块自适应球形矢量量化算法压缩SAR原始数据

提出使用块自适应球形矢量量化算法压缩SAR原始数据,该算法充分利用SAR原始数据经过自适应块处理之后在较小的数据块范围内具有稳定高斯分布的特点,使用格型矢量技术中的球形码书量化器进行量化,可以提高算法的压缩性能。通过运用球形矢量量化算法对SAR原始数据进行压缩、解压缩获取相应的SAR图像与块自适应量化和块自适应矢量量化经过同样过程得到SAR图像进行比较分析,得出块自适应球形格矢量量化算法是算法复杂度和算法性能之间比较好的折中。     

基于数值计算的机载SAR空变运动补偿算法

针对机载合成孔径雷达(SAR)高分辨率宽测绘带(HRWS)成像问题,在分析结合两步运动误差补偿的距离徙动算法基础上,提出一种基于数值计算的空变运动误差补偿算法。通过对粗聚焦图像进行分块,在子块的两维波数域进行空变运动补偿,补偿的相位包括方位相位误差、距离相位误差以及方位和距离的耦合相位,因此该算法在复杂航迹、高分辨和宽测绘带情况下仍具有较好的鲁棒性。最后对SAR仿真数据和实测数据进行处理,并与结合两步运动误差补偿的距离徙动算法进行比较,处理结果表明该算法能够更好地补偿空变运动误差。     

匀转速逆合成孔径雷达的越距离徙动补偿

针对ISAR系统中的匀转速目标,本文提出了一种有效的校正由目标均转速旋转引起的越距离徙动(MTRC)的方法,对方位向上越距离徙动进行校正。它采用基于PD算法的Radon变换在方位向上得到精确的二次相位系数估计值,然后直接在时域上对越距离徙动校正,获得了更高的分辨率。Outlier-delete算法是一种在时域校正方位向越距离徙动的算法,在高信噪比条件下可以实现很好的聚焦效果,而在低信噪比条件下,该算法会出现严重误估计,导致聚焦失败。本文提出的Radon-PD算法具有很好的抗噪性,通过仿真并与Outlier-delete算法进行性能比较,验证了算法的有效性和可行性。     

基于图像域分块的条带SAR 自聚焦算法

文章针对条带合成孔径雷达,提出一种基于图像域分块的自聚焦算法。该算法在图像域进行方位向分子 块,采用图像偏移(MD)算法减小相位误差梯度的拼接误差,实现条带SAR图像的自聚焦处理。给出了算法流程, 讨论了算法的主要步骤及原理,并利用实测数据对算法进行了验证。实测数据处理结果表明该算法能有效改善条 带SAR图像质量。     

一种超高分辨率机载聚束SAR两维自聚焦算法

受运动参数测量误差和大气扰动等因素影响,合成孔径雷达(SAR)图像通常会发生散焦,利用自聚焦对散焦的SAR图像进行后处理是一种有效的重聚焦手段。传统的自聚焦算法都只是针对方位一维相位误差的估计和补偿。随着成像分辨率的提高,自聚焦时残留距离徙动的校正成为SAR成像面临的一个新挑战。本文推导得到了极坐标格式算法处理后残留距离徙动和方位相位误差的解析表达式,分析了两者之间的内在关系,并利用该关系,提出了一种能够同时进行残留距离徙动和方位相位误差补偿的两维自聚焦算法。实测数据处理结果表明,在残留距离徙动效应不可忽略的条件下,该方法能够极大地改善原有自聚焦算法的聚焦性能。     

一种横向机动弹道下SAR成像算法

针对横向机动弹道下SAR成像回波方位向和距离向严重耦合、弹载SAR平台实时性要求高的特点,提出了一种基于频谱分析的扩展SAR成像算法。首先,以初始距离相同的目标作为成像处理对象,建立了横向机动下弹载SAR成像模型,分析了回波相位和瞬时距离的泰勒展开;然后,采用包含水平面速度和偏航加速度参数的相位因子依次进行距离徙动校正、二次相位补偿和多普勒中心频率补偿,实现了SAR图像的精确聚焦。该算法处理流程简单、实时性高,适合横向机动弹道下的中等分辨率的大斜视成像,给出了算法流程,仿真验证了算法有效性。     

