Multipath, the skewed positions due to signal deflections from surrounding objects, remains one of the limiting sources of error in position measurements determined by 1-Hertz Global Positioning System (GPS) data. There is currently no standard automated technique to remove multipath consequently... Show moreMultipath, the skewed positions due to signal deflections from surrounding objects, remains one of the limiting sources of error in position measurements determined by 1-Hertz Global Positioning System (GPS) data. There is currently no standard automated technique to remove multipath consequently affecting the accuracy of any geodetic or seismological application of GPS data. For GPS data to provide sub-centimeter position accuracy, multipath error must first be removed. Characterizing multipath entails identifying sources that contribute to relevant position errors for certain satellite-receiver pairs. In this study, signal-to-noise ratios (SNR) from 1-hz receivers were used to make this characterization possible. SNR recorded by the receivers are sensitive to changes in the time-varying GPS environments and are a conduit for revealing multipath. The analysis of SNR power spectra identified receiver-recording characteristics indicative of specular multipath. These included large amplitudes and high frequency or long period interference. With knowledge of the period of observed multipath, a forward model helped in predicting the distance from the theoretical horizontal reflector to the antenna. This was possible since the distance from a horizontal reflector to antenna determines, in part, the phase and frequency of multipath. Preliminary results have identified time frames and specific satellite-receiver pairs in which significant multipath occurs. This, coupled with actual photos of receiver environments, aids in predicting when, where, and why significant multipath will appear. Knowledge gained from multipath characterization can be applied toward the prevention or removal of multipath at other GPS sites with the Parkfield array as a representative model. Show less
