Collaborative Research: NSWP--Scintillation-Scale Ionospheric Imaging using GPS and other RF Data in Inverse Diffraction Algorithms

合作研究：NSWP——在逆衍射算法中使用 GPS 和其他 RF 数据进行闪烁尺度电离层成像

• 批准号: 0720209
• 负责人: Mark Psiaki
• 金额: $ 23.69万
• 依托单位: Cornell University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-09-01 至 2012-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0720209&HistoricalAwards=false
• 关键词: Collaborative; Research; NSWP; Scintillation; Scale

This project will infer fine-scale electron density variations of the equatorial ionosphere by developing and applying estimation algorithms to data recorded from scintillating GPS radio signals. The resulting electron density profiles will provide images of the bubble structures that are thought to cause the phenomena of radio frequency scintillations and equatorial spread-F. The project will include algorithm development, data collection campaigns, and data analysis. The algorithms to be developed will perform diffraction tomography calculations; the input data are received Radio Frequency (RF) signal amplitudes and phases from an array of receivers that are experiencing scintillations. The algorithms will estimate electron density profiles by developing and applying model estimation/inversion techniques to models such as a phase screen with Fresnel forward scattering. The estimation techniques will exploit the availability of dual-frequency GPS scintillation data that can be monitored because of new civilian GPS L2 signals now becoming available. They will also exploit the ability of GPS to make group-delay measurements; use of these data will follow development of a model predicting how group delay is affected by a disturbed ionosphere. The algorithms will be applied to data from two types of equatorial scintillation collection campaigns. One type of campaign will collect data using small arrays of wide-band digital storage receivers and MATLAB post-processing to acquire and track scintillating signals. The second type will use a medium sized array of real-time GPS software radio receivers. Some of the effort will go toward completing development of the latter type of receiver. Two distinctive features of this project are its use of very robust receiver technology, which will enable collection of very accurate RF amplitude and phase data for very strong scintillations and its development of generalized estimation/inversion algorithms. These algorithms that go beyond the capabilities of currently existing or proposed algorithms in their use of multi-frequency data, in their problem formulations, and in their algorithmic implementation based on optimization or fixed-point methods. The project focuses on very strong scintillations since these are the most important from an operational standpoint since they have the biggest impact on communications and navigation signals. The project's broader impacts include the development of instruments that can be used in education as well as in research and the improved communication and navigation system reliability that will result from an improved understanding of scintillations.

该项目将通过开发和应用估计算法来推断赤道电离层的精细电子密度变化，方法是对闪烁的全球定位系统无线电信号记录的数据进行估计。由此产生的电子密度分布将提供气泡结构的图像，这些气泡结构被认为是导致射频闪烁和赤道扩散-F现象的原因。该项目将包括算法开发、数据收集活动和数据分析。将要开发的算法将执行衍射层析成像计算；输入数据是从经历闪烁的接收器阵列接收的射频(RF)信号的幅度和相位。这些算法将通过开发和应用模型估计/反演技术来估计电子密度分布，这些模型例如具有菲涅尔前向散射的相位屏。估计技术将利用双频全球定位系统闪烁数据的可用性，由于新的民用全球定位系统L2信号现已可用，可以监测这些数据。他们还将利用GPS进行群体延迟测量的能力；这些数据的使用将在开发预测群体延迟如何受到干扰的电离层影响的模型之后进行。这些算法将应用于两种类型的赤道闪烁采集活动的数据。一种类型的活动将使用宽带数字存储接收器的小阵列和MatLab后处理来收集数据，以获取和跟踪闪烁信号。第二类将使用中等大小的实时GPS软件无线电接收器阵列。其中一些努力将用于完成后一种类型接收器的开发。该项目的两个显著特点是它使用了非常强大的接收器技术，这将使收集非常准确的射频幅度和相位数据来实现非常强的闪烁，以及开发通用的估计/反演算法。这些算法在使用多频率数据、问题描述以及基于最优化或定点方法的算法实现方面超出了当前现有或建议的算法的能力。该项目侧重于非常强的闪烁，因为从操作的角度来看，这些闪烁是最重要的，因为它们对通信和导航信号的影响最大。该项目的更广泛影响包括开发可用于教育和研究的仪器，以及提高通信和导航系统的可靠性，这将导致对闪烁的更好理解。