Benchmarking Automated Rayleigh-Wave Arrival Angle Measurements for USArray Seismograms

Surface-wave arrival angles are an important secondary set of observables to constrain Earth’s 3D structure. These data have also been used to refine information on the alignments of horizontal seismometer components with the geographic coordinate system. In the past, particle motion has been inspected and analyzed on single three-component seismograms, one at a time. But the advent of large, dense seismic networks has made this approach tedious and impractical. Automated toolboxes are now routinely used for datasets in which station operators cannot determine the orientation of a seismometer upon deployment, such as conventional free-fall ocean bottom seismometers. In a previous paper, we demonstrated that our automated Python-based toolbox Doran–Laske-Orientation-Python compares favorably with traditional approaches to determine instrument orientations. But an open question has been whether the technique also provides individual high-quality measurements for an internally consistent dataset to be used for structural imaging. For this feasibility study, we compared long-period Rayleigh-wave arrival angles at frequencies between 10 and 25 mHz for 10 earthquakes during the first half of 2009 that were recorded at the USArray Transportable Array—a component of the EarthScope program. After vigorous data vetting, we obtained a high-quality dataset that compares favorably with an arrival angle database compiled using our traditional interactive screen approach, particularly at frequencies 20 mHz and above. On the other hand, the presence of strong Love waves may hamper the automated measurement process as currently implemented.

A Fused Variable by Night Light Images and MODIS Products for Improving Urban Built-Up Area Extraction

The boundary of urban built-up areas is the baseline data of a city. Rapid and accurate monitoring of urban built-up areas is the prerequisite for the boundary control and the layout of urban spaces. In recent years, the night light satellite sensors have been employed in urban built-up area extraction. However, the existing extraction methods have not fully considered the properties that directly reflect the urban built-up areas, like the land surface temperature. This research first converted multi-source data into a uniform projection, geographic coordinate system and resampling size. Then, a fused variable that integrated the Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS) night light images, the Moderate-resolution Imaging Spectroradiometer (MODIS) surface temperature product and the normalized difference vegetation index (NDVI) product was designed to extract the built-up areas. The fusion results showed that the values of the proposed index presented a sharper gradient within a smaller spatial range, compared with the only night light images. The extraction results were tested in both the area sizes and the spatial locations. The proposed index performed better in both accuracies (average error rate 1.10%) and visual perspective. We further discussed the regularity of the optimal thresholds in the final boundary determination. The optimal thresholds of the proposed index were more stable in different cases on the premise of higher accuracies.

UAV-based aeromagnetic gradient measurements and inversion

<p>Rotary wing UAV’s are used in aeromagnetic measurements for UXO detection. That way, contaminated areas can be mapped fast and with high resolution. Until today, only the total magnetic intensity (TMI) is evaluated, even when a three axis fluxgate magnetometer is flown. In this project, we use two three component fluxgate sensors, an inertial measurement unit (IMU) and a GPS antenna. The IMU allows for a projection of the magnetic data into the geographic coordinate system as well as the calculation of the sensor positions relative to the GPS antenna. With this system, it is possible for the first time to evaluate the component gradients between the magnetometers.</p><p>The sensors are attached to the UAV via a versatile, T-shaped boom hanging below the UAV with the sensors positioned in a horizontal distance of 50 cm. The total mass of the flight system is about 5 kg with an air time of 15 minutes.</p><p>For the inversion, we use a dipole model which calculates the magnetic data for all sensor positions. Because the sources of the magnetic anomalies are unknown as a general rule, there is no distinction between induced and remanent magnetisation. Instead, the three components of the magnetic moment are fitted alongside the positions of the anomaly sources. The number of dipoles to be fitted and their initial parameters are arbitrary. For the inversion, the TMI and component gradients between the sensors are considered.</p><p>In order to analyse the accuracy of the complete system, we conducted surveys over a test field of 100 x 20 m, separated into four sections with varying anomaly configurations. As anomaly sources, we used neodymium magnets which we characterised in laboratory measurements. For optimal coverage and to compare flight directions, the test field was surveyed both lengthways and crossways with a sensor height of 1.5 m above ground. Inversion results show that when component gradients are used, overlapping anomalies can be separated and parameterised. The mean errors of the derived anomaly positions are 5 cm, the total magnetic moment can be determined with an accuracy of 0.35 Am<sup>2</sup>, whereby the errors in direction (declination and inclination) are 4 ° and 2 °, respectively.</p>

Virtual Polar Region Method Based on the Earth’s Transverse Ellipsoid Model

Experimental verification is very important for the research of inertial navigation and integrated navigation technology, but most researchers do not have the opportunity to conduct experiments directly in the polar regions. In order to solve the problem of inertial navigation verification in high latitude areas, a virtual polar region method based on transverse ellipsoid model is proposed. The method converts the reference information, initial state, and inertial sensor data into polar regions based on the transverse geographic coordinate system and can ensure that the attitude, velocity, and altitude information relative to the local-level frame remain unchanged. Therefore, the actual test data in the middle and low latitudes can be reconstructed accurately in the polar region without singularities, trajectory deformation, and principle errors. Simulation and vehicle tests show that the proposed method can achieve the same verification effect as the actual polar experiment.

