Model simplification strategies for testing

When developing complex models/algorithms, it is usually difficult to evaluate full model test results. The only option to verify complex model output is to compare it with some other implementation, for example Matlab toolboxes.

In addition to using 3rd parties for comparison, you should add functionality that lets you to simplify the model to a form whose results can be easily interpreted by a technical person. For example, if you are working on an algorithm that converts Geodetic coordinates to ECEF, you could have a function that temporarily sets the ellipsoid to a sphere (by making the eccentricity zero). It is easy to calculate expected results for a perfect sphere.

Similarly, if you develop a kinetic 6DoF flight simulation, you should have functions or flags that let you easily turn off complicating factors like aerodynamics (by multiplying coefficients with zero), wind, variable gravity, Coriolis, ellipsoidal Earth and terrain elevation. Your aim is to simplify your model to a ballistic flight in vacuum with constant gravity over a flat and non-rotating Earth. You can then use high school physics to calculate expected trajectories and compare them with your model outputs.

To clear doubts about your code, you should be able to quickly show that it obeys basic geometrical/physical laws.