基于CZT的机载并行双站斜视SAR成像算法

建立了机载并行双站斜视合成孔径雷达(SAR)的几何模型,给出了雷达回波的数学表达式,推导了它的二维频谱并对其特点做了分析。在二维频域内,先用聚焦函数对观测场景中心的点目标做精确成像,然后用Chirp-Z变换(CZT)校正中心点两侧目标回波的距离徙动,再通过方位向逆傅里叶变换得到了雷达图像。该算法利用了CZT能够处理非线性调频信号的特点,简化了处理过程,提高了计算效率和成像精度。仿真实验验证了这种基于CZT的新算法在处理并行双站斜视SAR数据时的有效性。     

一种孔径和频率二维稀疏的步进频SAR成像方法

 步进频率信号(SFWs)在不增加雷达系统瞬时带宽的情况下能够获得高的距离向分辨率的同时,也存在着抗干扰能力较差及其等效重复频率较低的问题,并且在方位向积累时间内由于雷达载机工作状态的变化,会导致方位向的数据录取不完整。针对上述问题,提出一种孔径和频率二维稀疏的步进频合成孔径雷达(SAR)成像方法。首先,分析了稀疏步进频率信号(SSFWs)的SAR成像模型,然后基于压缩感知理论完成距离向成像处理。其次,针对稀疏孔径的回波数据,通过构造成像算子和压缩感知重建模型的方法实现其距离徙动校正和方位压缩处理,进而获得二维成像结果。相比于传统的步进频率信号SAR成像,利用所提方法能够在少量的频率资源和雷达回波数据情况下实现准确的SAR成像。最后,通过对仿真和实测的步进频率雷达数据进行成像处理,验证了所提方法的有效性和可行性。     

基于杂波对消-自聚焦的多通道SAR-GMTI

对超高频(UHF)波段多通道合成孔径雷达(SAR)动目标检测技术进行研究,解决了长相干积累时间导致动目标在方位向散焦严重的问题。采用分块自聚焦技术对多通道SAR地面移动目标指示(GMTI)系统自适应杂波抑制后的SAR图像进行处理,改善杂波抑制后的SAR图像中动目标的聚焦情况,增强动目标与周围剩余杂波的对比度,进而提高恒虚警率(CFAR)检测的性能。与传统杂波抑制后直接进行CFAR检测方法相比较,该方法降低了检测虚警概率。实测数据处理结果显示动目标的信杂比明显提高,动目标方位向聚焦成功,证明了该方法的有效性。     

一种新的非平行轨迹机载双站斜视SAR成像算法(英文)

本文提出了一种用于非平行轨迹机载双站斜视SAR条带模式成像的新的解析算法。该算法用收、发雷达的多普勒调频率贡献比为加权系数推导了点目标回波的二维频谱。通过解目标位置相对于收、发载机飞行轨迹的耦合,将这个二维频谱中目标的距离参数和方位参数进行了分离。在二维频域内,补偿掉双站扭曲项后利用二维Chirp-Z变换(2D-CZT)校正了距离向和方位向的徙动,获得了精确聚焦的目标图像。雷达回波的二维残余徙动用沿距离向和方位向的分块来限制,推导了数据分块的条件,由此可以实现宽场景成像。仿真试验验证了这种2D-CZT算法的有效性。     

Synthetic aperture radar image formation from compressed data usinga new computation technique

