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kanhereashwinkanhereashwin
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Added Rinex 3 .o file parsing
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‎gnss_lib_py/__init__.py‎

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from gnss_lib_py.parsers.precise_ephemerides import *
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from gnss_lib_py.parsers.nmea import *
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from gnss_lib_py.parsers.smartloc import *
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from gnss_lib_py.parsers.rinex import *
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from gnss_lib_py.utils.coordinates import *
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from gnss_lib_py.utils.filters import *

‎gnss_lib_py/parsers/rinex.py‎

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"""Functions to process broadcast navigation and observations from Rinex.
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"""
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__authors__ = "Ashwin Kanhere"
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__date__ = "19 Jul 2023"
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import numpy as np
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import georinex as gr
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from gnss_lib_py.parsers.navdata import NavData
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import gnss_lib_py.utils.constants as consts
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from gnss_lib_py.utils.time_conversions import datetime_to_gps_millis
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class RinexObs3(NavData):
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"""Class handling Rinex 3 observation files [1]_.
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The Rinex Observation files (of the format .yyo) contain measured
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pseudoranges, carrier phase, doppler and signal-to-noise ratio
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measurements for multiple constellations and bands.
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This loader converts those file types into a NavData in which
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measurements from different bands are treated as separate measurement
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instances. Inherits from NavData().
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References
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----------
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.. [1] https://files.igs.org/pub/data/format/rinex305.pdf
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"""
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def __init__(self, input_path):
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"""Loading Rinex 3 observation files into a NavData based class.
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Should input path to RXM-RAWX.csv file.
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Parameters
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----------
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input_path : string or path-like
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Path to measurement csv file
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"""
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obs_file = gr.load(input_path).to_dataframe()
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obs_header = gr.rinexheader(input_path)
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obs_measure_types = obs_header['fields']
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rx_bands = []
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for rx_measures in obs_measure_types.values():
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for single_measure in rx_measures:
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band = single_measure[1]
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if band not in rx_bands:
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rx_bands.extend(band)
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obs_file.reset_index(inplace=True)
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# Convert time to gps_millis
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gps_millis = [datetime_to_gps_millis(df_row['time']) \
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for _, df_row in obs_file.iterrows()]
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obs_file['gps_millis'] = gps_millis
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obs_file = obs_file.drop(columns=['time'])
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obs_file = obs_file.rename(columns={"sv":"sv_id"})
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# Convert gnss_sv_id to gnss_id and sv_id (plus gnss_sv_id)
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obs_navdata_raw = NavData(pandas_df=obs_file)
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obs_navdata_raw['gnss_sv_id'] = obs_navdata_raw['sv_id']
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gnss_chars = [sv_id[0] for sv_id in np.atleast_1d(obs_navdata_raw['sv_id'])]
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gnss_nums = [sv_id[1:] for sv_id in np.atleast_1d(obs_navdata_raw['sv_id'])]
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gnss_id = [consts.CONSTELLATION_CHARS[gnss_char] for gnss_char in gnss_chars]
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obs_navdata_raw['gnss_id'] = np.asarray(gnss_id)
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obs_navdata_raw['sv_id'] = np.asarray(gnss_nums, dtype=int)
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# Convert the coded column names to glp standards and extract information
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# into glp row and columns format
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info_rows = ['gps_millis', 'gnss_sv_id', 'sv_id', 'gnss_id']
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super().__init__()
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for band in rx_bands:
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rename_map = {}
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keep_rows = info_rows.copy()
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measure_type_dict = self._measure_type_dict()
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for measure_char, measure_row in measure_type_dict.items():
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measure_band_row = \
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obs_navdata_raw.find_wildcard_indexes(f'{measure_char}{band}*',
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max_allow=1)
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measure_row_chars = measure_band_row[f'{measure_char}{band}*'][0]
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rename_map[measure_row_chars] = measure_row
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keep_rows.append(measure_row_chars)
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band_navdata = obs_navdata_raw.copy(rows=keep_rows)
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band_navdata.rename(rename_map, inplace=True)
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# Remove the cases with NaNs in the measurements
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for row in rename_map.values():
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band_navdata = band_navdata.where(row, np.nan, 'neq')
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# Assign the gnss_lib_py standard names for signal_type
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rx_constellations = np.unique(band_navdata['gnss_id'])
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signal_type_dict = self._signal_type_dict()
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signal_types = np.empty(len(band_navdata), dtype=object)
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for constellation in rx_constellations:
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signal_type = signal_type_dict[constellation][band]
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signal_types[band_navdata['gnss_id']==constellation] = signal_type
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band_navdata['signal_type'] = signal_types
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if len(self) == 0:
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self.concat(band_navdata, inplace=True)
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else:
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self.concat(band_navdata, inplace=True)
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self.sort('gps_millis', inplace=True)
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@staticmethod
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def _measure_type_dict():
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"""Map of Rinex observation measurement types to standard names.
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Returns
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-------
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measure_type_dict : Dict
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Dictionary of the form {rinex_character : measure_name}
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"""
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measure_type_dict = {'C': 'raw_pr_m',
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'L': 'carrier_phase',
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'D': 'raw_doppler_hz',
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'S': 'cn0_dbhz'}
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return measure_type_dict
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@staticmethod
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def _signal_type_dict():
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"""Dictionary from constellation and signal bands to signal types.
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Returns
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-------
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signal_type_dict : Dict
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Dictionary of the form {constellation_band : {band : signal_type}}
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"""
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signal_type_dict = {}
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signal_type_dict['gps'] = {'1' : 'l1',
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'2' : 'l2',
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'5' : 'l5'}
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signal_type_dict['glonass'] = {'1' : 'g1',
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'4' : 'g1a',
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'2' : 'g2',
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'6' : 'g2a',
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'3' : 'g3'}
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signal_type_dict['galileo'] = {'1' : 'e1',
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'5' : 'e5a',
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'7' : 'e5b',
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'8' : 'e5',
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'6' : 'e6'}
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signal_type_dict['sbas'] = {'1' : 'l1',
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'5' : 'l5'}
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signal_type_dict['qzss'] = {'1' : 'l1',
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'2' : 'l2',
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'5' : 'l5',
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'6' : 'l6'}
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# beidou needs to be refined because the current level of detail isn't enough
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# to distinguish between different signals
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signal_type_dict['beidou'] = {'2' : 'b1',
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'1' : 'b1c',
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'5' : 'b2a',
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'7' : 'b2b',
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'8' : 'b2',
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'6' : 'b3'}
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signal_type_dict['irnss'] = {'5' : 'l5',
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'9' : 's'}
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return signal_type_dict

