Ionospheric Disturbance Analysis And Delay Correction Algorithms For Landslide And Earthquake Monitoring

Landslides in large open-pit mines and earthquakes are two kinds of typical solid Earth hazards in China. Prior works suggested that ionosphere, as one of important components of solar-terrestrial system, is greatly sensitive to variations of solar-terrestrial environment. It also have considerable effects on electromagnetic waves through it, and have serious influences on various satellite systems in it. Therefore, it is significant to conduct ionosphere research for space monitoring of solid Earth hazards, not only to guarantee the reliability of interferometric synthetic aperture radar (InSAR) to realize high precision monitoring of landslides in large open-pit mines, but also to provide early warning of strong earthquakes happened in solar-terrestrial environment based on ionospheric parameters. With the rapid development of global navigation satellite system (GNSS) and the continual increasement of continuously operating reference stations around the world, GNSS provide a novel means for ionosphere study, which has become one of most efficient and reliable methods for ionospheric sounding. In view of this, this dissertation focuses on several key issues among the ionospheric delay correction of InSAR and its application to landslide monitoring, and the analyzing and diagnosing ionosphere anomaly disturbances before strong earthquakes based on GNSS. The main works and results can be summarized as follows:1. In order to inverse the ionospheric vertical total electron content (VTEC) with high-precision in the region with less GNSS stations for space monitoring of solid Earth hazards, a novel strategy was established to estimate the precise VTEC of ionosphere. Firstly, the detailed characteristics of the negative contributions to the estimation of ionospheric VTEC were discussed, especially the integer ambiguities of GNSS carrier phase, the thermal noise of P code, the multipath offset and the instrumental biases inherent in the receivers and the transmitters of GNSS satellites, and then some reasonable methods were proposed to decrease or eliminate the effects from the negative contributions, including eliminating the integer ambiguities by smoothing pseudorange, decreasing the thermal noise by averaging noise in a continuously observed arc, calculating the total instrumental biases from the receiver and the transmitter using the observation data during midnight to dawn and solving the multipath offset as an unknown parameter. After that, the observation matrix was obtained in consideration of all the above contributions, and the least square method was used to solve the equations finally.2. To overcome the drawback from irregular solar electromagnetic radiation for ionospheric variation analysis, a nonlinear background removal method based on multiresolution wavelet transform (MWT) applicable to ionospheric VTEC data was proposed. Solar activity, as one of most important external impact factors for ionosphere, provide the ionization sources directly to form the ionosphere. However, the nonlinear solar radiation background increases difficulties in ionospheric variation analysis. It is difficult or even impossible to obtain correct ionospheric variations with a strong background in periods of high solar activity. Therefore, a novel method was proposed to detect and reveal the ionospheric anomaly variations, the results showed that the MWT-based method could handle the solar radiation background in the ionospheric TEC, the correlation coefficients between the extracted background and the observed solar indices reached up to 0.9 during the same observation period.3. In order to distinguish the sources of ionospheric anomaly variations, a novel algorithm was proposed to detect and diagnose ionospheric variations related to probable driving sources. In addition to the main influence on ionosphere from solar activity, geomagnetic activity can also change ionospheric TEC significantly. Geomagnetic activity variations not only cause globally changes, but also cause well-pronounced local perturbations of the ionospheric parameters. Therefore, the cross-wavelet analysis was used to diagnose ionospheric anomalies by gaining further insights into the dynamic relationship between the anomaly variability of ionospheric TEC and geomagnetic indices for the same set of observations. The results showed that the presented methodology for analyzing the time-frequency characteristics of ionospheric anomalies is capable of detecting and diagnosing the ionospheric variations possibly associated with earthquakes, especially for small and medium geomagnetic storms in unquiet solar-terrestrial environments.4. Thoroughly analyzing different influences on different bands of SAR from ionosphere, and studying the influence principles of ionosphere for differential interferometric synthetic aperture radar (D-InSAR) and multiple-aperture InSAR (MAI), and then an integrated approach by combining GNSS-TEC and NeQuick-2 model to correct ionospheric phase distortion of L-band SAR images was proposed. On this basis, following the idea of the small baseline subset (SBAS) approach, extending the traditional one-dimensional (1-D) deformation time-series monitoring along the line-of-sight (LOS) direction to the deformation field monitoring by combining the LOS-SBAS and AZI-SBAS methods with correcting ionospheric effects. Take the typical north-south direction landslide:Fushun west open-pit mine landslides as an example, we conducted the data processing and analysis with the above method, the results demonstrated that the proposed procedure was effective to monitor large-scale horizontal deformation and vertical deformation of landslides, especially for the north-south direction landslides.5. Based on the above ionospheric analysis algorithms, the ionospheric variations before the M9.0 Tohoku earthquake, the M8.0 Wenchuan earthquake and the M7.0 Lushan earthquake were studied comprehensively. The results showed that significant ionospheric disturbances above the forthcoming epicenter occurred on 8 March 2011, 3 days prior to the Tohoku earthquake, and on 9 May 2008,3 days prior to the Wenchuan earthquake. However, we did not observe any ionospheric anomaly over the epicenter in one month period before the Lushan earthquake, which happened five years later of the Wenchuan earthquake. On the basis of comparing and analyzing the characteristics of the ionospheric disturbances from the three earthquakes, we explored the possible interpretations on the different seismo-ionospheric effects based on the coupling theory of lithosphere-coversphere-atmosphere-ionosphere (LCAI).