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系統識別號 U0026-1910202015413400
論文名稱(中文) 利用超解析延遲都卜勒映射和反射BPSK/BOC訊號之海面風速遙測技術
論文名稱(英文) Remote Sensing of Ocean Surface Wind Speed Using Super-Resolution Delay-Doppler Maps and Reflected BPSK/BOC Signals
校院名稱 成功大學
系所名稱(中) 電機工程學系
系所名稱(英) Department of Electrical Engineering
學年度 109
學期 1
出版年 109
研究生(中文) 王澔宇
研究生(英文) Hao-Yu Wang
學號 N28044020
學位類別 博士
語文別 英文
論文頁數 105頁
口試委員 召集委員-卓大靖
口試委員-王和盛
口試委員-錢樺
口試委員-楊名
口試委員-李祖聖
口試委員-蔡聖鴻
口試委員-王振興
指導教授-莊智清
中文關鍵字 全球導航衛星系統反射法  延遲都卜勒映射  單影像超解析  超深超解析率  風速反演  獵風者衛星(TRITON)  二進制相位偏移  二進制偏置載波 
英文關鍵字 Global Navigation Satellite System Reflectometry (GNSS-R)  delay-Doppler map (DDM)  single image super-resolution (SISR)  very-deep super-resolution (VDSR)  wind speed retrieval  TRITON  BPSK  BOC 
學科別分類
中文摘要 在過去數年間,全球衛星導航系統反射法已然成為一個新式且可行的遙測技術用於監測地球表面的物理訊息。現存的太空全球衛星導航系統反射法任務(如: NASA主持的Cyclone GNSS)致力於改善對於颶風的軌跡預測以及結構分析。在未來,由台灣太空中心發展的獵風者衛星(TRITON)也將利用全球衛星導航系統反射法來提供海風的觀測數據。全球衛星導航系統反射法原理的基礎,即是透過接受及處理來自地球表面的全球衛星導航系統反射訊號後,從中提取有效的觀測量,並透過發展的地球物理模型函數來反演目標參數。由於這些反射訊號能量相當微弱,因此長時間的積分處理以恢復訊號強度是一個必要的程序。對於這些太空類別的任務,全球衛星導航系統反射法接收儀就涉及了計算複雜度/通訊成本與資料反演間的取捨問題。
一個全球導航衛星系統反射訊號接收儀會形成一組可反映表面特性的延遲都卜勒映射(DDM)觀測量。過去已有大量的文獻探討如何利用此觀測量來反演不同的地球物理參數以及反演演算法的開發。然而,對於延遲都卜勒映射觀測量解析度對資料反演的影響則相對缺乏。一個完整解析的延遲都卜勒映射觀測量可反映較完整的資訊,但同時也需要更多的計算資源以及對下鏈通道占用較多的頻寬。因此,現存的任務通常會使用壓縮的延遲都卜勒映射觀測量來反演參數,而完整解析的延遲都卜勒映射觀測量則會用於特定目的(如: 系統校正)。本論文開發了一種基於深度學習的超解析演算法,以低解析的延遲都卜勒映射觀測量來重建出高解析的延遲都卜勒映射觀測量。本文也將所提的方法用於Cyclone GNSS所發布的延遲都卜勒映射觀測量產品以驗證可行性。實驗結果顯示,使用低解析延遲都卜勒映射重建的超解析延遲都卜勒映射在風速反演的性能方面與使用原始解析度的延遲都卜勒映射有近乎相同的表現。透過統計分析,這個結果相當於在產生延遲都卜勒映射觀測量方面節省了94%的資料量,在資料傳輸方面節省了15%的數據量。實驗結果也顯示,在最差情況下,所提的方法在風速反演的性能方面僅損失了4%。這些發現對於未來的星載全球衛星導航系統反射法任務提供了一種可行的策略。
另一方面,隨著新全球導航衛星系統時代的到來,多頻多調變訊號可望強化定位性能以及遙測應用。眾所周知,有些導航系統的衛星會在單一個頻段上發送採用二進制相位偏移(BPSK)以及二進制偏置載波(BOC)調變技術的訊號。本論文利用接收到的反射訊號中包含不同調變的特性提出一種新的全球衛星導航系統反射法觀測量,又稱為複合延遲都卜勒映射。本文假設全球導航衛星系統反射訊號接收儀可在同一個頻段上同時接收到包含兩種調變的訊號,經過處理後來生成所提的觀測量。本文同時也探討了從所提的觀測量中提取測量值以及可行的風速反演演算法。所提的方法則仿照TRITON衛星的軌道特性進行模擬來進行驗證。
英文摘要 Over the past few years, Global Navigation Satellite System reflectometry (GNSS-R) has become a new and feasible remote sensing method for geophysical information monitoring on the Earth’s surface. For instance, the Cyclone GNSS (CYGNSS), hosted by NASA, is dedicated to improving the trajectory prediction and structural analysis for hurricanes. In the future, the TRITON satellite, constructed by the National Space Organization (NSPO), Taiwan, will also use the GNSS-R method to provide ocean wind observation data. The basic principle of this method is to receive and process reflected GNSS signals scattered from the Earth’s surface, extract valid observations from them, and retrieve the target parameters through the developed geophysical model function (GMF). Since the power of the reflected signal is very weak, it is necessary to restore the signal strength through a long integration process. For these space-borne missions, the GNSS-R receiver involves the trade-off between computation complexity/communication cost and data retrieval.
