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本书系统地介绍了GPS和强震仪数据融合处理的基本原理和算法模型，主要包括松组合模型、紧组合模型、自适应组合模型、改进的松组合模型、改进的紧组合模型、组合处理中关键技术问题、基线漂移与地表倾斜的关系以及各传感器观测的特点分析等。对GPS测速增强解算和基于联网模式的强震仪基线漂移校正也进行了分析介绍。本书可供从事GPS灾害监测预警方面的科研、生产人员参考，也可作为高等学校大地测量与地球物理专业的教材使用
。This book introduced the basic principle and algorithm of the data process by integration of GPS and strong-motion records systemically.It mainly includes the loose integration model，tight integration model，adaptive integration model，improved loose integration model，improved tight integration model，key issues about the integration process，the relationship between baseline shift and ground tilting，the characteristic analysis of different sensors.The augmentation solution approach about the GPS velocity estimation and strong-motion's net-based baseline shift correction are also introduced and analyzed.The book can be utilized by these who are engaged in scientific research and/or production about GPS disaster monitoring and early warning，it also can be used as the textbook or reference book for the related specialties in geodesy and geophysics.
Chapter 1 Introduction 11
1.1 Scientific background 12
1.1.1 GPS solution approaches 12
1.1.2 Strong-motion data solution approaches 14
1.1.3 Integration of GPS and accelerometer observations 16
1.2 Aims and objectives 17
1.2.1 Augmentation approach 17
1.2.2 Integration approach 17
1.2.3 Adaptive approach 18
1.2.4 The key issues about integration 18
1.2.5 The relationship between baseline shift and ground tiling 18
1.3 Organization of the book 18
Chapter 2 Real-time monitoring the ground motion using GPS with real time corrections 21
2.1 Introduction 21
2.2 Methodology 22
2.2.1 The velocity determination model based on broadcast ephemeris 22
2.2.2 Extracting corrections from the reference station 23
2.2.3 The velocity determination model based on reference station correction 24
2.2.4 Retrieve the final true velocity and displacement 25
2.2.5 The data processing flow of the augmentation approach 25
2.3 Experiment analysis 26
2.3.1 Comparison of displacement and velocity between GPS and strong-motion sensor 27
2.3.2 Comparison of displacement and velocity results between different sample rate data 27
2.3.3 Comparison of GPS results between the single station method and augmentation method 28
2.3.4 Comparison of the observation residuals and initial trend drift correction 30
2.4 Conclusion 32
Chapter 3 Application of a net-based baseline correction scheme to strong-motion records of the 2011 Mw 9.0 Tohoku earthquake 33
3.1 Introduction 33
3.2 Methodology 36
3.2.1 Selection of reference records 36
3.2.2 Net-based correction on target records 38
3.2.3 Detection of outlier records 38
3.3 Application to strong-motion data for the 2011 Mw 9.0 Tohoku earthquake 39
3.3.1 Data 39
3.3.2 Selected reference records 40
3.3.3 Augmented target records 40
3.3.4 Outlier records 44
3.3.5 Improvements over the previous empirical approaches 45
3.4 Conclusion and discussion 50
Chapter 4 Cost-effective monitoring of ground motion related to earthquakes，landslides or volcanic activity by joint use of a singlefrequency GPS and a MEMS accelerometer 52
4.1 Introduction 52
4.2 Method 54
4.3 Outdoor experiments 55
4.4 Discussion and conclusions 60
Chapter 5 A new algorithm for tight integration of real-time GPS and strong-motion records，demonstrated on simulated，experimental and real seismic data 62
5.1 Introduction 62
5.2 Mathematical model 64
5.3 A new approach to combine GPS and seismic accelerometer data 67
5.4 Validation and analysis 68
5.4.1 Simulated dataset 68
5.4.2 Experimental Test 69
5.4.3 Application to a real earthquake：E1 Mayor-Cucapah Mw 7.2，2010 72
5.5 Summary and discussion 75
Chapter 6 Adaptive recognition and correction of baseline shifts from collocated GPS and accelerometer using two phases Kalman filter 77
