We ran the coil balancing procedure 4 times while iterating through the output matrix optimization.

Attachment 1, pages 1 to 4 show the progression of cross coupling from current output matrix (which is theoretical ideal) to the latest iteration. We plot the sensed DOF ASD which we used to determine the cross coupling when different excitations are fed using the LOCKIN1 feeding 13Hz oscillation of 200 counts amplitude along the vector defined in output matrix. That means, when we change the output matrix, in subsequent tests, we alos change the exciation direction along with it.

Unfortunately, we don't see a very good optimizations over iterations. While we see some peaks going down in sensed PIT and sensed POS (through MC_F), we rather see an increase in cross coupling in the sensed YAW.

Scripts:

• For running the tests, we used script in scripts/SUS/OutMatCalc/crossCoupleTest.py and wrote commanding scripts in the /users/anchal/20210329_MC2_TestingNewOutMat .
• The optimization code is at in scripts/SUS/OutMatCalc/outMatOptimize.py.
• The code reads sensed DOF data using nds2 and calculated cross spectral density among the sensed DOF at the excitation frequencies.
• This is normalized by the power spectral density of reference data (no excitation) and power spectral density of position data to create a TF estimate.
• The real values of the sensor matrix thus created is used to get the inverse matrix.
• The inverse matrix is first normalized along each row by diagonal elements to get 1 there and then multiplied by previous output matrix to create a new output matrix.
• I guess, reading the code will be a better way of understanding this algorithm.