gnatss.parsed package#
- gnatss.parsed.get_parsed_ant_positions(raw_df: DataFrame, gps_df: DataFrame | None = None) DataFrame#
Calculates the approximate antenna positions at ping transmit and reply using a less robust method than the standard Kalman Filter in order to accommodate sparsely sampled data.
This routine is meant to process 2-minute parsed QC data telemetered to shore in real time and operates in two possible modes. If processed GNSS antenna positions are provided this routine will use them. Otherwise it defaults to the positions logged by the INS.
If no processed GNSS antenna positions are provided, we will also insert dummy values for position uncertainty.
- Parameters:
- raw_dfpd.DataFrame
Pandas Dataframe containing parsed data at ping transmit/reply
- gps_dfpd.DataFrame
Pandas Dataframe containing GPS solutions Novatel Level-1 data
- Returns:
- pos_twttpd.DataFrame
Pandas Dataframe containing the resulting antenna positions, covariance, and standard deviation
- gnatss.parsed.get_parsed_rph(raw_df: DataFrame) DataFrame#
Reformats the INS RPH data from 2-minute parsed QC data. These data have only rough estimates of RPH at ping transmit and reply, so we cannot interpolate them. There is also no covariance data, so we insert dummy values to approximate “normal” uncertainties.
- Parameters:
- raw_dfDataFrame
Pandas Dataframe containing parsed data at ping transmit/reply
- Returns:
- cov_rph_twttpd.DataFrame
RPH data approximated at ping transmit/reply