A generic level 1 simulator for spaceborne GNSS-R missions and application to GEROS-ISS ocean reflectometry

©2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.In the past decade Global Navigation Satellites System Reflectometry (GNSS-R) has emerged as a new technique for earth remote sensing for various applications, such as ocean altimetry and sea state monitoring. After the success of the GNSS-R demonstrator payloads aboard the UK-DMC or TDS-1 satellites; at present, there are several missions planned to carry GNSS reflectometers. The GNSS rEflectometry, Radio Occultation, and Scatterometry onboard International Space Station (GEROS-ISS) is an innovative ISS experiment exploiting GNSS-R technique to measure key parameters of ocean, land, and ice surfaces. For GEROS-ISS mission, the European Space Agency (ESA) supported the study of GNSS-R assessment of requirements and consolidation of retrieval algorithms (GARCA). For this, it was required to accurately simulate the GEROS-ISS measurements including the whole range of parameters affecting the observation conditions and the instrument, which is called GEROS-SIM. To meet these requirements, the PAU/PARIS end-to-end performance simulator (P$^{2}$EPS) previously developed by UPC BarcelonaTech was used as the baseline building blocks for the level 1 (L1) processor of GEROS-SIM. P$^{2}$EPS is a flexible tool, and is capable of systematically simulating the GNSS-R observations for spaceborne GNSS-R missions. Thanks to the completeness and flexibility, the instrument-to-L1 data module of GEROS-SIM could be implemented by proper modification and update of P$^{2}$EPS. The developed GEROS-SIM was verified and validated in the GARCA study as comparing to the TDS-1 measurements. This paper presents the design, implementation, and results of the GEROS-SIM L1 module in a generic way to be applied to GNSS-R instruments.Peer ReviewedPostprint (author's final draft

Potential synergetic use of GNSS-R signals to improve the sea-state correction in the sea surface salinity estimation: Application to the SMOS mission

It is accepted that the best way to monitor sea surface salinity (SSS) on a global basis is by means of L-band radiometry. However, the measured sea surface brightness temperature (TB) depends not only on the SSS but also on the sea surface temperature (SST) and, more importantly, on the sea state, which is usually parameterized in terms of the 10-m-height wind speed (U10) or the significant wave height. It has been recently proposed that the mean-square slope (mss) derived from global navigation satellite system (GNSS) signals reflected by the sea surface could be a potentially appropriate sea-state descriptor and could be used to make the necessary sea state TB corrections to improve the SSS estimates. This paper presents a preliminary error analysis of the use of reflected GNSS signals for the sea roughness correction and was performed to support the European Space Agency’s Soil Moisture and Ocean Salinity (SMOS) mission; the orbit and parameters for the SMOS instrument were assumed. The accuracy requirement for the retrieved SSS is 0.1 practical salinity units after monthly averaging over 2◦ × 2◦ boxes. In this paper, potential improvements in salinity estimation are hampered mainly by the coarse sampling and by the requirements of the retrieval algorithm, particularly the need for a semiempirical model that relates TB and mss.Postprint (published version

Information retrieval from spaceborne GNSS Reflectometry observations using physics- and learning-based techniques

This dissertation proposes a learning-based, physics-aware soil moisture (SM) retrieval algorithm for NASA’s Cyclone Global Navigation Satellite System (CYGNSS) mission. The proposed methodology has been built upon the literature review, analyses, and findings from a number of published studies throughout the dissertation research. Namely, a Sig- nals of Opportunity Coherent Bistatic scattering model (SCoBi) has been first developed at MSU and then its simulator has been open-sourced. Simulated GNSS-Reflectometry (GNSS-R) analyses have been conducted by using SCoBi. Significant findings have been noted such that (1) Although the dominance of either the coherent reflections or incoher- ent scattering over land is a debate, we demonstrated that coherent reflections are stronger for flat and smooth surfaces covered by low-to-moderate vegetation canopy; (2) The influ- ence of several land geophysical parameters such as SM, vegetation water content (VWC), and surface roughness on the bistatic reflectivity was quantified, the dynamic ranges of reflectivity changes due to SM and VWC are much higher than the changes due to the surface roughness. Such findings of these analyses, combined with a comprehensive lit- erature survey, have led to the present inversion algorithm: Physics- and learning-based retrieval of soil moisture information from space-borne GNSS-R measurements that are taken by NASA’s CYGNSS mission. The study is the first work that proposes a machine learning-based, non-parametric, and non-linear regression algorithm for CYGNSS-based soil moisture estimation. The results over point-scale soil moisture observations demon- strate promising performance for applicability to large scales. Potential future work will be extension of the methodology to global scales by training the model with larger and diverse data sets

