多变量全局寻优与智能优化在星座组网中的应用

顶层任务规划通常与星座组网紧密结合，小卫星分散灵活的特性尤其适用于星群规模化在轨运行。针对热点区域覆盖和全球覆盖的不同任务需求，提出了对构型多变量进行全局寻优和利用智能优化技术进行星座构型优化的方法，两种优化方法可分别获得小规模星群最优效能与超大型星群的较优效能。优化方法不受轨道类型和任务目标分布的约束，具有良好的鲁棒性。     

Analysis and design of Cubesat constellation for the Mediterranean south costal monitoring against illegal immigration

Costal monitoring is focused on fast response to illegal immigration and illegal ship traffic. Especially, the illegal ship traffic has been present in media since April 2015, as the number of reported deaths of immigrants crossing the Mediterranean significantly increased. Satellite images provide a possibility to at least partially control both types of events. This paper defines the principal criteria to select the best satellite constellation architecture for maritime and coastal monitoring, filling the gaps of imagery techniques in term of real-time control. The primary purpose of a constellation is to obtain global measurement improving the temporal resolution. The small size and low-cost are the main factors, which make CubeSats ideal for use in constellations. We propose a constellation of 9 Cubesats distributed evenly in 3 different planes. This reduces the revisit time enhancing the coverage duration. In addition, it also allows observing fire, damage on building and similar disasters. In this analysis, the performance criteria were reported such as the revisit time, the vision duration and the area coverage.     

Built-up land mapping capabilities of the ASTER and Landsat ETM+ sensors in coastal areas of southeastern China

Worldwide urbanization has accelerated expansion of urban built-up lands and resulted in substantial negative impacts on the global environments. Precisely measuring the urban sprawl is becoming an increasing need. Among the satellite-based earth observation systems, the Landsat and ASTER data are most suitable for mesoscale measurements of urban changes. Nevertheless, to date the difference in the capability of mapping built-up land between the two sensors is not clear. Therefore, this study compared the performances of the Landsat-7 ETM+ and ASTER sensors for built-up land mapping in the coastal areas of southeastern China. The comparison was implemented on three date-coincident image pairs and achieved by using three approaches, including per-band-based, index-based, and classification-based comparisons. The index used is the Index-based Built-up Index (IBI), while the classification algorithm employed is the Support Vector Machine (SVM). Results show that in the study areas, ETM+ and ASTER have an overall similar performance in built-up land mapping but also differ in several aspects. The IBI values determined from ASTER were consistently higher than from ETM+ by up to 45.54% according to percentage difference. The ASTER also estimates more built-up land area than ETM+ by 5.9–6.3% estimated with the IBI-based approach or 3.9–6.1% with the SVM classification. The differences in the spectral response functions and spatial resolution between relative spectral bands of the two sensors are attributed to these different performances.     

An approach to multi-temporal MODIS image analysis using image classification and segmentation

This paper discusses an approach for river mapping and flood evaluation based on multi-temporal time series analysis of satellite images utilizing pixel spectral information for image classification and region-based segmentation for extracting water-covered regions. Analysis of MODIS satellite images is applied in three stages: before flood, during flood and after flood. Water regions are extracted from the MODIS images using image classification (based on spectral information) and image segmentation (based on spatial information). Multi-temporal MODIS images from “normal” (non-flood) and flood time-periods are processed in two steps. In the first step, image classifiers such as Support Vector Machines (SVM) and Artificial Neural Networks (ANN) separate the image pixels into water and non-water groups based on their spectral features. The classified image is then segmented using spatial features of the water pixels to remove the misclassified water. From the results obtained, we evaluate the performance of the method and conclude that the use of image classification (SVM and ANN) and region-based image segmentation is an accurate and reliable approach for the extraction of water-covered regions.     

