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If you bought the cheap magnetomter module like HMC5883L you can not use it without calibration. Measurement of magnetic field will be subjected to distortion. There are two categories of these distortions: the hard iron distortions and the soft iron distortions. The hard iron errors refer to the presence of magnetic fields around the sensor (magnets, power supply wires) and are related to measurement offset errors, while the soft iron errors refer to the presence of ferromagnetic materials around the sensor, which skew the density of the Earth's magnetic field locally and are related to scaling offset errors.
You can read more information about these distortions. In other words, to get the correct magnetometer data you should get the calibrated magnetometer data. One of the ways to resolve this problem: you should apply the bias to the vector of the non calibrated magnetometer data (X, Y, Z coordinates) and then multiply the transformation matrix by this resulting vector: Picture 1 In this case the magnetometer calibration is the process of getting the transformation matrix and the bias. To get these data you can use the MagMaster program. Example of using the MagMaster Hardware:. Software:. MagMaster (placed in MagMaster folder).
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MagViewer (placed in MagMaster folder) Firmware:. Arduino Sketch (placed in MagMaster folder) Picture 2 Picture 3 Picture 4 Connect the magnetometer module to the arduino board via I2C bus (picture 4). Upload the arduino sketch to the arduino board (see 'ArduinoCode' folder in the 'MagMaster' folder). This arduino sketch requires the HMC5883L library, copy the folder 'HMC5883L' (placed in 'ArduinoCode' folder) to the folder 'C: Program Files Arduino libraries'.
Then run the MagViewer.exe, select the serial port of the arduino board (the boud rate of the seraial port should be 9600 bps) and click 'Run MagViewer'. Now you can see the coordinates of the magnetometer data vector in 3D space on a real time (picture 5, video 1, 2). These data are not calibrated yet. Picture 5 Video 1 Video 2 If you see the points of the magnetometer vector coordinates in 3D space the arduino board and the PC connection works right. Now close the MagViewer window and run the MagMaster.exe (picture 6). Select the serial port of the arduino board. The green strings X, Y, Z will indicates the coordinates of the magnetometer vector.
Picture 6 Place the magnetometer module as shown on the picture 8.1 and click 'Point 0' button of the 'Axis X+' groupbox. For the placement of the module you can use the wooden bar or the paper box (picture 7). If you can not connect your magnetometer device to PC then you can use any other way to get to know the magnetometer data. You can enter these data in the program manually. Picture 7 Place the magnetometer as shown on the picture 8.2 and click 'Point 180' button of the 'Axis X+' groupbox and so on. You should do in the following way:.
Picture 8.1: 'Point 0', 'Axis X+'. Picture 8.2: 'Point 180', 'Axis X+'. Picture 8.3: 'Point 0', 'Axis X-'. Picture 8.4: 'Point 180', 'Axis X-'. Picture 8.5: 'Point 0', 'Axis Y+'.
Picture 8.6: 'Point 180', 'Axis Y+'. Picture 8.7: 'Point 0', 'Axis Y-'. Picture 8.8: 'Point 180', 'Axis Y-'. Picture 8.9: 'Point 0', 'Axis Z+'. Picture 8.10: 'Point 180', 'Axis Z+'.
Picture 8.11: 'Point 0', 'Axis Z-'. Picture 8.12: 'Point 180', 'Axis Z-' Picture 8 You should fill the table. After that click 'Calculate Transformation Matrix and Bias' and get the required matrix and bias (picture 9). Picture 9 The transformation matrix and the bias are got. Now you can calculate the calibrated magnetometer data in your device on a real time with using the matrix and the bias as shown on picture 1. The example of the arduino sketch of using this calculation you can find in the 'ArduinoTestResults' folder.
You can apply the sphere radius stabilization algorithm to your program (use for it the ArduinoRadiusStabilization folder placed in MagMaster folder). The calibrated magnetometer vector coordinates in 3D space with the radius stabilization shown on the picture 10 and video 3, 4. Picture 10 Video 3 Video 4 Using of the arduino is only example, you can easy adopt the arduino code for any other system and use the MagMaster program with it.