Developing the Test Bench for a Next-Generation Bistatic GNSS Reflectometry Receiver Instrument

Recently, scientists have started to exploit global navigational satellite system (GNSS) signals for geophysical remote sensing using a technique called "reflectometry" (GNSS-R). This involves an airborne or spaceborne receiver measuring direct GNSS satellite signals as well as the reflected signals off of the surface of the Earth. This enables scientists to measure properties of Earth’s surface at the reflection point. NASA launched a constellation of eight micro-satellites, called CYGNSS, in December of 2016 that carried GNSS-R receivers. CYGNSS tracks reflected GPS signals to measure ocean wind speed for hurricane forecasting. Use of GPS signals has several advantages in terms of cost, temporal coverage, and spatial coverage. Researchers at The Ohio State University are involved in the CYGNSS Science Team and testing of first generation GNSS-R receivers. The success of the project so far has motivated a potential follow-on mission as researchers are identifying opportunities for improvement and expansion of reflectometry capabilities. A next-generation reflectometry receiver is being developed which should be capable of tracking more than the GPS L1 C/A-coded signal to increase the number of visible reflections. To evaluate the behavior of this new instrument, a test bench is implemented based on a test-system created for CYGNSS. The design and validation of the test bench is documented in this thesis. The test bench developed for CYGNSS is not capable of simulating other GNSS bands, cannot generate long-duration signals, and does not incorporate GNSS meta-data or navigational messages in its simulations. The purpose of this project is to improve the quality of the test bench hardware and software used to test GNSS-R instruments and add support for the new instrument's enhanced features. In this work we accomplish the following tasks: we assemble a transceiver from software defined radios; we modify the signal generator for parallel processing; we provide an efficient and simple user interface; we add support for the L1, L5, E1bc, and E5a bands; and we include actual satellite meta-data, including navigational messages and realistic timing information, in our simulations. Deliverable test signals, which are generated and transmitted by the completed system, are validated to confirm an accurate simulation of the receiver's space environment. Analysis of time-domain samples verifies modulation of spread-spectrum codes and simulated doppler shift. An FFT of these time-domain samples visually confirms the frequency contents of these signals in spectrum plots. Signal acquisition is performed on the files to identify PRN codes and verify the presence of multiple satellites. RF lab equipment verifies the frequency content of the test-system output. In the Summer of 2018, testing of the completed receiver will commence. We plan to subject the receiver to a 24-hour broadcast of a dual-band signal from the test bench according to the procedure outlined in a test plan developed by May 15th. We hope that this effort discloses any problems with the receiver prior to space deployment, at which time it will be impossible to make changes. This research provides a valuable tool for testing reflectometry receivers in the future. It is easily adapted for expansion of features and to add support for alternative applications. The test bench supports development of a valuable reflectometry instrument, which may facilitate the University's involvement in a follow-on mission to CYGNSS.NASANo embargoAcademic Major: Electrical and Computer Engineerin

