openpilot_comma/selfdrive/locationd/laikad.py

#!/usr/bin/env python3
import time
from multiprocessing import Process, Queue
from typing import List, Optional

import numpy as np
from collections import defaultdict

from cereal import log, messaging
from laika import AstroDog
from laika.constants import SECS_IN_MIN
from laika.ephemeris import EphemerisType, convert_ublox_ephem
from laika.gps_time import GPSTime
from laika.helpers import ConstellationId
from laika.raw_gnss import GNSSMeasurement, calc_pos_fix, correct_measurements, process_measurements, read_raw_ublox
from selfdrive.locationd.models.constants import GENERATED_DIR, ObservationKind
from selfdrive.locationd.models.gnss_kf import GNSSKalman
from selfdrive.locationd.models.gnss_kf import States as GStates
import common.transformations.coordinates as coord
from selfdrive.swaglog import cloudlog

MAX_TIME_GAP = 10


class Laikad:

  def __init__(self, valid_const=("GPS", "GLONASS"), auto_update=False, valid_ephem_types=(EphemerisType.ULTRA_RAPID_ORBIT, EphemerisType.NAV)):
    self.astro_dog = AstroDog(valid_const=valid_const, auto_update=auto_update, valid_ephem_types=valid_ephem_types)
    self.gnss_kf = GNSSKalman(GENERATED_DIR)
    self.orbit_p: Optional[Process] = None
    self.orbit_q = Queue()

  def process_ublox_msg(self, ublox_msg, ublox_mono_time: int, block=False):
    if ublox_msg.which == 'measurementReport':
      report = ublox_msg.measurementReport
      if report.gpsWeek > 0:
        latest_msg_t = GPSTime(report.gpsWeek, report.rcvTow)
        self.fetch_orbits(latest_msg_t + SECS_IN_MIN, block)
      new_meas = read_raw_ublox(report)

      measurements = process_measurements(new_meas, self.astro_dog)
      pos_fix = calc_pos_fix(measurements, min_measurements=4)
      # To get a position fix a minimum of 5 measurements are needed.
      # Each report can contain less and some measurements can't be processed.
      corrected_measurements = []
      if len(pos_fix) > 0 and abs(np.array(pos_fix[1])).mean() < 1000:
        corrected_measurements = correct_measurements(measurements, pos_fix[0][:3], self.astro_dog)

      t = ublox_mono_time * 1e-9
      self.update_localizer(pos_fix, t, corrected_measurements)
      localizer_valid = self.localizer_valid(t)

      ecef_pos = self.gnss_kf.x[GStates.ECEF_POS].tolist()
      ecef_vel = self.gnss_kf.x[GStates.ECEF_VELOCITY].tolist()

      pos_std = self.gnss_kf.P[GStates.ECEF_POS].flatten().tolist()
      vel_std = self.gnss_kf.P[GStates.ECEF_VELOCITY].flatten().tolist()

      bearing_deg, bearing_std = get_bearing_from_gnss(ecef_pos, ecef_vel, vel_std)

      meas_msgs = [create_measurement_msg(m) for m in corrected_measurements]
      dat = messaging.new_message("gnssMeasurements")
      measurement_msg = log.LiveLocationKalman.Measurement.new_message
      dat.gnssMeasurements = {
        "positionECEF": measurement_msg(value=ecef_pos, std=pos_std, valid=localizer_valid),
        "velocityECEF": measurement_msg(value=ecef_vel, std=vel_std, valid=localizer_valid),
        "bearingDeg": measurement_msg(value=[bearing_deg], std=[bearing_std], valid=localizer_valid),
        "ubloxMonoTime": ublox_mono_time,
        "correctedMeasurements": meas_msgs
      }
      return dat
    elif ublox_msg.which == 'ephemeris':
      ephem = convert_ublox_ephem(ublox_msg.ephemeris)
      self.astro_dog.add_ephems([ephem], self.astro_dog.nav)
    # elif ublox_msg.which == 'ionoData':
    # todo add this. Needed to better correct messages offline. First fix ublox_msg.cc to sent them.

