School of Geodesy and Geomatics

Since the Selective Availability was turned off, the velocity and acceleration can be determined accurately with a single GPS receiver using raw Doppler measurements. The carrier-phase-derived Doppler measurements are normally used to determine velocity and acceleration when there is no direct output of the raw Doppler observations in GPS receivers. Due to GPS receiver clock drifts, however, a GPS receiver clock jump occurs when the GPS receiver clock resets itself (typically with 1 ms increment/ decrement) to synchronize with the GPS time. The clock jump affects the corresponding relationship between measurements and their time tags, which results in non-equidistant measurement sampling in time or incorrect time tags. This in turn affects velocity and acceleration determined for a GPS receiver by the conventional method which needs equidistant carrier phases to construct the derived Doppler measurements. To overcome this problem, an improved method that takes into account, GPS receiver clock jumps are devised to generate non-equidistantderived Doppler observations based on non-equidistant carrier phases. Test results for static and kinematic receivers, which are obtained by using the conventional method without reconstructing the equidistant continuous carrier phases, show that receiver velocity and acceleration suffered significantly from clock jumps. An airborne kinematic experiment shows that the greatest impact on velocity and acceleration reaches up to 0.2 m/s, 0.1 m/s 2 for the horizontal component and 0.5 m/s, 0.25 m/s 2 for the vertical component. Therefore, it can be demonstrated that velocity and acceleration measurements by using a standalone GPS receiver can be immune to the influence of GPS receiver clock jumps with the proposed method.

[1] Nowadays more and more high-rate real-time GPS data become available that provide a great opportunity to contribute to earthquake early warning (EEW) system in terms of capturing regional surface displacements, as an independent information source, useful for promptly estimating the magnitude of large destructive earthquake. In our study, we demonstrate the performance of the real-time ambiguity-fixed precise point positioning (PPP) approach using 5 Hz GPS data collected during El Mayor-Cucapah earthquake (Mw 7.2, 4 April 2010). The PPP-based displacements show to agree with accelerometer-based displacement at centimeter level. The key for successfully obtaining high precision displacements is the efficient ambiguity resolution. PPP with ambiguity fixing can result in correct permanent co-seismic offsets and correct recovery of moment magnitude and fault slip inversion at levels comparable to post-processing.

Real-time precise GNSS satellite orbit and clock products are the prerequisite of real-time GNSS-based applications. To obtain real-time GNSS satellite orbit and clock, three approaches exist currently, namely, the prediction-estimation approach, the prediction-correction approach and the estimation approach. Different from the former two approaches, which are based on the predicted orbit, the last approach estimates orbit and clock in an integrated way, thus it is the most rigorous one. However, the simultaneously estimation of both orbit and clock parameters makes it very time-consuming. In this contribution, the extended Kalman filter with parallel computation proposed for real-time GPS satellite clock estimation (Gao, et al., 2017) is introduced to improve the computational efficiency. In the introduced method, the epoch observations are processed sequentially and the covariance update process is accelerated with the Open Multi-Processing. With observation data from about 70 globally distributed stations spanning days 001-003 of 2018, the real-time GPS orbit and clock are estimated for validation. The epoch average processing time of the introduced method achieves around 2.9 s on average with 16 CPU cores, while that of the traditional method without Open Multi-Processing is about 4.1 s. When compare the estimated orbit and clock to the IGS final products, the daily constellation-mean RMS of orbit achieve 2.7, 5.7, 4.9 cm for the radial, along-track

In this paper, the admittance function between seafloor undulations and vertical gravity gradient anomalies were derived. Based on this admittance function, bathymetry model of 1 minute resolution were predicted from vertical gravity gradient anomalies and ship soundings in the experimental area from northwest Pacific. The accuracy of the model is evaluated using ship soundings and existing models, including ETOPO1, GEBCO, DTU10 and V15.1 from SIO. The model’s STD is 69.481m, comparable with V15.1 which generally believed to have the highest accuracy.

Accuracy of ordinary sensor node localization in wireless sensor networks mainly depends on the signal parameter such as time-of-arrival and signal strength estimation errors and the accuracy of the anchor node locations. In this paper a lowcomplexity but efficient algorithm is derived to improve anchor location accuracy in the presence of both anchor-to-anchor distance and AOA estimates and GPS measurements. Also, a Lenvenberg-Marquardt (LM) optimization based algorithm is developed for accuracy improvement when anchor-to-anchor distance estimates and GPS measurements are provided. Further, we derive the Cramer-Rao lower bound (CRLB) to benchmark the anchor position accuracy. To our knowledge, improving anchor node location accuracy and deriving the CRLB in the presence of both GPS and anchor-to-anchor measurements in 3-D scenarios are not reported in the literature. Simulation results demonstrate that the proposed approaches can improve the anchor position accuracy substantially and that the accuracy of the two developed algorithms approaches the corresponding CRLB.

This appendix provides an analytical analysis of the hyperbolic navigation problem for the 2D case with three base stations. The problem may be defined either as a navigation problem (receiver in the mobile device) or as a tracking problem (transmitter in the mobile device). In either case, it is assumed that the receiver measures the pseudo-range to the three base stations and from these data the position of the mobile device is sought.

In this study the focus is on ocean surface altimetry using the signals transmitted from GNSS (Global Navigation Satellite System) satellites. A low-altitude airborne experiment was recently conducted off the coast of Sydney. Both a LiDAR experiment and a GNSS reflectometry (GNSS-R) experiment were carried out in the same aircraft, at the same time, in the presence of strong wind and rather high wave height. The sea surface characteristics, including the surface height, were derived from processing the LiDAR data. A two-loop iterative method is proposed to calculate sea surface height using the relative delay between the direct and the reflected GNSS signals. The preliminary results indicate that the results obtained from the GNSS-based surface altimetry deviate from the LiDAR-based results significantly. Identification of the error sources and mitigation of the errors are needed to achieve better surface height estimation performance using GNSS signals.

Global Navigation Satellite System reflectometry (GNSS-R) has recently drawn significant attention since it can be employed in a range of applications including sea state, ocean altimetry, soil moisture measurement, and disaster (e.g. flooding, bushfire, and earthquake) monitoring. Although research on GNSS-R in the past two decades has made advances, there are no (or few) real applications of the technique. This is mainly because GNSS-R is still not a mature technique, there are no satellite-borne missions, there are few systematic airborne experiments, and GNSS-R is not yet able to provide information with high enough resolution and reliability. The authors are investigating new approaches to improve the performance of the GNSSbased geophysical parameter estimation. This paper focuses on the sea surface roughness estimation through an analysis of the reflected signal power. In particular, the theoretical modelling of the sea wave and surface scattering is studied in detail. Solution-level and waveform-level combination techniques are proposed to improve the estimation accuracy through jointly processing the measurements of the reflected signals which are transmitted by multiple GNSS satellites. These combination methods also can be employed for other parameter estimation tasks. Airborne experiments were carried out by a UNSW-owned light aircraft over the sea off the coast of Sydney. The data were logged using the NordNav software receiver which has four front-ends so that the signals arriving at the LHCP (left hand circularly polarized) and RHCP (right hand circularly polarized) antennas could be recorded simultaneously. Both the delay waveforms and delay-Doppler waveforms were generated from the processing of the real data. Theoretical delay waveforms were also generated. The preliminary results confirm that the waveform-matching estimation method is not suited for scenarios where the flight height is below 500 m.