Inside GNSS Media & Research

MAR-APR 2018

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Page 50 of 67 M A R C H / A P R I L 2 0 1 8 Inside GNSS 51 see the open-source code. But as a summary: pseudorange = (t Rx - t Tx )*c, t Tx = ReceivedSvTimeNanos [ns], t Rx = (TimeNanos + TimeOffsetNanos) - (FullBiasNanos+BiasNanos) - weekNumberNs [ns], where weekNumberNs =604800e9 *floor(-FullBiasNanos/604800e9) This summary is correct for GPS when time of week is known (State = STATE_TOW_DECODED or STATE_TOW_KNOWN). For other constellations and/or other states you must take care of details such as modulo milliseconds, and system time offsets. is is beyond the scope of this article, but these details are handled by the analysis tools and the resulting pseudorang- es are available in the derived data. The Desktop Analysis Tools compute smoothed pseudoranges as follows. For intervals where the hard- wa re clock is cont i nuous, t he smoothed pseudorange for a par- ticular satellite signal is the least squares solution x to the matrix equation: Wy = WAx where y = [column vector of raw pseudoranges column vector of prr], prr is the measured pseudorange-rate or, if available, the change in carrier phase divided by Δt, Δt is the time interval between measurements W is a diagonal matrix, with W ii = 1/σ(y i ) at is, the smoothed pseudorange is the minimum vari- ance linear estimator of the true pseudorange, given the mea- surements and variances of pseudorange (pr) and pseudorange- GnssClock TimeNanos GNSS Receiver hardware clock value TimeUncertaintyNanos Uncertainty of above value FullBiasNanos Difference between receiver clock and true GPS time since 0000Z, January 6, 1980. BiasNanos Sub-nanosecond part of above number DriftNanosPerSecond Receiver clock's drift DriftUncertaintyNanosPerSecond Uncertainty of above value HardwareClockDiscontinuityCount Count of hardware clock discontinuities GnssMeasurement Svid Satellite ID ConstellationType BeiDou, Galileo, GLONASS, GPS, QZSS, SBAS TimeOffsetNanos Time offset if measurements are asynchronous State Sync state (Code lock, bit sync, frame sync, etc.) ReceivedSvTimeNanos Received satellite time, at the measurement time ReceivedSvTimeUncertaintyNanos Error estimate of above value Cn0DbHz Carrier-to-noise density ratio PseudorangeRateMetersPerSecond Pseudorange rate (-Doppler) PseudorangeRateUncertaintyMetersPerSecond Error estimate of above value AccumulatedDeltaRangeMeters Accumulated delta range (carrier phase) AccumulatedDeltaRangeUncertaintyMeters Error estimate of above value AccumulatedDeltaRangeState Valid, Cycle slip or Loss-of-lock/Reset CarrierFrequencyHz Carrier frequency of the tracked signal AgcDb Automatic Gain Control level Table 1 describing raw measurements: Key raw measurement values, with variable names used by GnssLogger APK (phone app). This table shows a subset of all the measurement types, for a complete list see the API described online (start at rate (prr), and zero-mean uncorrelated errors. In plain English, this is the best estimate we can get by post-processing all the available information. Derived Data Once you have processed a log file with the desktop tools, you can save all the derived data to a comma-separated text file. e derived data file includes: satellite azimuth and elevation, raw pseudorange, smoothed pseudorange, and the residual errors of the raw and smoothed pseudoranges (residual errors derived from the known reference positions). e derived data also con- tains the receiver clock bias and frequency error. From this file you can regenerate all the line plots and the skyplot produced by the Desktop Analysis Tools. e tools provide interactive controls, and custom param- eters. We'll introduce these now and then show three examples of how to use them for analysis. For greater control you can set custom parameters by including a text file: CustomParam.txt in the same directory as your log file. In this file you can declare the satellite(s) to be used for computing the clock errors ( Figure 2 ).

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