  def update_localizer(self, pos_fix, t: float, measurements: List[GNSSMeasurement]):
    # Check time and outputs are valid
    if not self.localizer_valid(t):
      # A position fix is needed when resetting the kalman filter.
      if len(pos_fix) == 0:
        return
      post_est = pos_fix[0][:3].tolist()
      filter_time = self.gnss_kf.filter.filter_time
      if filter_time is None:
        cloudlog.info("Init gnss kalman filter")
      elif abs(t - filter_time) > MAX_TIME_GAP:
        cloudlog.error("Time gap of over 10s detected, gnss kalman reset")
      else:
        cloudlog.error("Gnss kalman filter state is nan")
      self.init_gnss_localizer(post_est)
    if len(measurements) > 0:
      kf_add_observations(self.gnss_kf, t, measurements)
    else:
      # Ensure gnss filter is updated even with no new measurements
      self.gnss_kf.predict(t)

  def localizer_valid(self, t: float):
    filter_time = self.gnss_kf.filter.filter_time
    return filter_time is not None and (t - filter_time) < MAX_TIME_GAP and all(np.isfinite(self.gnss_kf.x[GStates.ECEF_POS]))

  def init_gnss_localizer(self, est_pos):
    x_initial, p_initial_diag = np.copy(GNSSKalman.x_initial), np.copy(np.diagonal(GNSSKalman.P_initial))
    x_initial[GStates.ECEF_POS] = est_pos
    p_initial_diag[GStates.ECEF_POS] = 1000 ** 2

    self.gnss_kf.init_state(x_initial, covs_diag=p_initial_diag)

  def get_orbit_data(self, t: GPSTime, queue):
    cloudlog.info(f"Start to download/parse orbits for time {t.as_datetime()}")
    start_time = time.monotonic()
    try:
      self.astro_dog.get_orbit_data(t, only_predictions=True)
    except RuntimeError as e:
      cloudlog.info(f"No orbit data found. {e}")
      return
    cloudlog.info(f"Done parsing orbits. Took {time.monotonic() - start_time:.2f}s")
    if queue is not None:
      queue.put((self.astro_dog.orbits, self.astro_dog.orbit_fetched_times))

  def fetch_orbits(self, t: GPSTime, block):
    if t not in self.astro_dog.orbit_fetched_times:
      if block:
        self.get_orbit_data(t, None)
        return
      if self.orbit_p is None:
        self.orbit_p = Process(target=self.get_orbit_data, args=(t, self.orbit_q))
        self.orbit_p.start()
      if not self.orbit_q.empty():
        ret = self.orbit_q.get()
        if ret:
          self.astro_dog.orbits, self.astro_dog.orbit_fetched_times = ret
          self.orbit_p.join()
          self.orbit_p = None

  def __del__(self):
    if self.orbit_p is not None:
      self.orbit_p.kill()


def create_measurement_msg(meas: GNSSMeasurement):
  c = log.GnssMeasurements.CorrectedMeasurement.new_message()
  c.constellationId = meas.constellation_id.value
  c.svId = meas.sv_id
  c.glonassFrequency = meas.glonass_freq if meas.constellation_id == ConstellationId.GLONASS else 0
  c.pseudorange = float(meas.observables_final['C1C'])
  c.pseudorangeStd = float(meas.observables_std['C1C'])
  c.pseudorangeRate = float(meas.observables_final['D1C'])
  c.pseudorangeRateStd = float(meas.observables_std['D1C'])
  c.satPos = meas.sat_pos_final.tolist()
  c.satVel = meas.sat_vel.tolist()
  return c


def kf_add_observations(gnss_kf: GNSSKalman, t: float, measurements: List[GNSSMeasurement]):
  ekf_data = defaultdict(list)
  for m in measurements:
    m_arr = m.as_array()
    if m.constellation_id == ConstellationId.GPS:
      ekf_data[ObservationKind.PSEUDORANGE_GPS].append(m_arr)
      ekf_data[ObservationKind.PSEUDORANGE_RATE_GPS].append(m_arr)
    elif m.constellation_id == ConstellationId.GLONASS:
      ekf_data[ObservationKind.PSEUDORANGE_GLONASS].append(m_arr)
      ekf_data[ObservationKind.PSEUDORANGE_RATE_GLONASS].append(m_arr)

  for kind, data in ekf_data.items():
    gnss_kf.predict_and_observe(t, kind, data)


def get_bearing_from_gnss(ecef_pos, ecef_vel, vel_std):
  # init orientation with direction of velocity
  converter = coord.LocalCoord.from_ecef(ecef_pos)

  ned_vel = np.einsum('ij,j ->i', converter.ned_from_ecef_matrix, ecef_vel)
  bearing = np.arctan2(ned_vel[1], ned_vel[0])
  bearing_std = np.arctan2(np.linalg.norm(vel_std), np.linalg.norm(ned_vel))
  return float(np.rad2deg(bearing)), float(bearing_std)


def main():
  sm = messaging.SubMaster(['ubloxGnss'])
  pm = messaging.PubMaster(['gnssMeasurements'])

  laikad = Laikad()
  while True:
    sm.update()

    if sm.updated['ubloxGnss']:
      ublox_msg = sm['ubloxGnss']
      msg = laikad.process_ublox_msg(ublox_msg, sm.logMonoTime['ubloxGnss'])
      if msg is not None:
        pm.send('gnssMeasurements', msg)


if __name__ == "__main__":
  main()