基于高分四号数据的多时相多通道云检测算法

针对高分四号（GF-4）卫星影像波段较少导致传统云检测算法难以区分云与冰雪像元的问题,提出一种多时相多通道云检测算法。该算法首先对GF-4卫星影像进行辐射定标和配准,然后利用云与典型地表的光谱差异得到潜在云像元,之后利用序列GF-4卫星影像之间的差异识别出移动的云像元,最后利用中红外波段反演地表亮度温度来去除冰雪像元。该算法在海南、辽宁和安徽3个研究区域进行验证,并将检测结果与传统单时相云检测算法、支持向量机（SVM）云检测算法和实时差分（RTD）云检测算法的检测结果进行对比。结果表明,该算法优于其他3种云检测算法,准确识别率均达到90%以上,误检率均低于5%,有利于GF-4卫星影像的进一步利用。     

Comparison of Landsat OLI,ASTER, and Sentinel 2A data in lithological mapping : A Case study of Rich area (Central High Atlas,Morocco)

The eastern part of the Rich area consists of the massive Paleozoic and Meso-Cenozoic cover formations that present the geodynamic development of the study area, where is characterized by various carbonate facies of Jurassic age. The geographical characteristic of the study area leaves the zone difficult to map by conventional methods. The objective of this work focuses on the mapping of the constituent lithological units of the study area using multispectral data of Landsat OLI, ASTER, and Sentinel 2A MSI. The processing of these data is based on a precise methodology that distinguishs and highlights the limits of the different lithological units that have an approximate similarity of spectral signature. Three techniques were used to enhance the image including Principal Component Analysis (PCA), Minimum Noise Fraction (MNF), and Independent Component Analysis (ICA). Lithological mapping was performed using two types of supervised classification : Maximum likelihood classifier (MLC) and Support Vector Machine (SVM).The results of processing data show the effectiveness of Sentinel 2A data in mapping of lithological units than the ASTER and Landsat OLI data. The classification evaluation of two methods of the Sentinel 2A MSI image showed that the SVM method give a better classification with an overall accuracy of 93,93% and a Kappa coefficient of 0.93, while the MLC method present an overall accuracy of 82,86% and a Kappa coefficient of 0.80. The results of mapping obtained show a good correlation with the geological map of the study area as well as the efficiency of remote sensing in identification of different lithological units in the Central High Atlas.     

Operation and Application of A, B Satellites for Environment and Disaster Monitoring and Forecasting

Environment and disaster monitoring and forecasting small satellite constellation A and B satellites (HJ-1-A, B) are called "environment and disaster reduction satellites A and B' for short. The constellation adopts a 10:30 LT sun-synchronous circular orbit, with orbit altitude of 649 km. HJ-1-A and HJ-1-B are distributed with a phase difference of 180o in the same orbital plane, so as to enhance the time resolution of earth observation. The satellites have orbit maintenance capability, the lifetime is 3 years. Both satellites adopt CAST968 platforms. Two wide-coverage multispectral CCD cameras with resolution 30 m and width 700 km, a super-spectral imager with resolution 100 m and width 50 km as well as a data transmission subsystem of 120 Mbit/s are deployed on HJ-1-A, which also carries Ka communication testing equipment of Thailand. HJ-1-B has two wide-coverage multispectral CCD cameras (the same as satellite A), one infrared camera with resolution 150 m and width 720 km and a data transmission subsystem of 60 Mbit/s. The coverage period of the wide-coverage multispectral CCD camera is 48 hours. The revisit period of super-spectral imager is 96 hours and the coverage period of infrared camera is 96 hours.      

基于覆盖圆的太阳同步回归轨道卫星目标轨迹调整方法

遥感卫星星座在环境监测、地理测绘等领域运用中,需要考虑目标轨迹分布的优化问题.轨迹分布与星座的重访能力和进出站间隔保持等应用需求密切相关.目前对星下点轨迹分布的优化和调整还缺乏准确实用的方法,存在卫星数目增多带来的计算量增加问题和对多种需求综合考虑不够的问题.为了克服现有技术的不足,解决太阳同步回归轨道遥感卫星星座的目...     

