阵振动的数学模型基础上,得到修正的时变阵列导向矢量。采用时变的阵列导向矢量在一个振动周期内计算MUSIC谱,搜索空时二维的MUSIC谱的谱峰,得到本次采样快拍数据时阵列振动位于振动周期中的时刻和信源方位的联合估计。根据阵列振动的数学模型就可以进一步预测下一次采样快拍数据时刻阵列各阵元的位置误差,从而实现振动条件下的阵元位置误差校正和稳健的DOA估计。计算机仿真结果表明了提出算法的有效性。      

A Fast and Accurate Far-Field Pseudopolar Format Radar Imaging Algorithm

A novel imaging algorithm to be used under the condition of having an image scene in the far field of a linear radar aperture is presented. This is an application scenario that is drastically different from those of spaceborne and airborne synthetic aperture radar (SAR) systems, which has not been properly addressed to date. The technique is particularly tailored for a stepped-frequency continuous wave (CW) or frequency-modulated CW radar. The radar aperture must be linear and can be formed either with a physical or synthetic array. With the suggested method, the radar reflectivity of the image scene is obtained through an interpolation-free series expansion, where only 2-D fast Fourier transforms of the frequency-domain backscatter data are required. The resulting image is sampled on a “polarlike” or pseudopolar grid, which is introduced to simplify the formulation. The main advantages of this method are its extremely low computational cost and the high accuracy of the resulting imagery. The technique is extensively validated both with numerical simulations and two ground-based SAR data sets. Last but not least, numerical simulations show that this technique can be used with an ultrawideband radar of 1 GHz of bandwidth.      

A statistical approach for determining radiometric precisions andaccuracies in the calibration of synthetic aperture radar imagery

A model that estimates a relative error bound for the radiometric calibration of synthetic aperture radar (SAR) imagery is presented. This model is based on a statistical `Coefficient of Variation of Error Model', which produces a relative error bound by propagating the measured or estimated uncertainties in the radar system parameters utilized to correct digitally processed SAR image intensity values. Using this model, algorithms are generated for absolute and relative radiometric calibration of SAR imagery. These algorithms are parametrically exercised using radar system parameters from an existing airborne SAR system to determine their impact on the relative error bound     

基于变步长搜索黄金分割优化的自聚焦算法

为了获得高分辨的合成孔径雷达(SAR)图像,需采用自聚焦算法对SAR图像进行处理。文中介绍了利用图像对比度最优准则进行自聚焦的原理方法,将对比度最优自聚焦过程等效为最优一维搜索模型。同时,介绍了变步长搜索黄金分割算法的原理,首先通过变步长搜索确定搜索区间,然后采用黄金分割法进行迭代收敛,当满足终止条件时,停止迭代并得到最终的多普勒调频率最优估计值。与现有的算法相比,基于变步长搜索黄金分割优化的自聚焦算法具有收敛速度快、鲁棒性强的优点。实测数据处理结果验证了算法的有效性。