LECTURE 4 (CH16)
OBSERVATION EQUATIONS
Least Squares adjustment by observation equation method:
Written relating observed values to residual errors and unknown parameters
1 observation equation for each observation
Number of equations = number of unknowns
If redundant observations made, least squares method can be applied
Expression for each residual obtained from every observation equation
Residuals then squared and added to get a function:
Squared variance
Weighted squared variance:
From Example:
Compute most probable value for equally weighted distance observations:
Find mean value (most probable value of observed length)
Write following observation equations that define residual for any observed quantity at
difference between most probable value and any individual observations
,
From Example:
OBSERVATION EQUATIONS
Least Squares adjustment by observation equation method:
Written relating observed values to residual errors and unknown parameters
1 observation equation for each observation
Number of equations = number of unknowns
If redundant observations made, least squares method can be applied
Expression for each residual obtained from every observation equation
Residuals then squared and added to get a function:
Squared variance
Weighted squared variance:
From Example:
Compute most probable value for equally weighted distance observations:
Find mean value (most probable value of observed length)
Write following observation equations that define residual for any observed quantity at
difference between most probable value and any individual observations
,
From Example: