10-DOF MEMS IMU INCORPORATES SENSOR FUSION ALGORITHM FOR EXCEPTIONALLY PRECISE ORIENTATION SENSING IN INDUSTRIAL, DEFENSE AND AVIONICS APPLICATIONS
Kalman filtering is a mathematical algorithm that estimates the given state of a noisy, variable process by taking multiple measurements over time, and merging these with a predictive state estimator. When embedded in the ADIS16480, the Kalman filter intelligently combines the MEMS IMU’s motion sensor inputs to deliver exceptionally precise positioning data, even under complex operating conditions characterized by constant, unpredictable movement. By embedding the filter in the Blackfin processor’s core, ADI also saves designers the time and cost associated with the intensive code development, testing and external processing required by other MEMS IMUs.
“When determining exact position or orientation, industrial and defense electronics systems are dependent not only on the accuracy of individual sensors, but on the sophistication of accurately and dynamically combining multiple inputs,” said Bob Scannell, iSensor business development manager, MEMS/Sensors Group, Analog Devices. “The ADIS16480 MEMS IMU’s embedded, extended Kalman filter helps the system discern which sensors to ‘trust’ based on contextual awareness. This allows system-level designers to achieve positional accuracy under a variety of demanding environmental conditions by either letting the filter autonomously adjust, or by tuning the filter via its programmable interface.”