Abstract: At present, pedestrian dead reckoning(PDR) has gradually become a hot spot in the research and application of indoor location. In view of the large cumulative error of the gyroscope in calculating the pedestrian heading, a pedestrian heading algorithm based on smart phone sensor is proposed. The algorithm adjusts the error compensation coefficient of the PI regulator in real time according to the angular velocity data output by the gyroscope and the parameters of the mobile phone sensor to compensate the heading angle of the preprocessed accelerometer and the magnetometer data. The gyroscope data is filtered by complementary filtering to obtain the combined heading angle.Based on low cost smart phone, we collect smart phone sensor data under the strong and weak environment of magnetic field, and compare the accuracy of the algorithm with the traditional complementary filtering algorithm and the nine axis data fusion algorithm in calculating pedestrian direction.Experimental results show that compared with the traditional complementary filtering algorithm and the nine-axis data fusion algorithm, the proposed algorithm improves the positioning accuracy by 68.4% and 65.9%, respectively, and the average heading error decreases by 3.4° and 1.8° in the indoor environment of strong magnetic interference,it verifies the proposed algorithm has better anti-magnetic interference performance and improves the reliability of pedestrian heading.

Key words: smartphone sensor, gyroscope, complementary filtering algorithm, PI regulation, magnetic interference