GNSS reflectometry for land remote sensing applications

Soil moisture and vegetation biomass are two essential parameters from a scienti c and economical point of view. On one hand, they are key for the understanding of the hydrological and carbon cycle. On the other hand, soil moisture is essential for agricultural applications and water management, and vegetation biomass is crucial for regional development programs. Several remote sensing techniques have been used to measure these two parameters. However, retrieving soil moisture and vegetation biomass with the required accuracy, and the appropriate spatial and temporal resolutions still remains a major challenge. The use of Global Navigation Satellite Systems (GNSS) reflected signals as sources of opportunity for measuring soil moisture and vegetation biomass is assessed in this PhD Thesis. This technique, commonly known as GNSS-Reflectometry (GNSS-R), has gained increasing interest among the scienti c community during the last two decades due to its unique characteristics. Previous experimental works have already shown the capabilities of GNSS-R to sense small reflectivity changes on the surface. The use of the co- and cross-polarized reflected signals was also proposed to mitigate nuisance parameters, such as soil surface roughness, in the determination of soil moisture. However, experimental evidence of the suitability of that technique could not be demonstrated. This work analyses from a theoretical and an experimental point of view the capabilities of polarimetric observations of GNSS reflected signals for monitoring soil moisture and vegetation biomass. The Thesis is structured in four main parts. The fi rst part examines the fundamental aspects of the technique and provides a detailed review of the GNSS-R state of the art for soil moisture and vegetation monitoring. The second part deals with the scattering models from land surfaces. A comprehensive description of the formation of scattered signals from rough surfaces is provided. Simulations with current state of the art models for bare and vegetated soils were performed in order to analyze the scattering components of GNSS reflected signals. A simpli ed scattering model was also developed in order to relate in a straightforward way experimental measurements to soil bio-geophysical parameters. The third part reviews the experimental work performed within this research. The development of a GNSS-R instrument for land applications is described, together with the three experimental campaigns carried out in the frame of this PhD Thesis. The analysis of the GNSS-R and ground truth data is also discussed within this part. As predicted by models, it was observed that GNSS scattered signals from natural surfaces are a combination of a coherent and an incoherent scattering components. A data analysis technique was proposed to separate both scattering contributions. The use of polarimetric observations for the determination of soil moisture was demonstrated to be useful under most soil conditions. It was also observed that forests with high levels of biomass could be observed with GNSS reflected signals. The fourth and last part of the Thesis provides an analysis of the technology perspectives. A GNSS-R End-to-End simulator was used to determine the capabilities of the technique to observe di erent soil reflectivity conditions from a low Earth orbiting satellite. It was determined that high accuracy in the estimation of reflectivity could be achieved within reasonable on-ground resolution, as the coherent scattering component is expected to be the predominant one in a spaceborne scenario. The results obtained in this PhD Thesis show the promising potential of GNSS-R measurements for land remote sensing applications, which could represent an excellent complementary observation for a wide range of Earth Observation missions such as SMOS, SMAP, and the recently approved ESA Earth Explorer Mission Biomass.La humedad del suelo y la biomasa de la vegetaci on son dos parametros clave desde un punto de vista tanto cient co como econ omico. Por una parte son esenciales para el estudio del ciclo del agua y del carbono. Por otra parte, la humedad del suelo es esencial para la gesti on de las cosechas y los recursos h dricos, mientras que la biomasa es un par ametro fundamental para ciertos programas de desarrollo. Varias formas de teledetección se han utilizado para la observaci on remota de estos par ametros, sin embargo, su monitorizaci on con la precisi on y resoluci on necesarias es todav a un importante reto tecnol ogico. Esta Tesis evalua la capacidad de medir humedad del suelo y biomasa de la vegetaci on con señales de Sistemas Satelitales de Posicionamiento Global (GNSS, en sus siglas en ingl es) reflejadas sobre la Tierra. La t ecnica se conoce como Reflectometr í a GNSS (GNSS-R), la cual ha ganado un creciente inter es dentro de la comunidad científ ca durante las dos ultimas d ecadas. Experimentos previos a este trabajo ya demostraron la capacidad de observar cambios en la reflectividad del terreno con GNSS-R. El uso de la componente copolar y contrapolar de la señal reflejada fue propuesto para independizar la medida de humedad del suelo de otros par ametros como la rugosidad del terreno. Sin embargo, no se pudo demostrar una evidencia experimental de la viabilidad de la t ecnica. En este trabajo se analiza desde un punto de vista te orico y experimental el uso de la informaci on polarim etrica de la señales GNSS reflejadas sobre el suelo para la determinaci on de humedad y biomasa de la vegetaci on. La Tesis se estructura en cuatro partes principales. En la primera parte se eval uan los aspectos fundamentales de la t ecnica y se da una revisi on detallada del estado del arte para la observaci on de humedad y vegetaci on. En la segunda parte se discuten los modelos de dispersi on electromagn etica sobre el suelo. Simulaciones con estos modelos fueron realizadas para analizar las componentes coherente e incoherente de la dispersi on de la señal reflejada sobre distintos tipos de terreno. Durante este trabajo se desarroll o un modelo de reflexi on simpli cado para poder relacionar de forma directa las observaciones con los par ametros geof sicos del suelo. La tercera parte describe las campañas experimentales realizadas durante este trabajo y discute el an alisis y la comparaci on de los datos GNSS-R con las mediciones in-situ. Como se predice por los modelos, se comprob o experimentalmente que la señal reflejada est a formada por una componente coherente y otra incoherente. Una t ecnica de an alisis de datos se propuso para la separacióon de estas dos contribuciones. Con los datos de las campañas experimentales se demonstr o el bene cio del uso de la informaci on polarim etrica en las señales GNSS reflejadas para la medici on de humedad del suelo, para la mayor a de las condiciones de rugosidad observadas. Tambi en se demostr o la capacidad de este tipo de observaciones para medir zonas boscosas densamente pobladas. La cuarta parte de la tesis analiza la capacidad de la t ecnica para observar cambios en la reflectividad del suelo desde un sat elite en orbita baja. Los resultados obtenidos muestran que la reflectividad del terreno podr a medirse con gran precisi on ya que la componente coherente del scattering ser a la predominante en ese tipo de escenarios. En este trabajo de doctorado se muestran la potencialidades de la t ecnica GNSS-R para observar remotamente par ametros del suelo tan importantes como la humedad del suelo y la biomasa de la vegetaci on. Este tipo de medidas pueden complementar un amplio rango de misiones de observaci on de la Tierra como SMOS, SMAP, y Biomass, esta ultima recientemente aprobada para la siguiente misi on Earth Explorer de la ESA

