Comments (5)
So I assume the difference of the reading vector and the combined bias vector should be multiplied by either the A_1
matrix or the A
matrix
Matrix<double> A_1 = SQ * hm / hmb;
Console.WriteLine("A-1 matrix:");
Console.WriteLine(A_1.ToString());
// Calculate A to permit comparison with MagCal
Matrix<double> A = A_1.Inverse();
Console.WriteLine("A matrix:");
Console.WriteLine(A.ToString());
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Hi,
the equation on the picture is correct. The transformation matrix is the A_1 matrix.
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// Calculate combined bias
B[0] = -B[0]; // x-axis combined bias
B[1] = -B[1]; // y-axis combined bias
B[2] = -B[2]; // z-axis combined bias
As the bias vector is produced by 10 rows of data. Can it be used with any of the data rows in the set (with A_1
matrix) to produce a calibrated vector?
In my case I have access to live sensor data. Do you think it would work to take the 10 most recent sensor updates and expect a good result? Can I use one row of data?
I have read more about magnetometer calibration, and some more source code examples. As I understand it a few values (which should be as accurate as possible) is taked to construct the sphere.
So MagCal is about constructing the A_1 matrix based off sphere/ellipsoid calculation. So it is not about implementing calibration on live data fully - it has to be done all well. (My use case being mobile app development)
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Can I generate a sphere with earth's magnetic field vector of world magnetic model? See: https://www.ngdc.noaa.gov/geomag/WMM/calculators.shtml - you can use Single Point Calculator and give latitude longitude of gps. It should give the ideal sphere based off the actual earth's magnetic field.
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I managed to set it up correctly. With list storing recent values, calibrating the newest value. It had almost the same calibration accuracy as the default ios calibration.
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