Robustness Evaluation and Improvements of an In-situ Hand Calibration Method for Low-end IMUs in Pedestrian Navigation Applications

Y. Li, X. Niu, Q. Wang, C. Shi

Abstract:	GNSS (Global Navigation Satellite Systems) and INS (Inertial Navigation Systems) have different advantages and can be integrated to provide variety of navigation information which is precise, reliable, and with high data rate. Especially during these decades, advances in Micro-Electro-Mechanical Systems (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-sized, light-weight, with low power consumption, extremely low cost and high reliability. By virtue of such advantages, MEMS chips have become appropriate candidates for various applications such as pedestrian navigation systems (PNS) for seamless indoor/outdoor positioning. With MEMS gyros and accelerometers installed in the consumer electronics, various applications can be chosen according to personal interests. However, the error levels of MEMS inertial sensors can be several magnitudes higher than that of traditional ones. These errors, if not compensated for, will accumulate and lead to increasing attitude and position errors during the navigation process. Calibration is known to be the fundamental way to remove the major part of the deterministic sensor errors of inertial sensors and IMUs. The gyro and accelerometer biases and scale factors are the dominant error sources during the IMU stand-alone process. Approximately, for 2-D navigation, the gyro biases result in a position error proportional to the time cubed. Meanwhile, the accelerometer biases and the sensor scale factors introduce position errors proportional to time squared. Calibrations are particularly useful for the removal of the biases and scale factor errors. However, both the biases and scale factors of the MEMS sensors will change with time and are highly dependent on the environmental conditions such as temperature. Therefore, even though in-lab calibration at room temperature is known to be the useful way to remove the major part of the deterministic sensor errors, the actual values of sensor errors vary from that obtained through calibration process due to the difference between the operational and calibration temperatures. Thus a quick and convenient in-field calibration is needed to mitigate the drift of inertial sensor errors. The calibration process should be doable by a non-professional user without any specific equipment. To meet the above demands, we have developed an efficient in-situ hand calibration method. The algorithm of the proposed calibration method makes use of the navigation algorithm of the loosely-coupled GNSS/INS integrated systems, but uses a kind of pseudo GNSS observations when there is no accurate GNSS observation. Such pseudo-observations can be stated as: if an IMU was rotating approximately around its measurement center, the range of its position and its linear velocity would be both within a limited scope. Using a Kalman filtering algorithm, the biases and scale factors of both accelerometer triad and gyroscope triad can be calibrated together within a short period (about 30 seconds), requiring only motions by hands. This hand calibration method is suitable for most consumer grade MEMS IMUs due to its zero cost and easy operation. The hand calibration method had shown enough accuracy for MEMS IMUs, but requires the users to stay put for a period. However, the real applications request that the IMU errors can be calibrated and compensated while the users are moving, e.g. walking, taking a bus or train and etc. During these navigation scenarios, the accuracy of the pseudo-observations will be impacted by the motions. In this paper, the performance of this calibration method will be evaluated under typical pedestrian navigation scenarios. To be specific, we will investigate the impact of the pedestrian motions on the availability of the pseudo-observations. Furthermore, the investigation results can be used to guide the improvement of the calibration method. During the pedestrian navigation process, the calibration algorithm is realized based on an extra Kalman filter, which is separated from the algorithm of pedestrian dead reckoning (PDR). From the algorithm perspective, several ways are considered to improve the performance of the calibration method. A quality control mechanism for the use of the pseudo-observations is designed. Such quality control mechanism can keep the calibration algorithm away from being destroyed by the unreasonable use of pseudo-observations under some extreme situations such as sudden acceleration or deceleration. Also, there is specific algorithm which makes auto detection of the best chances for calibration. The proposed calibration method relies on the IMU motions operated by the user hands, to make the sensor errors observable through the pseudo observations in the Kalman filtering. Thus we also analyze the observability of the system. This kind of analysis can help understand the estimator performance. Besides, it provides guidelines of the calibration motion to improve the efficiency of the calibration. The GNSS signals are also used as the measurements when they are available. The measurement noises (i.e. the inaccuracy) of both the pseudo-observations and GNSS observations are manifested in the measurement noise covariance matrix R, and are set and tuned according to the actual motions. Different MEMS IMUs are used to enrich the real tests. Research of this paper will conclude whether the proposed pseudo-observations are robust enough for the extra on-line calibration of IMU errors. It brings a new perspective of improving the performance of low cost pedestrian navigation systems: by calibrating the IMU errors through excavating and using extra prior information. The outcomes of this paper are helpful to promote the better utilization of low cost inertial sensors and navigation systems.
Published in:	Proceedings of the 26th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2013) September 16 - 20, 2013 Nashville Convention Center, Nashville, Tennessee Nashville, TN
Pages:	2213 - 2220
Cite this article:	Li, Y., Niu, X., Wang, Q., Shi, C., "Robustness Evaluation and Improvements of an In-situ Hand Calibration Method for Low-end IMUs in Pedestrian Navigation Applications," Proceedings of the 26th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2013), Nashville, TN, September 2013, pp. 2213-2220.
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