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‎README.md‎

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@@ -6,11 +6,30 @@ Actually, just analyze the Allan Variance for the IMU data. Collect the data whi
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## refrence
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refrence Matlab code: [`GyroAllan`](https://github.com/XinLiGitHub/GyroAllan "GyroAllan")
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Refrence technical report: ['Allan Variance: Noise Analysis for Gyroscopes'](http://cache.freescale.com/files/sensors/doc/app_note/AN5087.pdf "Allan Variance: Noise Analysis for Gyroscopes")
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Refrence Matlab code: [`GyroAllan`](https://github.com/XinLiGitHub/GyroAllan "GyroAllan")
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## IMU Noise Values
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Parameter | YAML element | Symbol | Units
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--- | --- | --- | ---
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Gyroscope "white noise" | `gyr_n` | <img src="https://latex.codecogs.com/svg.latex?{%5Csigma_g}"> | <img src="https://latex.codecogs.com/svg.latex?{%5Cfrac%7Brad%7D%7Bs%7D%5Cfrac%7B1%7D%7B%5Csqrt%7BHz%7D%7D}">
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Accelerometer "white noise" | `acc_n` | <img src="https://latex.codecogs.com/svg.latex?{%5Csigma_a}"> | <img src="https://latex.codecogs.com/svg.latex?{%5Cfrac%7Bm%7D%7Bs^2%7D%5Cfrac%7B1%7D%7B%5Csqrt%7BHz%7D%7D}">
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Gyroscope "bias Instability" | `gyr_w` | <img src="https://latex.codecogs.com/svg.latex?{%5Csigma_b_g}"> | <img src="https://latex.codecogs.com/svg.latex?{%5Cfrac%7Brad%7D%7Bs^2%7D%5Cfrac%7B1%7D%7B%5Csqrt%7BHz%7D%7D}">
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Accelerometer "bias Instability" | `acc_w` | <img src="https://latex.codecogs.com/svg.latex?{%5Csigma_b_a}"> | <img src="https://latex.codecogs.com/svg.latex?{%5Cfrac%7Bm%7D%7Bs^3%7D%5Cfrac%7B1%7D%7B%5Csqrt%7BHz%7D%7D}">
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* White noise is at tau=1;
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* Bias Instability is around the minimum;
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(according to technical report: ['Allan Variance: Noise Analysis for Gyroscopes'](http://cache.freescale.com/files/sensors/doc/app_note/AN5087.pdf "Allan Variance: Noise Analysis for Gyroscopes"))
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## sample test
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<img src="figure/imu.jpg">
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<img src="figure/gyr.jpg">
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<img src="figure/acc.jpg">
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* blue : Vi-Sensor, ADIS16448, `200Hz`
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* red : 3dm-Gx4, `500Hz`

‎figure/acc.jpg‎

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‎figure/gyr.jpg‎

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‎sample_data/data_16448_acc_t.txt‎

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