A convolution technique is proposed that allows direct reconstruction of the processed synthetic-aperture radar (SAR) image from the digitally-sampled, block-encoded raw data. This computational compression technique reduces the number of arithmetic operations from that required by fast Fourier transform (FFT) convolution for SAR processing. SAR phase histories are block encoded and directly processed into an image where only arithmetic additions are required for the processing. For SAR data previously block encoded, the processing time is reduced by a factor of 100 or more. A speed-up of three times over SAR processing by FET convolution has been demonstrated when both computation of the block encoding and subsequent direct processing are included in the time. SAR image quality measurements for a method of block encoding called vector quantization at compression ration ranging from 5:1 to 50:1 show image degradation proportional to the compression ratio. For a 5:1 compression radio, image quality measurements show minimal degradation     

An extended chirp scaling algorithm for spaceborne sliding spotlight synthetic aperture radar imaging

A system impulse response with low sidelobes is critical in synthetic aperture radar（SAR） images because sidelobes contribute to noise and interfere with nearby scatterers. However,the conventional tricks of sidelobe suppression are unable to be exactly applied to the case of spaceborne sliding spotlight SAR due to great azimuth shifts in both time and frequency domains. In this paper, an extended chirp scaling algorithm is presented for spaceborne sliding spotlight SAR data imaging. The proposed algorithm firstly uses the spectral analysis（SPECAN） technique to avoid the azimuth spectrum folding effect and then employs the chirp scaling（CS） algorithm to achieve data focusing, i.e., the so-called two-step approach. To suppress the sidelobe level, an efficient strategy for the azimuth spectral weighting which only involves matrix multiplications and short fast Fourier transformations（FFTs） is proposed, which is a post-process executed on the focused SAR image and particularly simple to be implemented. The SAR image processed by the proposed extended CS algorithm is very precise and perfectly phase-preserving. In the end, computer simulation results verify the analysis and confirm the validity of the proposed algorithm.     

Advanced high-order nonlinear chirp scaling algorithm for high-resolution wide-swath spaceborne SAR

Spaceborne Synthetic Aperture Radar (SAR) is a well-established and powerful imaging technology that can provide high-resolution images of the Earth’s surface on a global scale. For future SAR systems, one of the key capabilities is to acquire images with both high-resolution and wide-swath. In parallel to the evolution of SAR sensors, more precise range models, and effective imaging algorithms are required. Due to the significant azimuth-variance of the echo signal in High-Resolution Wide-Swath (HRWS) SAR, two challenges have been faced in conventional imaging algorithms. The first challenge is constructing a precise range model of the whole scene and the second one is to develop an effective imaging algorithm since existing ones fail to process high-resolution and wide azimuth swath SAR data effectively. In this paper, an Advanced High-order Nonlinear Chirp Scaling (A-HNLCS) algorithm for HRWS SAR is proposed. First, a novel Second-Order Equivalent Squint Range Model (SOESRM) is developed to describe the range history of the whole scene, by introducing a quadratic curve to fit the deviation of the azimuth FM rate. Second, a corresponding algorithm is derived, where the azimuth-variance of the echo signal is solved by azimuth equalizing processing and accurate focusing is achieved through a high-order nonlinear chirp scaling algorithm. As a result, the whole scene can be accurately focused through one single imaging processing. Simulations are provided to validate the proposed range model and imaging algorithm.     

基于Kalman滤波的高频CW电报信号自动识别

针对强噪声背景下高频CW电报信号检测算法性能严重下降、误码率较高的问题,文章提出一种基于卡尔曼滤波的高频CW电报信号同步检测识别算法。利用自同步法对CW电报信号实现位同步,进而利用卡尔曼滤波针对时变干扰噪声设置自适应阈值,对信号能量进行软判决,实现CW电报信号的自适应跟踪检测,提取有效信号进行识别。通过短波信道仿真软件和实际短波通信测试表明,该算法能够在强噪声背景下有效检测识别CW电报信号,且算法可由迭代实现。     

