Chapter 1 Introduction
1.1 Scientific background
1.1.1 GPS solution approaches
1.1.2 Strong-motion data solution approaches
1.1.3 Integration of GPS and accelerometer observations
1.2 Aims and objectives
1.2.1 Augmentation approach
1.2.2 Integration approach
1.2.3 Adaptive approach
1.2.4 The key issues about integration
1.2.5 The relationship between baseline shift and ground tiling
1.3 Organization of the book
Chapter 2 Real-time monitoring the ground motion using GPS with real time corrections
2.1 Introduction
2.2 Methodology
2.2.1 The velocity determination model based on broadcast ephemeris
2.2.2 Extracting corrections from the reference station
2.2.3 The velocity determination model based on reference station correction
2.2.4 Retrieve the final true velocity and displacement
2.2.5 The data processing flow of the augmentation approach
2.3 Experiment analysis
2.3.1 Comparison of displacement and velocity between GPS and strong-motion sensor
2.3.2 Comparison of displacement and velocity results between different sample rate data
2.3.3 Comparison of GPS results between the single station method and augmentation method
2.3.4 Comparison of the observation residuals and initial trend drift correction
2.4 Conclusion
Chapter 3 Application of a net-based baseline correction scheme to
strong-motion records of the 2011 Mw 9.0 Tohoku
earthquake
3.1 Introduction
3.2 Methodology
3.2.1 Selection of reference records
3.2.2 Net-based correction on target records
3.2.3 Detection of outlier records
3.3 Application to strong-motion data for the 2011 Mw 9.0 Tohoku earthquake
3.3.1 Data
3.3.2 Selected reference records
3.3.3 Augmented target records
3.3.4 Outlier records
3.3.5 Improvements over the previous empirical approaches
3.4 Conclusion and discussion
Chapter 4 Cost-effective monitoring of ground motion related to
earthquakes, landslides or volcanic activity by joint use
of a single-frequency GPS and a MEMS accelerometer
4.1 Introduction
4.2 Method
4.3 Outdoor experiments
4.4 Discussion and conclusions
Chapter 5 A new algorithm for tight integration of real-time GPS
and strong-motion records, demonstrated on simulated,
experimental and real seismic data
5.1 Introduction
5.2 Mathematical model
5.3 A new approach to combine GPS and seismic accelerometer data
5.4 Validation and analysis
5.4.1 Simulated dataset
5.4.2 Experimental Test
5.4.3 Application to a real earthquake : E1 Mayor-Cucapah Mw 7.2, 2010
5.5 Summary and discussion
Chapter 6 Adaptive recognition and correction of baseline shifts from
collocated GPS and accelerometer using two phases Kalman
filter
6.1 Introduction
6.2 Methodology
6.2.1 The model for tight integration of GPS and strong-motion measurements
6.2.2 The adaptive recognition of baseline shifts in strong-motion records
6.2.3 The implementation process
6.3 Validation
6.3.1 Experimental test using a shaking table
6.3.2 Application to a real earthquake:2011 Mw 9.0 Tohoku earthquake
6.4 Conclusion
Chapter 7 An improved loose integration method of coseismie waves retrieving from collocated GPS and accelerometer
7.1 Introduction
7.2 Overview of the traditional loose integration method
7.3 The improved loose integration method
7.4 Validation and analysis
7.5 Conclusion
Chapter 8 An improved method for tight integration of GPS and strong-motion records: complementary advantages
8.1 Introduction
8.2 Methodology
8.2.1 Using GPS to estimate baseline shifts for the strong-motion sensor
8.2.2 Using acceleration to constrain GPS solution and ambiguity-resolution
8.2.3 The implementation process of the method
8.3 Validations
8.3.1 Analysis of the baseline shift
8.3.2 Analysis of the displacement time series
8.3.3 Analysis of the zenith tropospheric delay
8.3.4 Analysis of the waveforms
8.4 Conclusions and discussions
Chapter 9 The study of key issues about integration of GNSS and
strong-motion records for real-time earthquake
monitoring
9.1 Introduction
9.2 Method and Data
9.3 Validation and analysis
9.3.1 Coordinate system
9.3.2 GNSS sampling rate
9.3.3 The constrain of the dynamic noises
9.3.4 GNSS data quality
9.3.5 Convergence speed
9.3.6 Ambiguity resolution
9.4 Conclusions and discussions
Chapter 10 The study of baseline shift error in strong-motion and ground tilting during co-seismic period based on GPS observations
10.1 Introduction
10.2 Extracting strong-motion baseline shift based on GPS observation
10.3 Extracting of ground tilting information based on GPS observation
10.4 Validation and analysis
10.4.1 Experiment introduction and data processing
10.4.2 Result analysis
10.4.3 A case study of the earthquake event: 2011 Mw 9.0 Tohoku-Oki earthquake
10.5 Conclusion
Chapter 11 Comparison of high-rate GPS, strong-motion records and
their joint use for earthquake monitoring: a ease study of
the 2011 nw 9.0 Tohoku earthquake
11.1 Introduction
11.2 Datasets and processing approaches
11.2.1 Data description
11.2.2 Processing approaches
11.3 Results and analysis
11.3.1 Comparison of horizontal co-seismic movement
11.3.2 Comparison in time-frequency domain of the displacement time series
11.3.3 Comparison of velocity waveforms
11.3.4 Comparison of P wave detection
11.4 Conclusions and discussions
Chapter 12 Synthesis
12.1 Conclusions
12.1.1 GPS velocity estimation augmentation approach
12.1.2 Strong-motion net-based augmentation approach
12.1.3 Loose integration of GPS and strong-motion observations
12.1.4 Tight integration of GPS and strong-motion observations
12.1.5 Adaptive integration of GPS and strong-motion observations
12.1.6 Improved loose integration of GPS and strong-motion observations
12.1.7 Improved tight integration of GPS and strong-motion observations
12.1.8 Key issues of integration of GPS and strong-motion observations
12.1.9 Relationship between baseline shifts and ground tilting
12.1.10 Comparison of different sensors for earthquake monitoring and early warning
12.2 Outlook
12.2.1 Study the earthquake early warning model
12.2.2 Study the integration of multi-sensor and data quality control
12.2.3 Develop a new sensor and real-time application system
Acronyms and abbreviations
References
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