Behavior of Broadcast Ionospheric-Delay Models from GPS, Beidou, and Galileo Systems

The GNSS observations suffer from different types of errors that could affect the achieved positioning accuracy based on the receiver type used. Single-frequency receivers are widely used worldwide because of its low cost. The ionospheric delay considers the most challenging error for single-frequency GNSS observations. All satellite navigation systems, except GLONASS, are advising their users to correct for the ionospheric delay using a certain model. Those models’ coefficients are sent to users in the system’s navigation message. These models are different in their accuracy and behavior based on its foundation theory as well as the updating rate of their coefficients. The GPS uses Klobuchar model for mitigating the ionospheric delay. BeiDou system (BDS-2) adopts a slightly modified Klobuchar model that resembles GPS ICA (Ionospheric Correction Algorithm) with eight correction parameters but is formulated in a geographic coordinate system with different coefficients in origin and updating rate. Galileo system uses a different model (NeQuick model). This article investigates the behavior of the three models in correcting the ionospheric delay for three stations at different latitudes during 3 months of different states of ionospheric activity, comparing with International GNSS Service-Global Ionospheric Maps (IGS-GIMs). It is advised from this research’s outputs to use the GPS model for mitigating the ionospheric delay in low-latitude regions during the state of low-and medium-activity ionosphere. It is advised to use the BeiDou model for mitigating the ionospheric delay in mid-latitude regions during different states of ionospheric activity. It is advised to use the Galileo model for mitigating the ionospheric delay in high-latitude regions during different states of ionospheric activity. Also, the Galileo model is recommended for mitigating the ionospheric delay for low-latitude regions during the state of high-activity ionosphere.

Integrated navigation approaches of vehicle aided by the strapdown celestial angles

The integrated navigation method based on star sensor celestial angles (altitude angle and azimuth angle) is proposed to serve the need for rapidly responsive, reliable, and precise of a hypersonic vehicle under a sophisticated environment. An integrated navigation algorithm suitable for large azimuth misalignment is established under launching point inertial coordinate and local geographical coordinate system based on altitude angle and azimuth angles. Meanwhile, a Bayesian method for data dropouts aided by the strapdown celestial angles is presented for the rapid variability in the celestial star angle with active galaxies. A nonlinear Bayesian filter is applied to implement the simulation on account of the nonlinear feature of the state and measurement equations. The simulation results showed that the Bayesian method for integrated navigation data dropouts could be accomplished by altitude angle and azimuth angle aiding in both launching point inertial coordinate and local geographical coordinate systems, which converge to 1′ in 10 s. The method indicated that the integrated navigation significant errors derived from initial localization and initial attitude alignment could be modified by the strapdown inertial navigation system (SINS) supported by the star sensor’s celestial angle in the local geographic coordinate system in the early launch stage. For the seconds of the flight phase, the integrated navigation aided by celestial angles in the launching point inertial coordinate system was guaranteed for the feasibility and validity. During the flight, the feasibility and validity of integrated navigation were guaranteed aided by celestial angles in launching point inertial coordinate system.

Compensation Method for Diurnal Variation in Three-Component Magnetic Survey

Considering that diurnal variation interferes with three-component magnetic surveys, which inevitably affects survey accuracy, exploring an interference compensation method of high-precision is particularly desirable. In this paper, a compensation method for diurnal variation is proposed, the procedure of which involves calibrating the magnetometer error and the misalignment error between magnetometer and non-magnetic theodolite. Meanwhile, the theodolite is used to adjust the attitude of the magnetometer to unify the observed diurnal variation into the geographic coordinate system. Thereafter, the feasibility and validity of the proposed method were verified by field experiments. The experimental results show that the average error of each component between the observed value of the proposed method and that of Changchun Geomagnetic station is less than 1.2 nT, which indicates that the proposed method achieves high observation accuracy. The proposed method can make up for the deficiency that traditional methods cannot meet the requirements of high accuracy diurnal variation compensation. With this method, it is possible for us to set up temporary diurnal variation observation station in areas with complex topography and harsh environment to assist aeromagnetic three-component survey.

Indoor Positioning Integrating PDR/Geomagnetic Positioning Based on the Genetic-Particle Filter

This paper proposes a fusion indoor positioning method that integrates the pedestrian dead-reckoning (PDR) and geomagnetic positioning by using the genetic-particle filter (GPF) algorithm. In the PDR module, the Mahony complementary filter (MCF) algorithm is adopted to estimate the heading angles. To improve geomagnetic positioning accuracy and geomagnetic fingerprint specificity, the geomagnetic multi-features positioning algorithm is devised and five geomagnetic features are extracted as the single-point fingerprint by transforming the magnetic field data into the geographic coordinate system (GCS). Then, an optimization mechanism is designed by using gene mutation and the method of reconstructing a particle set to ameliorate the particle degradation problem in the GPF algorithm, which is used for fusion positioning. Several experiments are conducted to evaluate the performance of the proposed methods. The experiment results show that the average positioning error of the proposed method is 1.72 m and the root mean square error (RMSE) is 1.89 m. The positioning precision and stability are improved compared with the PDR method, geomagnetic positioning, and the fusion-positioning method based on the classic particle filter (PF).

CREATION OF A DIGITAL ELENATION MODEL BY THE METHOD OF RADAR INTERFEROMETRY

The article discusses the experience of applying the technique of constructing a digital elevation model (DEM) by the method of radar interferometry using Sentinel-1A / 1B data on the territory of the Amur region near the city of Svobodny in June 2019. The presented method, which consists of 9 main stages, is implemented in the PHOTOMOD Radar software package. The stages of processing include: loading the initial data and converting them into the internal format of the program; creating a project for processing and combining images of an interferometric pair (recalculating the raster of the auxiliary image into the geometry of the main image); construction pictures of interferogram and coherence and it is also possible to calculate pictures of phase and amplitude; filtering the interferogram and phase transformation (recalculation of the obtained values in meters); construction of a digital elevation model and its geocoding into a geographic coordinate system (WGS 84). After that, the results obtained are assessed and compared with the SRTM digital elevation model, namely, a visual comparison of two digital elevation models, their subtraction (SRTM – model obtained from Sentinel-1A / 1B data) and a comparison heights characteristic relief points. Also made conclusions and considered the possibilities of further projects