Frank, Have you made any progress on your program? I'm also trying something myself. I took the 3Dscatter processing sketch and made an android 'app' that reads an HMC5883 over the USB. It gives the same visual as Yuri's MagViewer. If I can wrap my head around his matrix math code, I want to add a button to calculate the transformation and bias.
BTW, Yuri, I finally got my board calibrated using your MagMaster. No point in borrowing if I couldn't get it right. Comment by on April 17, 2016 at 6:14pm. Harry, Yes, I have made a fair bit of progress.
I found a MATLAB that does a spherical estimate based on a random (but hopefully representative) set of magnetometer points. Here's the text at the top of the routine:% performs magnetometer calibration from a set of data% using Merayo technique with a non iterative algoritm% J.Merayo et al. 'Scalar calibration of vector magnemoters'% Meas.
Well, I may have spoken too soon about porting the MATLAB routine to C#. I'm getting lost in the translation from MATLAB code to MathNet matrix functions. For instance, I am reasonably sure that the MATLAB line D=triu(qr(D));%avoids to compute the svd of a large matrix corresponds to the MathNet.Numerics code //D=triu(qr(D));%avoids to compute the svd of a large matrix QR DQR = D.QR; Matrix Q = (Matrix)DQR.Q; Matrix R = (Matrix)DQR.R; Matrix D2 = (Matrix)R.UpperTriangle; //this is the same as Octave's triu(qr(D)) But the results from the same input test data set are not identical (close, but not exactly the same). Also, the MATLAB code implements the Cholesky function as a user function, while MathNet implements a Cholesky class - same with the MATLAB code's Usolve & Utsolve functions. So, I'm stuck.
If there is anyone out there who can help with the MATLAB - to - MathNet.Numerics translation, please contact me;-). In the meantime I discovered that the MATLAB code doesn't do a very good job of handling 'outlier' data, so I'm modifying my GUI to allow the user to visually select and remove outlier points from the dataset before using it for calibration. At the very least, I'll wind up with a nice GUI front end to the MATLAB code:/ Frank Comment by on April 20, 2016 at 3:09pm.
Hi All, Well, I was able to produce a decent GUI for magnetometer calibration, based on a MATLAB script. Since I wasn't smart enough to port all the MATLAB math to C#, I did the next best thing - I used calls into Octave to actually run the script, while the GUI does everything else. You still need a recent copy of Octave (I'm using octave-cli-4.0.1.exe), but that is free and readily available for windoze. I thought I had it made, until I discovered that my redistribution license for the EyeShot 3D visualization library I was using had expired, and it was WAY too expensive to re-subscribe! So, I wound up re-doing the entire GUI in WPF in order to use the WPF 3D visualization capability. Along with the use of the, I was able to (mostly) replace the EyeShot niceness with Helix Toolkit viewports and associated objects.
In any case, I have attached a zip file to this post containing the first releasable version of my magnetometer calibration utility, and a screenshot that shows the layout. As can be seen from the above screenshot, the GUI is divided into three main sections. The top section deals with acquiring, saving and importing raw magnetometer data. Data is acquired by connecting your magnetometer's serial output to any PC USB port. While the port is open and acquiring data, the magnetometer (or the device in which it is installed) is rotated in all three axes so as to form a nice filled spheroid of raw points. There is no need to rotate in any particular order - just enough so that all areas in the sphere are covered with some data points.
Outlier points can be pruned by selecting and then removing all points outside a specified radius. The middle section shows the 'raw' and 'calibrated' 3D views, and is intended to facilitate preparation of a raw dataset for input into the MATLAB script, and display of the results of processing all 'raw' points through the calibration expression generated by the script. The bottom section simply displays the compensation expression to be implemented in the end-user's program, along with the actual values generated by the MATLAB script.
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If the values in the Compensation Matrix and the Center Offset are plugged into the Compensation Expression, then raw magnetometer values can be converted point-by-point to calibrated ones suitable for navigation. The utility should be reasonably self-explanatory, but I do plan to create a more detailed blog post on my personal blog '; please check there for additional details. I also plan to set up a GitHub repository, as soon as I figure out how to do it;-). This program is definitely a work in progress, so please feel free to tell me what problems you find or features you think should be included.
Hmm, can't figure out how to attach a file, so instead I have put it on my Google Drive site. It can be downloaded using Regards, Frank.