An Efficient Method for Evaluating the Performance of MEMS IMUs

Abstract

Advances in MEMS technology combined with the miniaturization of electronics, have made it possible to produce chip-based inertial sensor for use in measuring angular velocity and acceleration. These chips are small, lightweight, consume very little power and are extremely reliable. They have therefore found a wide spectrum of applications in the automotive and other industrial applications. Currently, new MEMS inertial sensors or IMUs developed by various manufacturers continue to emerge on the market. However, such sensors should be evaluated in terms of navigation performance. Common testing in the lab can provide parameters such as sensor noise density and bias instability but cannot predict the corresponding performance of a full navigation system. IMU/GPS field testing is the only way to evaluate the performance of MEMS IMUs especially when GPS signals are temporarily blocked. However, testing every MEMS sensor (or IMU) in the field is not practical since it is a time- consuming and costly task. Therefore, the main objective of this paper is the development of an efficient method for evaluating the navigation performance of any MEMS IMU using lab testing only. The developed method is based on using MEMS sensors static data signals to estimate the MEMS sensor errors. Hence, by grafting these errors into the signals of a high quality IMU (gyro drift of 0.005 deg/h), collected in a previously conducted typical field test, a quasi field dataset of the MEMS is obtained since the high quality IMU signals can be considered as the true inertial sensor. Such emulated MEMS IMU field data can then be processed with the corresponding GPS data collected in the same test to evaluate the MEMS IMU navigation performance. To test the efficiency of the proposed method, several land-vehicle kinematic datasets with GPS, a high-quality IMU and different MEMS IMUs were used. Static data of the same MEMS IMUs was collected and then the proposed method was applied. The performance of the MEMS IMU actual and emulated datasets is compared during several GPS signal blockage periods. The results show that both solutions have a similar behavior with an average difference of only 20% in terms of accumulated position drifts. This illustrates the usefulness of the proposed technique in addition to the cost and time savings.