Abstract
Due to the universal presence of motion, vibration, and shock, inertial motion sensors can be applied in various contexts. Development of the microelectromechanical (MEMS) technology opens up many new consumer and automotive applications for accelerometers and gyroscopes. The large variety of application creates different requirements to inertial sensors in terms of accuracy, size, power consumption and cost. It makes it difficult to choose sensors that are suited best for the particular application. Signal processing methods depend on the application and should reflect on the physical principles behind this application. This chapter describes the principles of operation of accelerometers and gyroscopes, different applications involving the inertial sensors. It also gives examples of signal processing algorithms for pedestrian navigation and motion classification.
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Notes
- 1.
In short, non-holonomic constraints allow to neglect the lateral and vertical speeds of the vehicle.
- 2.
Scale factors are not exactly constant: for instance, the scale factors of MEMS sensors depend strongly on the temperature.
- 3.
There exist higher-order Gauss–Markov process where the difference equation (3) contains older values of the process.
- 4.
The growth is almost quadratic with small heading errors; however, with larger heading errors, the sine and cosine functions in (19) bound the error growth.
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Collin, J., Davidson, P., Kirkko-Jaakkola, M., Leppäkoski, H. (2013). Inertial Sensors and Their Applications. In: Bhattacharyya, S., Deprettere, E., Leupers, R., Takala, J. (eds) Handbook of Signal Processing Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-6859-2_3
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