‎notebooks/tutorials/parsers.ipynb‎

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"print('Loaded NMEA data with raw data and ECEF coordinates\\n', nmea_navdata)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "fe8e8d6a",
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"metadata": {},
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"source": [
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"## Rinex v3 Observation File Parsing"
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]
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},
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{
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"cell_type": "markdown",
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"id": "af135db1",
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"metadata": {},
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"source": [
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"Rinex is another file standard that is used in the GNSS community to store and transmit navigation information.\n",
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"Files with the extension `.yyo`, where `yy` is the year in which the measurement was made, are used to store and transmit\n",
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"measurements.\n",
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"These measurements files can any constellation and each measurement usually contains the pseudorange, carrier phase (or difference from carrier frequency),\n",
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"doppler, and signal-to-noise ration measurements.\n",
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"In the following lines, we show how to load a ``.o`` file into a NavData instance."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "9f279032",
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"metadata": {},
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"outputs": [],
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"source": [
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"# download Rinex obs file and load it into NavData instance\n",
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"!wget https://raw.githubusercontent.com/Stanford-NavLab/gnss_lib_py/main/data/unit_test/rinex/obs/rinex_obs_mixed_types.20o --quiet -O \"rinex_obs_mixed_types.20o\"\n",
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"rinex_obs_3 = glp.RinexObs3(\"rinex_obs_mixed_types.20o\")\n",
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"print('Loaded Rinex Obs 3 data for the first time instant\\n', \\\n",
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" rinex_obs_3.where('gps_millis', rinex_obs_3['gps_millis', 0], 'eq'))"
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]
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},
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{
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"cell_type": "markdown",
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"id": "cf51b89e",

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