基于二维deramp处理的高分辨率 聚束SAR成像算法

有效解决回波信号的数据率是高分辨率聚束式星载SAR的难点之一.基于两步成 像算法和CS(Chirp Scaling)成像算法,提出了一种适用于高分辨率聚束式星载SAR的成像算 法——TDDCS(Two Dimension Deramp Chirp Scaling)成像算法.该算法从距离dechirp处理 后回波信号出发,首先利用二维deramp 处理来消除频谱混叠现象,这不仅能实现以对应条 带模式的脉冲重复频率来设计聚束SAR系统,也保证满足观测带宽度所需的回波窗长度,接 着利用CS处理和相位补偿实现精确的距离徙动校正,最后利用方位相匹配滤波 处理实现方位向压缩,得到最终的成像结果.基于等效斜视模型,给出了整个算法的详细推 导过程和实现流程,通过计算机仿真验证了本算法的有效性.      

用真实IMU/GPS数据进行机载SAR运动补偿处理

分析了机载SAR(Synthetic Aperture Radar)条带成像模式的运动补偿技术原理,通过对激光IMU/GPS(Inertial Measurement Units/Global Positioning System)组合提供的位置参数进行分析,表明Y12载机平台具有很大的运动误差,在此基础上利用高精度激光IMU/GPS组合提供的天线相位中心精确位置参数,结合距离-多普勒成像算法进行了机载SAR数据的运动补偿处理,试验表明利用此IMU/GPS提供的运动参数进行对具有很大运动误差的SAR数据运动补偿后,已不需要计算负担沉重的自聚焦类算法进行残留运动误差补偿,就能得到高质量的高分辨率SAR图像.     

基于DEM的星载SAR图像模拟以及用于图像精校正

根据星载SAR的距离-多普勒成像原理对DEM的三维位置点进行成像几何位置的计算,然后根据经验公式给出了雷达后向散射系数的模拟方法。针对DEM格网间隔和SAR图像分辨率的不同,以及由于侧视成像雷达的特点而导致山区的迎坡和背坡模拟图像点密度不均匀等问题,采用了基于DEM格网点内插的算法。最后应用模拟的SAR图像和真实图像匹配来实现星载SAR图像的几何精校正处理。通过采用RADARSAT的实际图像进行了图像的模拟和几何校正,证明了方法的可行性。     

Deramp range migration processing for space-borne spotlight synthetic aperture radar

The deramp range migration algorithm (DRMA) for space-borne spotlight synthetic aperture radar (SAR) is presented, which is based on the two-step algorithm and range migration algorithm. The presented algorithm combines the advantages of SPECAN algorithm and range migration algorithm. Firstly, the presented algorithm performs a bulk azimuth raw data compression to achieve a pixel spacing no larger than the expected azimuth resolution of the fully focused image. Therefore, the azimuth spectral folding phenomenon is overcome. Secondly, the residual and precise focusing of the synthetic aperture radar data is achieved by applying the range migration algorithm. The space-borne SAR focusing parameters’ computation is also described in the paper. At the end of this paper, results are presented which confirm the validity of the presented algorithm.     

基于去噪的SAR复图像SPIHT压缩算法

提出一种对合成孔径雷达(SAR,Synthetic Aperture Radar)复图像压缩的改进的分层树集合分割(SPIHT,Set Partitioning in Hierarchical Trees)算法,高效完成SAR复图像压缩,既有效地保留了SAR复图像的相位信息,又抑制了斑点噪声.首先根据SAR复图像的统计特征进行预处理,然后进行小波变换,对不同子带的小波变换系数采取不同的门限,进行软门限斑点噪声抑制,再经过SPIHT量化编码,得到压缩后的码流.仿真实验表明,在64倍高压缩比的情况下,通过对重建SAR复图像数据的相位误差、等效视数、平均空域相关系数等指标的测量,验证了该算法仍然具有很好的性能.      

