An empirical InSAR-optical fusion approach to mapping vegetation canopy height

Exploiting synergies afforded by a host of recently available national-scale data sets derived from interferometric synthetic aperture radar (InSAR) and passive optical remote sensing, this paper describes the development of a novel empirical approach for the provision of regional- to continental-scale estimates of vegetation canopy height. Supported by data from the 2000 Shuttle Radar Topography Mission (SRTM), the National Elevation Dataset (NED), the LANDFIRE project, and the National Land Cover Database (NLCD) 2001, this paper describes a data fusion and modeling strategy for developing the first-ever high-resolution map of canopy height for the conterminous U.S. The approach was tested as part of a prototype study spanning some 62,000 km² in central Utah (NLCD mapping zone 16). A mapping strategy based on object-oriented image analysis and tree-based regression techniques is employed. Empirical model development is driven by a database of height metrics obtained from an extensive field plot network administered by the USDA Forest Service-Forest Inventory and Analysis (FIA) program. Based on data from 508 FIA field plots, an average absolute height error of 2.1 m (r = 0.88) was achieved for the prototype mapping zone.     

一种新的InSAR基线估计方法

针对InSAR技术中基线估计误差对DEM精度的影响,从传统的基线估计方法入手,提出了一种新的估计基线参数的方法,并用仿真实验做了论证.结果表明,该方法比以往传统的方法得到的基线参数的精度更高,运算速度更快,应用范围更加广泛.     

Forest biomass mapping from lidar and radar synergies

The use of lidar and radar instruments to measure forest structure attributes such as height and biomass at global scales is being considered for a future Earth Observation satellite mission, DESDynI (Deformation, Ecosystem Structure, and Dynamics of Ice). Large footprint lidar makes a direct measurement of the heights of scatterers in the illuminated footprint and can yield accurate information about the vertical profile of the canopy within lidar footprint samples. Synthetic Aperture Radar (SAR) is known to sense the canopy volume, especially at longer wavelengths and provides image data. Methods for biomass mapping by a combination of lidar sampling and radar mapping need to be developed.In this study, several issues in this respect were investigated using aircraft borne lidar and SAR data in Howland, Maine, USA. The stepwise regression selected the height indices rh50 and rh75 of the Laser Vegetation Imaging Sensor (LVIS) data for predicting field measured biomass with a R² of 0.71 and RMSE of 31.33 Mg/ha. The above-ground biomass map generated from this regression model was considered to represent the true biomass of the area and was used as a reference map since no better biomass map exists for the area. Random samples were taken from the biomass map and the correlation between the sampled biomass and co-located SAR signature was studied. The best models were used to extend the biomass from lidar samples into all forested areas in the study area, which mimics a procedure that could be used for the future DESDYnI mission. It was found that depending on the data types used (quad-pol or dual-pol) the SAR data can predict the lidar biomass samples with R² of 0.63-0.71, RMSE of 32.0-28.2 Mg/ha up to biomass levels of 200-250 Mg/ha. The mean biomass of the study area calculated from the biomass maps generated by lidar-SAR synergy was within 10% of the reference biomass map derived from LVIS data. The results from this study are preliminary, but do show the potential of the combined use of lidar samples and radar imagery for forest biomass mapping. Various issues regarding lidar/radar data synergies for biomass mapping are discussed in the paper.     

基于标志点的InSAR系统仿真性能评估方法

系统仿真实验对于天基InSAR系统的总体设计和关键技术验证意义重大,性能评估是其中的关键环节之一。建立了由三大类共8项指标组成的InSAR系统性能指标体系,提出了基于标志点的InSAR系统仿真性能评估方法。该方法通过在仿真地面场景中合理布设标志点,并以标志点作为评估样本点来计算各项指标,可达到与理想干涉量评估方法相近的指标计算精度,同时避免了理想干涉量评估方法稳健性不足的问题,且计算效率更高。仿真实验结果验证了评估方法的有效性。     

对配准误差稳健的多基线相位展开方法

提出了一种对配准误差稳健的多基线相位展开方法.该方法首先根据配准误差的方向来确定最优联合观测矢量,进而确定存在配准误差时的真实导向矢量,并且用此导向矢量进行波束形成来进行相位展开,能够同时完成图像配准、干涉相位噪声滤波和相位展开,因此可以在SAR图像配准精度很差(可以允许达到一个分辨单元)的条件下得到稳健的相位展开性能,仿真结果证明了此方法的有效性.     