An approach for parameter estimation of combined CPPM and LFM radar signal

In this paper, the problem of parameter estimation of the combined radar signal adopting chaotic pulse position modulation (CPPM) and linear frequency modulation (LFM), which can be widely used in electronic countermeasures, is addressed. An approach is proposed to estimate the initial frequency and chirp rate of the combined signal by exploiting the second-order cyclostationarity of the intra-pulse signal. In addition, under the condition of the equal pulse width, the pulse repetition interval (PRI) of the combined signal is predicted using the low-order Volterra adaptive filter. Simulations demonstrate that the proposed cyclic autocorrelation Hough transform (CHT) algorithm is theoretically tolerant to additive white Gaussian noise. When the value of signal noise to ratio (SNR) is less than 4 dB, it can still estimate the intra-pulse parameters well. When SNR = 3 dB, a good prediction of the PRI sequence can be achieved by the Volterra adaptive filter algorithm, even only 100 training samples.     

基于SAR图像匹配结果可信度评价的INS/SAR自适应Kalman滤波算法

在惯性导航系统（INS）/合成孔径雷达（SAR）组合导航系统中，SAR图像易受斑点噪声的影响，图像匹配的精度对整个导航系统精度的影响十分明显，能够准确地分析SAR图像匹配过程中的误差特性，利用有效的图像匹配信息辅助INS进行组合定位尤为重要。针对上述问题，在加权Hausdorff距离匹配算法的基础上，对影响SAR图像匹配精度的因素进行了分析，提出了一种基于模糊推理的匹配结果可信度评价准则，经过可信度筛选，将有效的匹配信息与INS进行组合；对合理范围内的匹配误差变化引起量测噪声统计特性发生变化，进而导致Kalman滤波精度下降的问题，研究采用改进的Sage-Husa自适应滤波算法对量测噪声方差阵进行动态调整，使其更加接近系统的当前状态。搭建仿真验证平台对所提算法进行了验证，结果表明，该算法能够在合理的匹配误差范围内，有效地筛选出可信的图像匹配结果，相比常规Kalman滤波算法，显著地提升了INS/SAR组合导航系统水平方向的定位精度。     

Robust adaptive filtering method for SINS/SAR integrated navigation system

This paper presents a new robust adaptive filtering method for SINS/SAR (Strap-down Inertial Navigation System/Synthetic Aperture Radar) integrated navigation system. This method adopts the principle of robust estimation to adaptive filtering of observational data. A robust adaptive filter is developed to adaptively determine the covariance matrix of observation noise, and adaptively adjust the covariance matrix of system state noise according to the adaptive factor constructed based on predicted residuals. Experimental results and comparison analysis demonstrate that the proposed method cannot only effectively resist disturbances due to system state noise and observation noise, but it can also achieve higher accuracy than the adaptive Kalman filtering method.     

Sum-difference Reduced-dimensional Processing in SAR Image Domain and Statistical Analysis for Ground Moving Target Indication

In this article, a new reduced-dimensional adaptive processing algorithm based on joint pixels sum-difference data for clutter rejection is proposed. The sum-difference data are obtained by orthogonal projection of the joint pixels data of different synthetic aperture radar (SAR) images generated by a multi-satellite radar system. In the sense of statistical expectation, the sum-differ- ence data contain the common and different information of the SAR images. Therefore, the objective of clutter cancellation can be achieved by adaptive processing. Moreover, based on the residual image after clutter rejection, statistical analysis of constant false-alarm rate (CFAR) detection of moving targets is also presented. Simulation results demonstrate the effectiveness and robustness of the proposed algorithm even with heterogeneous clutter and image co-registration error.     

Block floating point for radar data

Integer, floating point, and block floating point (BFP) data formats are analyzed and compared in order to establish the mathematical tools for selection of an optimal format which fulfils the demands of high resolution radar (SAR) data to large dynamic range and adequate S/N. The analysis takes quantization noise and saturation distortion into account and concludes that it is preferred to use small blocks and a (new) modified BFP format applying fractional exponents. Data from the EMISAR radar system are applied to illustrate the merits of the different schemes