基于小波变换的多方位角SAR图像融合方法

针对目标散射特性空变效应以及多方位角图像信息冗余的问题,提出了一种基于小波变换和边缘检测的多方位角SAR图像融合方法。首先,将图像进行小波变换,完成低频信息和高频信息的分离,实现图像的多分辨表征及序贯图像多方位角信息的融合;然后,利用改进的Robinson算子增强图像的轮廓特征;最后,融合实验和定量评估结果证明了本文所提融合方法的有效性。     

基于星上实时信号处理机的Chirp Scaling算法实现方法

基于改进的Chirp Scaling算法,提出了一种适用于星上实时信号处理机的高效成像处理实现方法,其核心思想也可应用于其它高分辨率星载SAR的精确成像算法.首先介绍了实时信号处理机的结构,分析了数据处理粒度及其并行流水处理结构.在此基础上,针对单个粒度的成像处理重新设计了算法流程,提出了一种高效的实现方法.利用实时信号处理机,对仿真的回波数据进行了成像处理实验,结果表明:在41?s内能够完成成像处理,成像处理速度和图像质量满足系统设计要求,从而验证了该方法的有效性.     

小波分析理论及其在雷达信号处理中的应用

依据所处理信号类型的不同,对小波变换与短时傅立叶变换进行了比较,说明小波变换适用于非平稳信号和奇异信号的处理.简要介绍了连续小波变换、离散小波变换和小波包理论的基本内容,讨论了小波变换实际应用中的采样和快速算法等几个关键问题.结合矢量量化技术,给出了一种用小波变换对星载SAR(Synthetic Aperture Radar)原始数据进行压缩的方法,结果表明,与传统的方法相比,由该方法压缩后的原始数据生成的SAR图像具有更大的信噪比.同时对小波变换用于雷达目标识别和SAR图像分类的性能进行了初步分析.      

Vector quantization for saturated SAR raw data compression

Spaceborne SAR involves the storage and transmission of large-size sampling data. Block adaptive quantization (BAQ) is now the most widely used onboard data compression algorithm due to its good tradeoff between system performance and complexity. However, when spaceborne SAR raw data is saturated, the performance of conventional BAQ deteriorates dramatically because its precondition of Gaussian distribution of raw data no longer holds. In order to solve this problem, an improved vector quantization (VQ) algorithm is proposed. This algorithm firstly introduces saturation modification to a conventional vector quantizer, obtains the saturation codebook based on Gaussian density function, and then obtains the new vector quantizer for the whole set of Saturation Degree (SD). This algorithm makes the vector quantizer match statistical model of data for the whole set of SD, so the performance of the compression is improved. The case of the 2D signal is explicitly computed. The performance of the proposed algorithm is verified by simulated and real data experiments.     

高分辨率多模式星载SAR系统设计方法

针对当前星载合成孔径雷达(SAR,Synthetic Aperture Radar)朝高分辨率、多模式方向快速发展的趋势,兼顾星载SAR系统多种工作模式的特点,总结星载SAR系统的星地一体化指标体系;在此基础上提出了高分辨率、多模式星载SAR系统星地一体化设计方法,给出了系统星地一体化设计流程,对雷达天线参数设计、雷达系统参数设计、雷达发射功率选择进行重点分析;以国外高分辨率、多模式星载SAR系统为例,以其总体技术指标及轨道参数为依据,设计了系统的中央电子设备参数、天线参数及波位参数,并分析了系统的性能,从而对所提出的设计方法进行了验证.该方法克服了现有方法的局限性,为高分辨率、多模式星载SAR系统研制提供了技术支撑.     

Novel method for reconstruction of hyperspectral resolution images from multispectral data for complex coastal and inland waters