Satellite measurements of atmospheric composition

Since 1978 a number of satellite borne sensors have been used to measure the composition of the earth's atmosphere. These include the LIMS and SAMS instruments on the Nimbus 7 satellite (launched in October 1978), the SAGE instrument on the AEM2 satellite (launched in february 1979) and various instruments on the SME spacecraft (launched October 1981). For many species, these have provided the first abundance measurements with high spatial and temporal resolution and with global coverage. In this paper the composition measurements that have become available from these programs will be reviewed. The paper will then describe some recent studies that have made use of the new data. As it is the exclusive subject of another invited paper, ozone will not be discussed in in any detail.     

Remote sounding of atmospheric gravity waves with satellite limb and nadir techniques

Recent advances in satellite techniques hold great potential for mapping global gravity wave (GW) processes at various altitudes. Poor understanding of small-scale GWs has been a major limitation to numerical climate and weather models for making reliable forecasts. Observations of short-scale features have important implication for validating and improving future high-resolution numerical models. This paper summarizes recent GW observations and sensitivities from several satellite instruments, including MLS, AMSU-A, AIRS, GPS, and CLAES. It is shown in an example that mountain waves with horizontal wavelengths as short as 30 km now can be observed by AIRS, reflecting the superior horizontal resolution in these modern satellite instruments. Our studies show that MLS, AMSU-A and AIRS observations reveal similar GW characteristics, with the observed variances correlated well with background winds. As a complementary technique, limb sounding instruments like CRISTA, CLAES, and GPS can detect GWs with better vertical but poorer horizontal resolutions. To resolve different parts of the broad GW spectrum, both satellite limb and nadir observing techniques are needed, and a better understanding of GW complexities requires joint analyses of these data and dedicated high-resolution model simulations.     

小卫星侦察星座性能评估研究

针对小卫星侦察星座性能评估问题，从覆盖、成本和弹性三方面对小卫星侦察星座的性能指标进行研究，分别构建了考虑存储容量约束的覆盖能力评估模型、成本估计模型以及弹性能力评估模型。在覆盖能力评估模型中，将卫星存储容量作为约束条件，结合卫星覆盖几何模型分析了卫星对地侦察的工作条件，提出考虑存储容量的覆盖指标计算方法；通过小卫星成本模型(small satellite cost model,SSCM)对星座各分系统的成本进行估计；在弹性评估模型中，提出了星座性能损失率指标，并根据星座失效状态概率函数确定了不同失效状态下星座性能损失率的权重。将上述模型应用于SkySat和吉林一号星座的性能评估过程中，结果表明SkySat比吉林一号覆盖能力强、成本低，弹性差。提出的三个模型可用于评价星座优劣，为小卫星侦察星座的建设和性能评估工作提供参考。     

Design of BDS-3 integrity monitoring and preliminary analysis of its performance

With the improvement in the service accuracy and expansion of the application scope of satellite navigation systems, users now have high demands for system integrity that are directly related to navigation safety. As a crucial index to measure the reliability of satellite navigation systems, integrity is the ability of the system to send an alarm when an abnormity occurs. The new-generation Beidou Navigation Satellite System (BDS-3) prioritized the upgrading of system integrity as an important objective in system construction. Because the system provides both basic navigation and satellite-based augmentation system (SBAS) services by the operational control system, BDS-3 adopts an integrated integrity monitoring and processing strategy that applies satellite autonomous integrity monitoring and ground-based integrity monitoring for both the basic navigation service and SBAS navigation service. BDS-3 also uses an improved and refined integrity parameter system to provide slow, fast and real-time integrity parameters for basic navigation, and provide SBAS-provided integrity information messages in accordance with Radio Technical Commission for Aeronautics (RTCA) specification and dual frequency, multi-constellation (DFMC) specification to support the SBAS signal frequency, single constellation operation and DFMC operation respectively. The performance of BDS-3 system integrity monitoring is preliminarily verified during on-orbit testing in different states, including normal operation, satellite clock failure and satellite ephemeris failure. The results show that satellite autonomous integrity monitoring, ground-based integrity monitoring and satellite-based augmentation all correctly work within the system. Satellite autonomous integrity monitoring can detect satellite clock failure but not satellite orbit failure. However, ground-based integrity monitoring can detect both. Moreover, the satellite-based augmentation integrity system monitors the differential range error after satellite ephemeris and clock error corrections based on user requirements. Compared to the near minute-level time-to-alert capability of ground-based integrity monitoring, satellite autonomous integrity monitoring reduces the system alert time to less than 4 s. With a combined satellite-ground monitoring strategy and the implementation of different monitoring technologies, the BDS-3 integrity of service has been considerably improved.     