A GNSS-R system will produce a set of delay-Doppler map (DDM) measurements that reveal surface characteristics. Even though the technique to retrieve different geophysical parameters have been developed, there is relatively little research on the analysis of DDM resolution on data retrieval quality. A fully-resolved DDM reveals more information but consumes more resources in terms of onboard processing and downlinking. As a result, existing tasks typically use compression in the retrieval process, while the fully-resolved DDM is reserved for specific purposes, such as calibration. In this dissertation, a deep learning super-resolution algorithm is developed to reconstruct a high-resolution DDM, also known as a super-resolution DDM, based on a low-resolution DDM. The proposed method is applied to the DDM product disseminated by the CYGNSS to verify the feasibility of the proposed method. The experimental results show that using the super-resolution DDM leads to almost identical performance to that obtained using the fully-resolved DDM in terms of wind speed retrieval. The statistical analysis shows that the proposed method may save 94% of the DDM data generation volume and 15% of the data transmission volume, and the performance degradation in terms of wind speed retrieval is negligible. These findings provide a potential strategy for future spaceborne GNSS-R missions.
With the advent of the new GNSS era, multi-frequency multi-modulation signals are expected to enhance not only positioning performance but also remote sensing applications. It is known that for some constellations, navigation satellites broadcast signals employing both binary phase-shift keying (BPSK) modulation and binary offset carrier (BOC) modulation in the same frequency band. This dissertation proposes a new GNSS-R measurement, called a composite delay-Doppler map (cDDM), that utilizes the received reflected GNSS signals with different modulation techniques for the purpose of retrieving wind speed. It is assumed that the GNSS-R receiver can receive BPSK and BOC signals simultaneously in the same frequency band (e.g., GPS III L1 C/A and L1C or QZSS L1 C/A and L1C) and can process the signals to generate the proposed GNSS-R measurements. An exploration of the observable features extracted from the composite DDM and the wind speed retrieval algorithm is also provided. The simulation verifies the proposed method under a configuration that is specified for the orbital and instrument specification of the upcoming TRITON mission.
論文目次 摘要 I
Abstract III
致謝 V
Contents VI
List of Figures VIII
List of Tables XIV
List of Abbreviations XVI
Chapter 1. Introduction 1
1.1. Background 1
1.2. Motivation and Objectives 4
1.3. Contributions 7
1.4. Organization 7
Chapter 2. GNSS Reflectometry Measurement: Delay-Doppler Map 9
2.1. Generation of Delay-Doppler Map 9
2.1.1. Specular Point Calculation 9
2.1.2. Delay and Doppler Calculation 14
2.1.3. Delay and Doppler Spreading over the Surface 16
2.1.4. DDM Processing 19
2.2. Performance Analysis of CIC Filter for DDM Generation 23
2.3. Summary 33
Chapter 3. Retrieval of Ocean Surface Wind Speed Using Super-Resolution Delay Doppler Maps 35
3.1. DDM Data Description 35
3.2. ECMWF Data Description 41
3.3. Super-Resolution DDM Reconstruction Model 43
3.4. Wind Speed Retrieval Method 50
3.5. Summary of the Proposed Method 54
Chapter 4. Experimental Results and Performance Analysis 57
4.1. Quality of the Super-resolution DDM 57
4.2. Performance Evaluation of SR-DDM-derived Wind Speed 64
4.3. Summary 67
Chapter 5. Retrieval of Ocean Surface Wind Speed Using Reflected BPSK/BOC Signals 69
5.1. Orbital and Instrumental Specifications of TRITON Mission 69
5.2. The Ground Truth Data for the Simulation: The ECMWF Product 71
5.3. The Proposed GNSS-R Measurement: Composite Delay-Doppler Maps 72
5.4. Development of Wind Speed Geophysical Model Function Based on the Composite Delay-Doppler Map 77
5.5. Summary 84
Chapter 6. Simulation Results and Performance Analysis 87
Chapter 7. Discussion and Conclusion 91
References 99
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