Directional scaling (of an ellipse)

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SUMMARY

This discussion focuses on the calibration of soft-iron distortion for a 2-axis magnetometer, specifically addressing the concept of directional scaling of the readings that form a rotated ellipse. The user references a Freescale publication regarding the necessity of scaling along the major axis of the ellipse. They explore the use of matrix transformations for scaling and express interest in non-linear programming techniques to achieve a circular locus of measurements. A potential solution involving the composition of rotation and scaling transformations is also mentioned.

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  • Understanding of 2-axis magnetometer calibration
  • Familiarity with matrix transformations for scaling
  • Knowledge of non-linear programming techniques
  • Basic concepts of ellipse geometry and properties
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Electronics engineers, data scientists working with sensor calibration, and researchers in magnetometry seeking to improve measurement accuracy through advanced mathematical techniques.

shimniok
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Hope this is in the right forum. I apologize in advance for my ignorance and imprecise discussion as I am at a major disadvantage, lacking rich mathematical educational background enjoyed by most here.

Background is that I'm curious about calibrating for soft-iron distortion calibration for a magnetometer. If I take a number of readings from a 2-axis magnetometer, the locus of readings forms a rotated ellipse. My understanding from a Freescale publication (pdf) is that calibration involves scaling along the major axis of this ellipse. I believe the correct term is directional scaling?

I've done some reading on using a matrix for scaling along the x and y axes. I've done some extensive searching for any hint as to how one might scale along an arbitrary direction. Or are there better approaches?

Ultimately my thought is this. A theoretical, perfectly calibrated magnetometer will have a locus of measurements that is a perfect circle. So I wonder if I can use some kind of non-linear programming approach to finding a scaling amount that comes closest to a circle by summing squares of difference at each point. This idea itself may be flawed. But it seems to be at least vaguely similar to a technique written about in a paper (pdf) I found recently.

I don't necessarily need the answer spoon fed, but would greatly appreciate some pointers in the right direction so my searches will be more fruitful. Many thanks in advance.
 
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