센티미터 급 광역 보강항법 시스템의 반송파 위상 기반 보정정보 생성 알고리즘에 관한 연구

학위논문(박사)--서울대학교 대학원 :공과대학 기계항공공학부,2020. 2. 기창돈.Recently, the demand for high-precision navigation systems for centimeter-level service has been growing rapidly for various Global Navigation Satellite System (GNSS) applications. The network Real-Time Kinematic (RTK) is one of the candidate solution to provide high-accuracy position to user in real-time. However, the network RTK requires a lot of reference stations for nationwide service. Furthermore, it requires high-speed data-link for broadcasting their scalar-type corrections. This dissertation proposed a new concept of satellite augmentation system called Compact Wide-Area RTK, which provides centimeter-level positioning service on national or continental scales to overcoming the limitation of the legacy network RTK methods. Using the wide-area network of multiple reference stations whose distance is 200~1,000 km, the proposed system generates three types of carrier-phase-based corrections: satellite orbit corrections, satellite code/phase clock (CPC) corrections, tropospheric corrections. Through the strategy of separating the scalar-type corrections of network RTK into vector forms of each error component, it is enable to expand network RTK coverage to continental scale using a similar number of reference stations as legacy meter-level Satellite-Based Augmentation System (SBAS). Furthermore, it is possible to broadcast their corrections over a wide-area using geosynchronous (GEO) satellite with extremely low-speed datalink of 250 bps likewise of legacy SBAS. To sum up, the proposed system can improve position accuracy by centimeter-level while maintaining the hardware infrastructure of the meter-level legacy SBAS. This study mainly discussed on the overall system architecture and core algorithms for generating satellite CPC corrections and tropospheric corrections. This study proposed a new Three-Carrier Ambiguity Resolution (TCAR) algorithm using ionosphere-free combinations to correctly solve the integer ambiguity in wide-area without any ionospheric corrections. The satellite CPC corrections are calculated based on multiple stations for superior and robust performance under communication delay and outage. The proposed algorithm dramatically reduced the latency compensation errors and message amounts with compare to conventional RTK protocols. The tropospheric corrections of the compact wide-area RTK system are computed using GPS-estimated precise tropospheric delay and weather data based model together. The proposed algorithm adopts spherical harmonics function to significantly reduce the message amounts and required number of GPS reference stations than the network RTK and Precise Point Positioning-RTK (PPP-RTK), while accurately modeling the spatial characteristic of tropospheric delay with weather data together. In order to evaluate the user domain performance of the compact wide-area RTK system, this study conducted the feasibility test on mid-west and south USA using actual GPS measurements. As a result, the 95% horizontal position error is about 1.9 cm and the 