An object-level strategy for pan-sharpening quality assessment of high-resolution satellite imagery

Current satellite imaging systems offer a trade-off between high spatial and high spectral resolution providing panchromatic images at a higher spatial resolution and multispectral images at a lower spatial resolution but rich in spectral information while a wide range of applications need the highest level of this information, simultaneously. Image fusion techniques as means of enhancing the information content of initial panchromatic and multispectral images produce new images, titled pan-sharpened, which inherent the advantages of the initial images. Considering the impact of fusion accuracy on the quality of corresponding applications, it is necessary to evaluate the quality of these processed images. During the last decade, a lot of quality evaluation metrics have been proposed which are mostly inspired by traditional image quality metrics. These methods are mostly based on applying quality metrics at the pixel level and evaluating final quality value based on averaging of obtained metric values through the whole image. However, obtained results clearly show that the behaviour of image fusion quality is inconsistent amongst different image objects. In this article, by applying image fusion quality metrics (IFQMs) to image objects, an object-level strategy for quality assessment of the image fusion process is proposed. The proposed strategy is applied to different satellite imagery covering residential and agricultural areas. Experimental results show higher capabilities of object-level quality assessment strategy in the quality assessment of the fusion process. Evaluating fusion quality at the object level provides the potential of fusion quality assessment for each individual image object in compliance with different parameters such as the type of objects and the effective size of objects in data set.     

星载合成孔径雷达的分辨特性

较全面和详细地论述了星载合成孔径雷达（ＳＡＲ）的分辨特性;导出了距离分辨率、方位分辨率和辐射分辨率的定量关系式;阐述了多种辐射分辨率定义的内涵,并对其错误概率进行了比较;介绍了ＳＡＲ图像的分辨体积和可懂度的概念,并且完成了ＳＡＲ图像分辨特性的方形等效。这些论述对于ＳＡＲ图像质量的评估和比较,以及系统参数的折衷设计具有重要意义。     

Using the MIR bands in vegetation indices for the estimation of grassland biophysical parameters from satellite remote sensing in the Alps region of Trentino (Italy)

Development of new methods for estimating biophysical parameters can be considered one of the most important targets for the improvement of grassland parameters estimation at full canopy cover. In fact, accurate assessment methods of biophysical characteristics of vegetation are needed in order to avoid the uncertainties of carbon terrestrial sinks.

Remote sensing is a valid tool for scaling up ecosystem measurements towards landscape levels serving a wide range of applications, many of them being related to carbon-cycle models. The aim of this study was to test the suitability of satellite platform sensors in estimating grassland biophysical parameters such as LAI, biomass, phytomass, and Green herbage ratio (GR). Also, we wanted to compare some of the most common NIR and red/green-based vegetation indices with ones that also make use of the MIR band, in relation to their ability to predict grassland biophysical parameters.

Ground-truth measurements were taken on July 2003 and 2004 on the Monte Bondone plateau (Italian Alps, Trento district) in grasslands varying in land use and management intensities. From satellite platforms, an IRS-1C-LISS III image (18/07/2003; 25 m resolution in the visible-NIR and 70 m resolution in the MIR) and a SPOT 5 image (27/07/2004, 10 m resolution in the visible-NIR and MIR) were used.

