StarID.id_stars

giant.stellar_opnav.star_identification:

StarID.id_stars(epoch=datetime.datetime(2000, 1, 1, 0, 0), compute_weights=False, temperature=0, image_number=0, lost_in_space=False)[source]

This method attempts to match the image points of interest with catalogue stars.

The id_stars() method is the primary interface of the StarID class. It performs all the tasks of querying the star catalogue, performing the initial pairing using a nearest neighbor search, refining the initial pairings with the second_closest_check and unique_check, and passing the refined pairings to the RANSAC routines. The matched and unmatched catalogue stars and image points of interest are stored in the appropriate attributes.

This method also returns a boolean index in the image points of interest vector, which extracts the image points that met the initial match criterion, and another boolean index into the image points of interest which extracts the image points of interest that were matched by the RANSAC algorithms. This can be used to select the appropriate meta data about catalogue stars or stars found in an image that isn’t explicitly considered by this class (as is done in the StellarOpNav class), but if you do not have extra information you need to keep in sync, then you can ignore the output.

If requested, the formal uncertainties for the catalogue unit vectors and pixel locations are computed and stored in the queried_weights_inertial and queried_weights_picture. These are computed by transforming the formal uncertainty on the right ascension, declination, and proper motion specified in the star catalogue into the proper frame.

Parameters:

  • epoch (datetime | Real) – The new epoch to move the stars to using proper motion

  • compute_weights (bool) – a flag specifying whether to compute weights for the attitude estimation and calibration estimation.

  • temperature (Real) – The temperature of the camera at the time of the image being processed

  • image_number (int) – The number of the image being processed

  • lost_in_space (bool) – A flag specifying whether the lost in space algorithm needs to be used

Returns:

The boolean index into the image points that met the original pairing criterion, and a second boolean index into the the result from the previous boolean index that extracts the image points that were successfully matched in the RANSAC algorithms

Return type:

Tuple[ndarray | None, ndarray | None]