95% vertical position error is 7.0 cm after the integer ambiguity is correctly fixed using GPS-only signals. The user ambiguity resolution takes about 2 minutes, and success-fix rate is about 100 % when stable tropospheric condition. In conclusion, the compact wide-area RTK system can provide centimeter-level positioning service to wide-area coverage with extremely low-speed data link via GEO satellite. We hope that this new system will consider as candidate solution for nationwide centimeter-level service such as satellite augmentation system of the Korea Positioning System (KPS).최근 자율주행자동차, 무인 드론 배송, 충돌 회피, 무인트랙터를 이용한 스마트 무인 경작 등 위성항법시스템(GNSS, Global Navigation Satellite System)을 사용하는 다양한 응용분야에서 수 cm 수준의 정밀 위치 정보에 대한 요구가 급격히 증가하고 있다. 본 학위논문에서는 1 m 급의 정확하고 신뢰성 높은 위치 서비스를 제공하는 기존의 정지궤도위성 기반 광역 보강항법 시스템(SBAS, Satellite-Based Augmentation System)의 기준국 인프라를 유지하면서 항법 성능을 수 cm 수준으로 향상시키기 위해 반송파 위상 기반의 초정밀 보정정보 생성 알고리즘에 관한 연구를 수행하였다. 실시간 정밀 측위(RTK, Real-Time Kinematic)는 반송파 위상 측정치에 포함된 미지정수를 정확하게 결정하여 수 cm 수준의 정밀 항법 서비스를 가능하게 하는 대표적인 기법이다. 그 중에서도 약 50~70 km 간격으로 분포된 다수의 기준국 정보를 활용하는 Network RTK 기법은 동적 사용자의 빠르고 정확한 위치 결정이 가능한 인프라로서 주목받고 있다. 하지만 스칼라 형태로 구성된 Network RTK 보정정보는 각 기준국 별로 관측된 위성 수에 따라 생성이 되기 때문에 보정 데이터 량이 상당히 방대하다. 메시지 전송에 필요한 데이터 량이 많을수록 고속의 통신 환경을 필요로 하며, 메시지 시간 지연이나 통신 단절에 매우 취약한 문제를 가지고 있다. 또한 스칼라 형태의 보정정보는 사용자와 기준국 간의 거리가 멀어질수록 보정 오차가 크게 발생하기 때문에 대륙 혹은 나라 규모의 광역에서 서비스하기 위해서는 수십~수백 개 이상의 기준국 인프라 구축이 필수적이다. 예를 들어, SBAS가 한반도 지역 서비스를 위해 5~7개의 기준국이 필요한 반면 Network RTK는 90~100개의 기준국이 필요하다. 즉 Network RTK는 시스템 구축 및 유지 비용이 SBAS 대비 약 15배 정도 많이 들게 된다. 본 논문에서는 기존 Network RTK의 문제점을 해결하기 위한 방법으로 대륙 급 광범위한 영역에서 실시간으로 cm급 초정밀 위치결정 서비스 제공이 가능한 Compact Wide-Area RTK 라는 새로운 개념의 광역보강항법시스템 아키텍처를 제안하였다. Compact Wide-Area RTK는 약 200~1,000 km 간격으로 넓게 분포된 기준국 네트워크를 활용하여 반송파 위상 기반의 정밀한 위성 궤도 보정정보, 위성 Code/Phase 시계 보정정보, 대류층 보정정보를 생성하는 시스템이다. 기존 스칼라 형태의 Network RTK 보정정보 대신 오차 요소 별 벡터 형태의 정밀 보정정보를 생성함으로써 데이터 량을 획기적으로 절감하고 서비스 영역을 확장할 수 있다. 최종적으로 SBAS와 마찬가지로 250 bps의 저속 통신 링크를 가진 정지궤도위성을 통해 광역으로 보정정보 방송이 가능하다. 본 논문에서는 3가지 보정정보 중 위성 Code/Phase 시계 보정정보와 대류층 보정정보 생성을 위한 핵심 알고리즘에 대해 중점적으로 연구하였다. 반송파 위상 기반의 정밀 보정정보 생성을 위해서는 먼저 미지정수를 정확하게 결정해야 한다. 본 논문에서는 삼중 주파수 반송파 위상 측정치의 무-전리층 조합을 활용하여 전리층 보정정보 없이도 정확하게 미지정수 결정 가능한 새로운 방법을 제안하였다. 위성 Code/Phase 시계 보정정보는 통신 지연 및 고장 시 우수하고 강건한 성능을 위해 다중 기준국의 모든 측정치를 활용하여 추정된다. 이 때 각 기준국 별 서로 다른 미지정수 때문에 발생하는 문제는 앞서 정확하게 결정된 기준국 간 이중차분 된 미지정수를 활용하여 수준을 조정하는 과정을 통해 해결이 가능하다. 그 결과 생성된 위성 Code/Phase 보정정보 메시지의 크기, 변화율, 잡음 수준이 크게 개선되었고, 통신 지연 시 오차 보상 성능이 기존 RTK 프로토콜 보다 99% 향상 됨을 확인하였다. 대류층 보정정보는 적은 수의 기준국 만을 활용하여 정확하게 대류층을 모델링하기 위해 자동 기상관측시스템으로부터 수집한 기상 정보를 추가로 활용하여 생성된다. 본 논문에서는 GNSS 기준국 네트워크로부터 정밀하게 추정된 반송파 위상 기반 수직 대류층 지연과 기상정보 기반으로 모델링 된 수직 대류층 지연을 함께 활용할 수 있는 새로운 알고리즘을 제안하였다. 구면조화함수를 사용하여 Network RTK 및 PPP-RTK 보다 필요한 메시지 양과 기준국 수를 크게 감소시키면서도 RMS 2 cm 수준으로 정확한 보정정보 생성이 가능함을 확인하였다. 본 논문에서 제안한 Compact Wide-Area RTK 시스템의 항법 성능을 검증하기 위해 미국 동부 지역 6개 기준국의 실측 GPS 데이터를 활용하여 테스트를 수행하였다. 그 결과 제안한 시스템은 미지정수 결정 이후 사용자의 95% 수평 위치 오차 1.9 cm, 95% 수직 위치 오차 7.0 cm 로 위치를 정확하게 결정하였다. 사용자 미지정수 결정 성능은 대류층 안정 상태에서 약 2분 내로 100% 의 성공률을 가진다. 