6.1 Introduction 77
6.2 Methodology 79
6.2.1 The model for tight integration of GPS and strong-motion measurements 79
6.2.2 The adaptive recognition of baseline shifts in strong-motion records 80
6.2.3 The implementation process 84
6.3 Validation 85
6.3.1 Experimental test using a shaking table 85
6.3.2 Application to a real earthquake：2011 Mw 9.0 Tohoku earthquake 87
6.4 Conclusion 91
Chapter 7 An improved loose integration method of coseismic waves retrieving from collocated GPS and accelerometer 92
7.1 Introduction 92
7.2 Overview of the traditional loose integration method 93
7.3 The improved loose integration method 94
7.4 Validation and analysis 95
7.5 Conclusion 98
Chapter 8 An improved method for tight integration of GPS and strong-motion records：complementary advantages 100
8.1 Introduction 100
8.2 Methodology 102
8.2.1 Using GPS to estimate baseline shifts for the strong-motion sensor 102
8.2.2 Using acceleration to constrain GPS solution and ambiguityresolution 104
8.2.3 The implementation process of the method 104
8.3 Validations 105
8.3.1 Analysis of the baseline shift 106
8.3.2 Analysis of the displacement time series 107
8.3.3 Analysis of the zenith tropospheric delay 109
8.3.4 Analysis of the waveforms 109
8.4 Conclusions and discussions 111
Chapter 9 The study of key issues about integration of GNSS and strong-motion records for real-time earthquake monitoring 113
9.1 Introduction 113
9.2 Method and Data 115
9.3 Validation and analysis 115
9.3.1 Coordinate system 116
9.3.2 GNSS sampling rate 116
9.3.3 The constrain of the dynamic noises 117
9.3.4 GNSS data quality 118
9.3.5 Convergence speed 119
9.3.6 Ambiguity resolution 120
9.4 Conclusions and discussions 121
Chapter 10 The study of baseline shift error in strong-motion and ground tilting during co-seismic period based on GPS observations 122
10.1 Introduction 122
10.2 Extracting strong-motion baseline shift based on GPS observation 124
10.3 Extracting of ground tilting information based on GPS observation 125
10.4 Validation and analysis 126
10.4.1 Experiment introduction and data processing 126
10.4.2 Result analysis 127
10.4.3 A case study of the earthquake event:2011 Mw 9.0 Tohoku-Oki earthquake 129
10.5 Conclusion 133
Chapter 11 Comparison of high-rate GPS，strong-motion records and their joint use for earthquake monitoring：a case study of the 2011 Mw 9.0 Tohoku earthquake 135
11.1 Introduction 135
11.2 Datasets and processing approaches 136
11.2.1 Data description 136
11.2.2 Processing approaches 137
11.3 Results and analysis 138
11.3.1 Comparison of horizontal co-seismic movement 138
11.3.2 Comparison in time-frequency domain of the displacement time series 139
11.3.3 Comparison of velocity waveforms 140
11.3.4 Comparison of P wave detection 140
11.4 Conclusions and discussions 144
Chapter 12 Synthesis 145
12.1 Conclusions 145
12.1.1 GPS velocity estimation augmentation approach 145
12.1.2 Strong-motion Net-based augmentation approach 146
12.1.3 Loose integration of GPS and Strong-motion observations 146
12.1.4 Tight integration of GPS and Strong-motion observations 146
12.1.5 Adaptive integration of GPS and Strong-motion observations 147
12.1.6 Improved loose integration of GPS and Strong-motion observations 147
12.1.7 Improved tight integration of GPS and Strong-motion observations 148
12.1.8 Key issues of integration of GPS and Strong-motion observations 148
12.1.9 Relationship between baseline shifts and ground tilting 149
12.1.10 Comparison of different sensors for earthquake monitoring and early warning 149
12.2 Outlook 150
12.2.1 Study the earthquake early warning model 150
12.2.2 Study the integration of Multi-sensor and data quality control 150
12.2.3 Develop a new sensor and real-time application system 150
Acronyms and abbreviations 151
References 153
