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I have a requirement of building an Inertial Measurement Unit (IMU) from the following sensors:
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:
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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IMU and GPS sensor fusion to determine orientation and position. Use inertial sensor fusion algorithms to estimate orientation and position over time. The algorithms are optimized for different sensor configurations, output requirements, and motion constraints.
GPS can only give you position and update rates are provided at a slower speed. A GPS INS fuses IMU data with calibrated IMU data with the GPS solution. As a result, this gives you orientation data, roll pitch and heading, and it will give you update rates at a higher rate than the GPS can.
The main difference between an Inertial measurement unit (IMU) and an AHRS is the addition of an on-board processing system in an AHRS, which provides attitude and heading information. This is in contrast to an IMU, which delivers sensor data to an additional device that computes attitude and heading.
Gyroscope accelerometer magnetometer sensor (IMU)IMUs are essentially Accelerometers + Gyroscopes + Magnetometer sensors, making it a complete package capable of easily calculating orientation, position, and velocity!
I have implemented sensor fusion for the Shimmer platform. These have been a big help:
An introduction to inertial navigation
An Introduction to the Kalman Filter
Pedestrian Localisation for Indoor Environments
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