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This repository contains a C++ class for IMU sensor modeling.
Hi,
I have doubt on capturing the raw imu values while IMU remaining still. That means, we have to keep the IMU z-axis aligned with gravity direction. is this interpretation is correct or we can capture the values at any orientation of IMU with gravity direction.
If we can capture at any orientation, the projection of acceleration due to gravity on xy-plane will be coming as a bias in the measurements. is this interpretation is correct?
When collecting data with Ascending Technologies Pelican quadrotor for 4 hours, the following Allan variance and power spectral density is produced:
This result does not reflect the anticipated Allan variance curve presented in the IMU Sensor Model Instructions. The issue then is (1) why does this discrepancy exist? and (2) can the sensor model code be modified to also model this discrepancy?
It seems that this code is intended to be used for gyro data "Only". I can see at the code a line where the data is integrated to obtain the angle.
% Integration of samples over time to obtain output angle ? theta = cumsum(meas)/fs;
Would it be possible to remove this line and run it for accelerometer data too?
Thank you beforehand.
Greetings Hanley,
I wanted to create a new thread for several questions and concerns that I have. I hope you can help me.
noise = Angle Random Walk + Bias Instability + Rate Random Walk.
However, let's assume that I'm finding the different values for an accelerometer data. Where the units are going to be g/sqrt(s),g/s and g/s^2 for Random Walk, Bias Instability and Rate Random Walk respectively. How are these values added with different units?.
In the following image. I have a concave section and the beginning. I can fit most of the other curves, but I was trying to understand the reason of this concavity. Is there any other type of noise that I'm not aware? What happens when I get curve such like this one? Would this part just discarded for the the noise analysis?
If one of the lines doesn't fit well, how can this be interpreted? Would it mean that particular parameter is not dominant in the noise analysis?
Thank you for your help and response beforehand, any help will be appreciated it.
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