LAI, biomass, and phytomass measurements showed logarithmic relationships with the investigated NIR and red/green-based indices. GreenNDVI showed the highest R² values (0.59, IRS 2003; 0.60, SPOT 2004). Index saturation occurred above approximately 100–150 g m⁻² of biomass (LAI 1.5–2). On the other hand, GR relationships were shown to be linear. MIR-based indices performed better than NIR and red/green-based ones in estimating biophysical variables, with no saturation effect. Biomass showed a linear regression with Canopy Index (MIR/green ratio) and with the Normalised Canopy Index (NCI) calculated as a normalised difference between MIR and green bands (IRS: R² = 0.91 and 0.90, respectively. SPOT: R² = 0.63 and 0.64). Similar correlations could also be found for LAI and phytomass, and GR predictability was shown to be higher than NDVI and GreenNDVI. According to these results obtained in the investigated areas, phytomass, biomass, LAI, and GR are linearly correlated with the investigated MIR band indices and as a result, these parameters could be estimated from the adopted satellite platforms with limited saturation problems.     

The NOAA satellites: A largely neglected tool in the land sciences

The NOAA satellite system comprises the polar-orbiting satellites which provide image data twice a day, and the geostationary satellites, which provide image data every 30 minutes. Data is provided in the visible, near infrared, and middle and far thermal infrared at 1 km resolution from the polar-orbiting satellites and in the visible at 1-km resolution and in the far thermal infrared at 8 km resolution from the geostationary satellites. Applications described include monitoring tectonic lineaments in Alaska, monitoring the Greenland Ice Sheet, mapping geomorphology in the Dakotas and monitoring volcano eruptions. Applications of the Heat Capacity Mapping Mission described include discriminating rock types and indications of mineral deposits. Current research into Land Sciences Applications are discussed and recommendations made for further areas of research.     

遥感器中的锁相转速控制

空间遥感器图像对地球要有一定的覆盖率,而且应有较高的地面景物分辨力。地面景物分辨力是衡量遥感器性能的重要指标。由于卫星的飞行将使地面景物在像片上的影像产生像移,所以必须进行精确的像移补偿,才能提高遥感器的地面景物分辨能力。设计了一个起动快、功耗小、抗干扰能力强、精度为0.1%的锁相环,它可以满足低轨道、地面景物分辨力为5m 的遥感器的使用要求。     

地下核试验监测中的卫星遥感技术及应用

卫星遥感技术在发现、监测、识别、定位和分析地下核试验中具有不可替代的独特作用, 且使得事先阻止核爆炸试验成为可能. 地下核试验的卫星核查与遥感监测是一个高度复杂的综合决策过程. 本文结合几个具体实例, 介绍了其中一些有效的遥感分析识别技术, 如图像序列分析、图像融合、变化检测、K-L变换、D-InSAR、数字三维地形、GIS数据库等. 卫星遥感的局限性在于, 其难以从物理上确认地下核爆炸事件且不可避免地存在虚警和漏警.      

高分四号卫星控制方案设计特点及在轨实现

高分四号(GF 4)是首颗地球静止轨道光学面阵遥感卫星.简要综述了国外该领域发展情况,重点介绍了高分四号卫星控制系统方案设计的主要特点,包括全星敏转移轨道技术、姿态小角度步进机动与快速稳定、以及阳光规避技术,并结合实际飞行情况介绍了上述技术的在轨验证情况,最后对后续该领域技术发展提出了展望     

距离相关系数融合GPR模型的卫星异常检测方法

卫星在轨运行期间，遥测数据表现形式通常为多维时间序列。高斯过程回归(GPR)模型可以为重要的遥测参数提供动态门限，及时发现隐藏在工程阈值内的故障征兆，但是高维卫星数据使得GPR模型具有局限性。因此，为获取与多个遥测参数相关的动态门限，在GPR模型的基础上，融合距离相关系数对预测变量进行选择，减少信息冗余和计算量，提高模型的可解释性，并估计模型的泛化误差以设置更合理的预测区间，提高模型的泛化能力，检测数据流的持续异常。对实际在轨卫星数据进行仿真实验，验证了距离相关系数融合GPR模型的卫星异常检测方法可以在卫星故障早期检测到数据异常，而且提高了模型的预测性能，降低了虚警率。