High‐rate (1‐Hz) Global Positioning System (GPS) data are beginning to be used for a variety of geophysical monitoring purposes, including seismology. Improving the precision of high‐rate GPS position estimates will increase the value of these 1‐Hz GPS monitoring systems. One technique that has been used to improve high‐rate GPS positioning takes advantage of the ground track repeat period of the satellites. This study investigates the GPS orbital repeat period and determines that it varies for each satellite and differs significantly from the generally assumed sidereal period. Orbit repeat periods are calculated and used to filter 1‐Hz GPS position estimates. Using the calculated orbit repeat period significantly reduces low frequency (0.001–0.04 Hz) errors in 1‐Hz GPS position estimates.

The use of GPS for navigation‐critical applications such as aircraft nonprecision approach or harbor and river crossings requires the navigation data to be both extremely accurate and extremely reliable. This paper describes a method for autonomous GPS satellite failure detection and isolation (D/I). The test statistic for the D/I algorithm is the range residual parameter for six or more satellites in view. Based on experiments conducted at Stanford, nominal carrier‐aided pseudorange measurement errors are modeled as Gaussian random variables with mean in the range from −5 m to + 5 m and standard deviation of 0.4 m. The theoretical statistical distribution of the range residual is given. Monte Carlo simulations present results of applying the algorithm to measurement sets containing a biased measurement. With a 100 m biased measurement present, successful detection is achieved 99.9 percent of the time, and successful D/I is achieved 72.2 percent of the time. The user is always aware when isolation is not possible. User positioning errors resulting from application of the algorithm are always the same or better than with the all‐in‐view solution.

Measurements of soil moisture are important for studies of climate and weather forecasting, flood prediction, and aquifer recharge studies. Although soil moisture measurement networks exist, most are sparsely distributed and lack standardized instrumentation. Measurements of soil moisture from satellites have extremely large spatial footprints (40-60 km). A methodology is described here that uses existing networks of continuously-operating GPS receivers to measure soil moisture fluctuations. In this technique, incoming signals are reflected off and attenuated by the ground before reception by the GPS receiver. These multipath reflections directly affect signal-to-noise ratio (SNR) data routinely collected by GPS receivers, creating amplitude variations that are a function of ground reflectivity and therefore soil moisture content. After describing this technique, multipath reflection amplitudes at a GPS site in Tashkent, Uzbekistan are compared to estimates of soil moisture from the Noah land surface model. Although the GPS multipath amplitudes and the land surface model are uncalibrated, over the 70-day period studied, they both rise sharply following each rainfall event and slowly decrease over a period of *10 days.

[1] In order to improve the accuracy of high-rate (1 Hz) displacements for geophysical applications such as seismology it is important to reduce systematic errors at seismic frequencies. One such GPS error source that overlaps with seismic frequencies and is not currently modeled is multipath. This study investigates the frequencies and repetition of multipath in high-rate GPS time series in order to maximize the effectiveness of techniques relying upon the geometric repeatability of GPS satellite orbits. The implementation of the aspect repeat time adjustment (ARTA) method described here uses GPS position time series to estimate time-varying and site-dependent shifts. As demonstrated for high-rate GPS sites in southern California this technique significantly reduces positioning noise at periods from 20 to 1000 s. For a 12-hour time series, ARTA methods improve the standard deviation of the north component from 8.2 to 5.1 mm and the east component from 6.3 to 4.0 mm. After applying ARTA corrections, common mode errors are removed by stacking. This method further improves the standard deviations to 3.0 and 2.6 mm for the north and east components, respectively.

[1] Multipath, wherein a signal arrives at the receiving antenna by more than one path, is a significant and largely unmodeled source of GPS positioning error. We present a technique for mitigating specular multipath in GPS carrier phase measurements using the signal-to-noise ratio (SNR), in which the frequency and amplitude content of non-stationary oscillations in SNR are modeled to extract multipath parameters (direct and reflected signal amplitudes, and the phase difference between direct and indirect signals). The frequency content of SNR data is estimated using wavelet analysis, then used to initialize an adaptive least squares process to solve for time-varying multipath parameters. Multipath corrections derived from these parameters are applied to the phase observables. We demonstrate this technique using campaign GPS data collected over a large salt flat (Salar de Uyuni), specifically a tripod-mounted station which experienced long-period (300-2000 s) multipath oscillations in SNR from ground reflections. By contrasting position solutions before and after applying multipath corrections, we demonstrate a reduction in carrier phase postfit residual RMS of up to 20% for static positioning, and 1-7 dB reduction in spectral power at multipath periods for kinematic positions.