GPS World, March 2011

INNOVATION Signal Processing 017 Center of mass 3869 dB Hz B 10 20 30 40 50 010 009 008 007 006 005 004 003 002 001 0 C N 0 dB Hz Normalized bin count FIGURE 3 Data collection Gamla Stan Old Town Stockholm top route and street view bottom cumulative histogram between successive starts Once the data collection is complete the reference data set is processed with a current almanac and an assumed elevation angle mask typically 5 degrees to produce an individual histogram for each satellite in view along with a cumulative histogram for the entire set as shown in Figure 3 bottom The masking calculation is particularly important in properly classifying which non reported C N 0 values should be ignored because the satellite in question is below the elevation angle mask at that location and time and which should be counted as blocked signals In addition to proper accounting for satellite masking the raw source data should also be manually trimmed to ensure that all data points used to build the histogram are taken homogeneously from the environment in question Thus the to exclude the section of open sky conditions between the similarly between the exit from the test area and the end of Finally the resulting histogram is combined with a randomized timing model to create a simulator scenario which is used to re test the same RUTs shown in Figure 2 Reference Receiver Considerations The accuracy of the data collection described above is fundamentally limited by the performance of the reference receiver in several ways First the default output format for GNSS data in many receivers is that of the National Marine Electronics Association NMEA 0183 standard the histograms presented in this article were derived from NMEA data This is imperfect in that the NMEA standard non proprietary GSV sentence requires C N 0 values to be quantized to the nearest whole dB Hz which introduces small rounding errors to the bin heights in the histograms In this study this effect was addressed by applying a uniformly distributed 05 dB Hz dither to all values in the corresponding simulated scenario quired an alternative data format must be used instead Second many receivers produce data outputs at 1 Hz limiting the ability to model temporal variations in C N 0 to frequencies less than 05 Hz owing to simple Nyquist considerations While the raw data for this study was obtained at walking speeds 1 to 2 meters per second and thus unlikely 0 fading studies done at higher speeds such as test drives may require a reference receiver capable of producing C N 0 measurements at a higher rate A third limitation is the sensitivity of the reference receiver Ideally the reference device would be able to track all signals present during data gathering regardless of signal strength and would instantaneously reacquire any blocked signals as soon as they became visible again Such a receiver would fully explore the space of all available signals present nitely sensitive so a conventional commercial grade high sensitivity receiver was used in this context Thus the resulting histogram is at best a reasonable but imperfect approximation of the true signal environment troduced if the net effects of the reference receivers noise accounted for in preparing the histograms If an active an modeling these losses is that the entire histogram with the exception of the blocked column is shifted sideways by a constant offset The correction applied to the histogram to account for this This can be done by generating a simulator scenario from the histogram of interest as described below and recording and the reference receiver A corresponding histogram is then built from the reference receivers output as before GPS World March 2011 www gpsworld com 46