midgard.gnss

midgard.gnss.solution_validation

Perform Chi-square test for residuals

Description:

Perform Chi-square test for residuals. Degrees of freedom (df) refers to the number of values that are free to vary df = number of valid satellites (nv) - number of parameters to be estimated (nx) - 1. GNSS solution validation based on the argument alpha, the level of significance (e.g. 99%), and defines the rejection level of the crossing events. Note that this is different from the false alarm rate, which instead refers to error type I

MAX_GDOPS (float)

MAX_GDOPS = 30.0

MIN_EL_MASK (float)

MIN_EL_MASK = 10.0

SOL_MIN_VALID_SATS (float)

SOL_MIN_VALID_SATS = 4.0

comp_quality_indicators()

Full name: midgard.gnss.solution_validation.comp_quality_indicators

Signature: (sol_vc_mat:<built-in function array>, logger:Callable=functools.partial(<function log at 0x7f15061d2ea0>, level='info')) -> Tuple[float, float, float]

Compute quality indicators

This function computes

  1. compute the distance root mean squared (DRMS)
  2. compute the circular error probable (CEP)
  3. compute the standard error ellipse (SEE)

Args:

Returns:

Tuple with quality indicators: (DRMS, CEP, SEE)

compute_DOPS()

Full name: midgard.gnss.solution_validation.compute_DOPS

Signature: (az:<built-in function array>, el:<built-in function array>, logger:Callable=functools.partial(<function log at 0x7f15061d2ea0>, level='info')) -> Tuple[float, float, float, float]

Compute DOP (dilution of precision)

In case of error, dop[0]-dop[3] are set to 0 and a warning is raised.

Args:

Returns:

Tuple with DOP values: (GDOP, PDOP, HDOP, VDOP).

sol_validation()

Full name: midgard.gnss.solution_validation.sol_validation

Signature: (residuals, alpha_siglev, n_params, az, el, logger=functools.partial(<function log at 0x7f15061d2ea0>, level='info')) -> bool

Validate a GNSS solution

Validating the GNSS solution is carried out by performing the following tasks:

  1. Chi-square test as outlier detection and rejections
  2. compute DOPS values
  3. compute the standard error ellipse
  4. compute the distance root mean squred (DRMS) <- TODO
  5. compute the circular error probable (CEP) <- TODO
  6. implementation of internal reliability
  7. implementation of external reliability

Args:

Returns:

True if solution is validated, False otherwise.