본 논문에서 제안한 시스템이 향후 한국형 위성항법 시스템(KPS, Korean Positioning System)의 전국 단위 센티미터 급 서비스를 위한 알고리즘으로 활용되기를 기대한다.CHAPTER 1. Introduction 1 1.1 Motivation and Purpose 1 1.2 Former Research 4 1.3 Outline of the Dissertation 7 1.4 Contributions 8 CHAPTER 2. Overview of GNSS Augmentation System 11 2.1 GNSS Measurements 11 2.2 GNSS Error Sources 14 2.2.1 Traditional GNSS Error Sources 14 2.2.2 Special GNSS Error Sources 21 2.2.3 Summary 28 2.3 GNSS Augmentation System 29 2.3.1 Satellite-Based Augmentation System (SBAS) 29 2.3.2 Real-Time Kinematic (RTK) 32 2.3.3 Precise Point Positioning (PPP) 36 2.3.4 Summary 40 CHAPTER 3. Compact Wide-Area RTK System Architecture 43 3.1 Compact Wide-Area RTK Architecture 43 3.1.1 WARTK Reference Station (WRS) 48 3.1.2 WARTK Processing Facility (WPF) 51 3.1.3 WARTK User 58 3.2 Ambiguity Resolution and Validation Algorithms of Compact Wide-Area RTK System 59 3.2.1 Basic Theory of Ambiguity Resolution and Validation 60 3.2.2 A New Ambiguity Resolution Algorithms for Multi-Frequency Signals 65 3.2.3 Extra-Wide-Lane (EWL) Ambiguity Resolution 69 3.2.4 Wide-Lane (WL) Ambiguity Resolution 71 3.2.5 Narrow-Lane (NL) Ambiguity Resolution 78 3.3 Compact Wide-Area RTK Corrections 83 3.3.1 Satellite Orbit Corrections 86 3.3.2 Satellite Code/Phase Clock (CPC) Corrections 88 3.3.3 Tropospheric Corrections 89 3.3.4 Message Design for GEO Broadcasting 90 CHAPTER 4. Code/Phase Clock (CPC) Correction Generation Algorithm 93 4.1 Former Research of RTK Correction Protocol 93 4.1.1 Observation Based RTK Data Protocol 93 4.1.2 Correction Based RTK Data Protocol 95 4.1.3 Compact RTK Protocol 96 4.2 Satellite CPC Correction Generation Algorithm 100 4.2.1 Temporal Decorrelation Error Reduced Methods 102 4.2.2 Ambiguity Level Adjustment 105 4.2.3 Receiver Clock Synchronization 107 4.2.4 Averaging Filter of Satellite CPC Correction 108 4.2.5 Ambiguity Re-Initialization and Message Generation 109 4.3 Correction Performance Analysis Results 111 4.3.1 Feasibility Test Environments 111 4.3.2 Comparison of RTK Correction Protocol 113 4.3.3 Latency Compensation Performance Analysis 116 4.3.4 Message Data Bandwidth Analysis 119 CHAPTER 5. Tropospheric Correction Generation Algorithm 123 5.1 Former Research of Tropospheric Correction 123 5.1.1 Tropospheric Corrections for SBAS 124 5.1.2 Tropospheric Corrections of Network RTK 126 5.1.3 Tropospheric Corrections of PPP-RTK 130 5.2 Tropospheric Correction Generation Algorithm 136 5.2.1 ZWD Estimation Using Carrier-Phase Observations 138 5.2.2 ZWD Measurements Using Weather Data 142 5.2.3 Correction Generation Using Spherical Harmonics 149 5.2.4 Correction Applying Method for User 157 5.3 Correction Performance Analysis Results 159 5.3.1 Feasibility Test Environments 159 5.3.2 Zenith Correction Domain Analysis 161 5.3.3 Message Data Bandwidth Analysis 168 CHAPTER 6. Compact Wide-Area RTK User Test Results 169 6.1 Compact Wide-Area RTK User Process 169 6.2 User Performance Test Results 173 6.2.1 Feasibility Test Environments 173 6.2.2 User Range Domain Analysis 176 6.2.3 User Ambiguity Domain Analysis 182 6.2.4 User Position Domain Analysis 184 CHAPTER 7. Conclusions 189 Bibliography 193 초 록 207Docto

