Making sense from sensor fusion data

Sensor fusion is becoming a popular technique for increasing the accuracy and useability of data from MEMS sensors in smartphones and other consumer devices. In essence, the technique involves combining data from multiple sensors to produce a faster and more accurate representation of what is happening outside the system.

Smartphones are prime candidates for sensor fusion techniques, and such implementations typically feature an accelerometer, gyroscope and magnetic sensor/magnetometer.

“In sensor fusion, the accelerometer, gyroscope and magnetic sensor are working in a team, they help each other,” explains Jay Esfandyari, MEMS Product Marketing Manager at ST Microelectronics. “You can take advantage of the strengths of those sensors and also use them to compensate for the weaknesses of each other.”

With MEMS gyroscopes for example, the major issue is drift, but data from the magnetic sensor can be used to compensate for this. In a smartphone, if the phone stops moving for a short period of time, perhaps a second, that can be sensed by the accelerometer; data from the gyroscope at that precise moment can then be used as the new zero rate. Working together allows the sensors to provide a meaningful output which is not subject to the weaknesses of any of the three sensors.

ST’s software solution for sensor fusion, the iNEMO Engine Sensor Fusion Suite combines data from an ST MEMS accelerometer, gyroscope and magnetic sensor (9 degrees of freedom).

“It gives you all the information you need from the sensors to develop your application, you don’t need to worry about the noise issue or the drift issue or the magnetic distortion issue,” Esfandyari says. “What you get out of iNEMO Engine is clean, reliable, robust data that you can use to develop the application.”

You can read the rest of this article in the September issue of Electronic Specifier Design by clicking here.

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