Hyperspectral resolution image products of a synthetic sensor featuring the high spatial resolution of the space-borne sensor can offer cost-effective means for enhancing our current capabilities in terms of providing an array of images in lieu of designing an expensive system for image acquisition, which can serve the expanding needs of the scientific and user communities for various critical water color applications. Despite several studies on enhancing the capability of land remote sensing sensors, full spectrum reconstruction of water color images with varying spectral bands is hampered by the lack of methods and accurate atmospheric correction procedures. In the present work, a novel method is developed for reconstruction of hyperspectral resolution images from high spatial-resolution Sentinel 2 Multispectral Instrument (MSI) data representative of many complex waters in coastal and inland zones. This method uses a deep neural network (DNN) with multiple blocks of deconvolution and dense layers. The spectral reconstruction of hyperspectral resolution images from multispectral data was based on rigorous training data from the atmospherically-corrected and validated HICO normalized water-leaving radiance products (with spectral resolution 438-868 nm sampled at 5.7 nm) of diverse water types. The generalizability and versatility of the DNN method was tested and evaluated systematically by means of various qualitative and quantitative analyses using concurrent space-borne (MSI and HICO) and in-situ measurements from different regional waters. Reconstructed hyperspectral resolution radiances obtained from the MSI images closely matched with independent HICO and MSI measurements within the desired accuracy. Successful reconstruction and validation of the hyperspectral radiances indicate that the proposed state-of-the-art method provides possible future directions for enhancing our current capabilities of space-borne sensors for various research purposes and societal applications at local, regional and global scales.     

一种基于DCT的SAR图像自聚焦算法

研究了一种基于离散余弦变换(DCT, Discrete Cosine Transform)的SAR(Synthetic Aperture Radar)图像自聚焦算法.该方法从复图像域出发,通过在距离压缩相位历史域引入相位误差模型,改变图像的聚焦程度直至一维像的DCT序列在高序数区域的权值达到最大,从而完成误差校正.同相位梯度自聚焦算法相比,该方法无需在图像域分离出强点目标,因此特别适用于无任何明显特征的图像.由于DCT存在快速算法,使得该自聚焦算法计算量较少,更易实现.实测数据及仿真数据的成像结果证明了此方法的可行性.      

星载SAR亚马逊雨林辐射定标仿真研究

辐射定标是准确、定量描述星载合成孔径雷达(SAR)系统性能的重要手段.星载SAR在轨运行期间,天线方向图较之发射前可能存在较大的失真,从而严重影响所获取的SAR图像数据质量,因此准确测量在轨飞行时天线俯仰向方向图特性并予以补偿是星载SAR辐射定标的主要内容之一.利用具有均匀后向散射系数特性的分布目标进行外定标是测量双程俯仰向天线方向图的最佳方案,而亚马逊雨林是全球最稳定、最均匀、最平坦的分布目标,后向散射系数几乎不随入射角变化,是公认的理想测试场地.鉴于目前我国尚无自行采集的星载SAR图像数据,我们对星载SAR回波功率仿真、天线方向图模型参数估算进行了深入、系统的研究,利用仿真的亚马逊雨林SAR功率图像成功地实现了星载SAR俯仰向天线方向图在轨测试关键环节的模拟,对我国的星载SAR辐射定标研究具有一定的理论意义和重要的工程实用价值.      

0.1m分辨率机载SAR孔径依赖性运动补偿方法

讨论了0.1m分辨率机载合成孔径雷达(SAR,Synthetic Aperture Radar)运动补偿方案设计中的一个新问题.超高方位分辨率意味着长合成孔径和大相干积累角,条带模式下的回波数据中可能包含不可忽略的方位角度相关的残余运动误差.分析了这种运动误差孔径依赖性对机载SAR成像质量的影响,它将造成图像的几何失真和方位散焦.提出了一种基于子孔径数据处理的补偿方法,根据雷达瞬时照射时刻与多普勒频率之间的关联性对数据进行方位向上的分段和补偿,可以直接嵌入联合一阶运动补偿和二阶运动补偿的成像处理流程中.仿真结果表明此孔径依赖性运动补偿方法进一步改善了图像的聚焦质量.     