Modeling and Theoretical Analysis of GNSS-R Soil Moisture Retrieval Based on the Random Forest and Support Vector Machine Learning Approach

Global Navigation Satellite System-Reflectometry (GNSS-R) as a microwave remote sensing technique can retrieve the Earth’s surface parameters using the GNSS reflected signal from the surface. These reflected signals convey the surface features and therefore can be utilized to detect certain physical properties of the reflecting surface such as soil moisture content (SMC). Up to now, a serial of electromagnetic models (e.g., bistatic radar and Fresnel equations, etc.) are employed and solved for SMC retrieval. However, due to the uncertainty of the physical characteristics of the sites, complexity, and nonlinearity of the inversion process, etc., it is still challenging to accurately retrieve the soil moisture. The popular machine learning (ML) methods are flexible and able to handle nonlinear problems. It can dig out and model the complex interactions between input and output and ultimately make good predictions. In this paper, two typical ML methods, specifically, random forest (RF) and support vector machine (SVM), are employed for SMC retrieval from GNSS-R data of self-designed experiments (in situ and airborne). A comprehensive simulated dataset involving different types of soil is constructed firstly to represent the complex interactions between the variables (reflectivity, elevation angle, dielectric constant, and SMC) for the requirement of training ML regression models. Correspondingly, the main task of soil moisture retrieval (regression) is addressed. Specifically, the post-processed data (reflectivity and elevation angle) from sensor acquisitions are used to make predictions by these two adopted ML methods and compared with the commonly used GNSS-R retrieval method (electromagnetic models). The results show that the RF outperforms the SVM method, and it is more suitable for handling the inversion problem. Moreover, the RF regression model built by the comprehensive dataset demonstrates satisfactory accuracy and strong universality, especially when the soil type is not uniform or unknown. Furthermore, the typical task of detecting water/soil (classification) is discussed. The ML algorithms demonstrate a high potential and efficiency in SMC retrieval from GNSS-R data