Low cost MEMs sensors are integrated in almost every Android device these days. These sensors are very useful in various applications like gaming, navigation, augmented reality etc. Once we know the correct orientation of the device, it becomes easy to develop such applications.
Android devices come with several built-in sensors like Accelerometer, Gyroscope, Magnetometer, Proximity, Pressure sensors etc. For positioning, tracking, activity recognition applications these sensors play a critical role.
Orientation can be determined by sensor fusion of accelerometer and magnetometer but it provides good accuracy as long as device is stationary or not moving linearly and also it suffers from surrounding magnetic interference. Orientation estimation systems often use gyroscope to increase reliability and accuracy.
Although gyroscopes provide a quick response to change in angles and do not have problems like interference, they suffer from bias and integration errors which introduce drift in signal.
In this paper a DNRF (Drift & Noise Removal Filter) is described that is implemented by sensor fusion of gyroscope, magnetometer and accelerometer which minimizes the drift and noise in output orientation. A numerical error correction approach is also mentioned to minimize the errors caused by gyro signal integration.
The orientation results obtained by proposed DNRF method are smooth and less noisy as compared to digital compass. The technique described is a less computational method of smart phone orientation that reduces the numerical as well as bias errors in gyro signal.
It has been observed that the proposed DNRF method provides a smooth, and less noisy orientation as compared to conventional digital compass. Moreover, by adding Gimbal lock removal block it becomes possible to get orientation in any arbitrary position.
To read this external content in full, download the complete paper from the author archives at Liverpool John Moores University, United Kingdom.