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I have a requirement of building an Inertial Measurement Unit (IMU) from the following sensors:

  • Accelerometer
  • Gyroscope
  • Magnetometer

I must integrate this data to derive the attitude of the sensor platform and the external forces involved (eg. subtract tilt from linear acceleration).

I must then use this information to compliment a standard GPS unit to provide higher consistent measurements than can be provided by GPS alone.

I do understand the basic requirements of this problem:

  • Integrate sensors. (To cancel noise, subtract acceleration).
  • Remove noise. (Kalman filter)
  • Integrate IMU measurement into GPS.

Whilst there are various libraries currently around that would do this for me (http://code.google.com/p/sf9domahrs/) I need to understand the mechanisms involved to a level where I am able to explain the techniques to other individuals after I have implemented the solution.

I have been looking at the following resources, but I am unsure which I should go for... I need something covering Sensor Fusion, Filtering, IMU, Integration.

Multisensor-Fusion-Integration-Intelligent-Systems

Positioning-Systems-Inertial-Navigation-Integration

Mechatronics-Intelligent-Systems-Off-road-Vehicles

Autonomous-Flying-Robots-Unmanned-Vehicles

I hope someone experienced in this area can provide any recommendations.

Many thanks.

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This is not a physics question as far as I can see, but rather a technological one. – dmckee♦ Apr 3 '12 at 14:19
@dmckee where would you suggest this question should go if not here? – James Apr 3 '12 at 14:24
I'm not aware of any site on the Stack Exchange network where this would be on topic. That happens: there is no guarantee that your question has a home. – dmckee♦ Apr 3 '12 at 14:26
Sensor fusion is not a physics question but it should be on topic at our partner site Computational Science at scicomp.stackexchange.com. – Alexander Apr 3 '12 at 16:09

closed as off topic by dmckee♦ Apr 3 '12 at 14:19

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