Validation of an active transponder for KOMPSAT-5 SAR image calibration

This paper describes the development and validation of a transportable active transponder designed for the image calibration of Korea Multi-Purpose Satellite-5 (KOMPSAT-5) with a synthetic aperture radar (SAR). Ground targets are essential in SAR image calibration. The environment for the deployment of ground targets for SAR image calibration should provide uniformity and minimum interference. The Amazon or deserts are regarded as desirable environments. However, such environments for SAR image calibration are difficult to find in Korea. Thus, it will be advantageous to have an active transponder whose performance will not be severely limited by the absence of such uniform environment. We have therefore developed an active transponder which has an adjustable internal delay and into which the orbit data of an arbitrary satellite can be loaded. The stored obit data with the aid of an internal global positioning system (GPS) receiver and gyroscope enables the active transponder to point to a selected satellite. In addition, a virtual deployment of the active transponder is possible due to its adjustable internal delay. Thus, the developed active transponder can be deployed at any place without environmental constraint. The performance of the developed active transponder is validated using the satellite TerraSAR-X, which is already in operation. The test results show that the active transponder is successfully compliant with the requirements for KOMPSAT-5 image calibration.     

chirp-scaling算法中运动补偿问题研究

由于避免了插值计算,在大前视角和大范围成像时,chirp-scaling算法(CSA)的性能优于距离-多普勒算法(RDA).自聚焦算法在SAR成像处理中通常是必不可少的,但是现有的自聚焦算法几乎都是与RDA相结合的.本文提出了能够将自聚焦算法与CSA相结合的方法,使得CSA更具有实用性.本文同时也提出了将基于运动传感器的运动补偿和基于雷达数据的自聚焦算法与CSA结合的方法.该方法非常适合于高分辨率机载SAR成像处理.      

An optimal selection of probability distribution functions for unsupervised land cover classification of PALSAR-2 data

Different types of classification techniques are available in the literature for the classification of Synthetic Aperture Radar (SAR) data into various land cover classes. Various SAR images are available for land cover classification such as ALOS PALSAR (PALSAR-1, PALSAR-2), RADARSAT and ENVISAT. In this paper, we have attempted to explore probability distribution function (pdf) based land cover classification using PALSAR-2 data. Over 20 different statistical distribution functions are analyzed for different classes based on statistical parameters. Probability distribution functions are selected based on Chi-squared goodness of fit test for each individual class. A decision tree based classifier is developed for classification based on the selected pdf functions and its statistical parameters. The proposed classification approach has an accuracy of 83.93%.     

机载设备外场数据的可靠性增长分析

对我国航空机载设备外场数据的性质进行分析后,提出该种数据是变动母体混合数据,不同于通常用于可靠性估计的不变母体数据。提出外场数据中含有可靠性增长信息。 为利用外场数据来分析和评估航空机载设备的可靠性增长和可靠性状态,提出一个数学模型。模型的基本原理是最小二乘法。为说明模型的使用提供了一个实例。     

TOPSAR data focusing based on azimuth scaling preprocessing

Both Doppler spectral aliasing and azimuth output time folding simultaneously exist in TOPSAR (Terrain Observation by Progressive Scans) raw data. Resampling in both Doppler frequency and azimuth time domain can resolve the azimuth aliasing problem but with the seriously increased computational complexity and memory consumption. According to the special characteristics of TOPSAR raw data support in the slow time/frequency domain (TFD), the presented azimuth scaling preprocessing step is introduced to not only resolve the Doppler spectral aliasing problem but also reduce the increased azimuth samples. Furthermore, the correction of sawtoothed azimuth antenna pattern (AAP) becomes easy to be implemented. The following conventional stripmap processor can be adopted to focus the residual TOPSAR raw data but with the result of azimuth aliased TOPSAR image. The mosaic approach, which has been presented to unfold azimuth aliased ScanSAR image, is exploited to resolve the problem of azimuth output folding in TOPSAR mode. Simulation results and pulse response parameters are given to validate the presented imaging approach.     

一种星载SAR模糊区回波信号仿真方法

模糊度是星载合成孔径雷达(SAR,Synthetic Aperture Radar)星地一体化系统方案设计中的重要技术指标.为了定量化研究模糊度对图像质量的影响,提出了一种星载SAR模糊区回波信号的仿真方法.该方法采用星载SAR模糊区回波信号模型.利用该方法生成包含观测区场景和模糊区场景的星载SAR回波信号,经成像处理后可以获得具有模糊特性的SAR图像.该仿真方法为定量化研究模糊度与图像质量之间的关系提供仿真工具,它能够反映模糊区目标的图形特征,为SAR图像的解译判读提供参考依据.计算机仿真结果验证了该方法的有效性.