基于卡尔曼滤波的InSAR柔性基线距离测量

对于柔性长基线构型的双天线InSAR系统,基线矢量动态偏移产生的误差会降低系统的成像质量,并最终影响高程精度。针对单相机和激光测距仪组合测量系统中如何提高基线距离向精度的问题,提出了一种基于卡尔曼滤波的基线距离测量方法。建立了基线距离向抖动数学模型,在此模型基础上提出了基于卡尔曼滤波的动态测量方法,对该方法进行了动态仿真分析。仿真结果表明,在几十米的测量距离内,该方法能够将基线距离向的测量精度降低到亚毫米量级,是测量基线距离的有效方法。     

双通道太赫兹成像雷达研究

介绍了一种具有双接收通道的太赫兹成像雷达,雷达工作频率为216 GHz,系统设计中,采用直接数字式频率合成器以及频率综合等方式,产生具有800 MHz 带宽的Ku 波段线性调频连续波信号,功分后分别与两个点频信号进行混频,产生36 GHz依400 MHz 的射频信号以及35. 95 GHz依400 MHz 的本振信号,分别驱动太赫兹发射机和接收机。本振信号功分两路,送入两个接收机,接收采用去斜接收体制,从而降低数据率。该雷达采用了6 倍频太赫兹发射模块,最终产生系统带宽为4. 8 GHz,从而获得3 cm 的距离分辨率。文中还重点研究了宽带系统标校,并开展了高分辨逆合成孔径成像实验,为后续太赫兹干涉合成孔径成像雷达研究奠定基础。     

InSAR中基于干涉图质量参数的相位展开

本文分析了二维相位展开算法的特点,探讨了基于干涉图质量参数的相位展开方法。按干涉图质量优劣排序,对InSAR干涉图进行相位展开,可以有效减小截断相位中无效点对相位展开结果的影响。文中给出了算法的详细描述,以及按干涉图质量参数排序进行相位展开的实验结果。     

基于加权相关信号子空间的多频相位融合方法

针对多频干涉合成孔径雷达(InSAR)干涉信号不同频率分量的相位融合问题,提出基于加权相关信号子空间方法(CSSM)的多频相位融合方法。该融合方法采用联合像素模型构建信号模型;对 CSSM构造聚焦矩阵的思想进行改进,通过对各频率分量对应的协方差矩阵进行加权聚焦应对不同频率分量的信噪比差异;并采用联合子空间投影方法估计干涉相位。仿真数据和 SIR-C雷达实际数据验证表明,该方法能够有效改善多频 InSAR的干涉相位估计性能。     

一种新的InSAR相位解缠算法

干涉相位解缠直接影响到干涉合成孔径雷达(InSAR)高程测量精度,是InSAR处理及其重要的一步。文中在研究了最小二乘法相位解缠的基础上,提出了一种基于解缠相位误差迭代补偿的加权最小二乘法。首先,采用加权最小二乘法得到相位解缠的初值,然后,再通过对解缠误差相位的迭代补偿,对解缠效果进行优化。另外,针对迭代次数的合理选择,还设计了一种迭代机制,避免了迭代次数过多引入的补偿冗余和迭代次数过少导致的补偿不足。相比最小二乘法,该方法通过加权处理对相位噪声的全局影响进行了约束;通过误差迭代补偿进一步大大提高了解缠精度。仿真试验结果表明:文中所提方法具有优越性。