uataq.gps#

GPS helpers: great-circle geometry and motion estimated from positions.

When a receiver logs only GPGGA sentences (position, altitude, fix quality) and not GPRMC, there is no recorded speed or course. Both can be recovered from the positions themselves, which is what estimate_speed_course() does; uataq.instruments.GPS calls it to fill whatever the files did not record.

Formulas from https://www.movable-type.co.uk/scripts/latlong.html. They assume a spherical Earth, which is well under GPS noise at these distances.

Validated against a day of recorded 1 Hz speed and course from the TRAX platform: correlation 0.995, median speed difference 0.00 m/s and median course error 0.4 degrees while moving. Position noise becomes speed noise, so widen estimate_window before thresholding a stationary platform.

Examples

The example reads the archive, so neither the docs build nor the tests run it (# doctest: +SKIP).

>>> import uataq
>>> data = uataq.read_data("trx01", "gps", time_range="2017-03")
>>> gps = data["gps"]
>>> # Speed_m_s is filled in the GPGGA-only years too
>>> moving = gps[gps.Speed_m_s > 1.0]

Attributes

EARTH_RADIUS_M

Mean Earth radius (m).

Functions

`bearing`	Return the initial great-circle bearing from the first point to the second.
`estimate_speed_course`	Estimate speed and course from a sequence of positions.
`gps_time_from_time_of_day`	Full GPS datetimes from a receiver's time of day and the logger's clock.
`haversine`	Great-circle distance between two points (haversine formula).