Pedestrian Trajectory Projection Based on Adaptive Interpolation Factor Linear Interpolation Quaternion Attitude Estimation Method

Abstract

In recent years, with the continuous development of the Internet of Things (IoT) technology, smart devices, such as smart homes and smart phones, have been widely used, so the demand for providing specific location services has gradually increased, while the traditional positioning service technology based on satellite information is difficult to provide reliable accuracy in indoor environments due to various constraints; meanwhile, because of the specific conditions of use, positioning methods requiring the presetting of auxiliary equipment will be ineffective. In order to solve these problems, autonomous indoor positioning technology using only a single sensor has an irreplaceable role. This article takes a low-cost, high-precision indoor positioning technique based on step heading style using only a single magnetic angular rate and gravity (MARG) sensor and proposes an interpolation factor-adaptive quaternionic attitude solving algorithm based on linear interpolation (LERP). The method uses a motion state metric matrix for describing the intensity of the current motion state and calculates the interpolation factor adaptively using the motion state metric matrix. Based on the characteristic that different motion states have different optimal interpolation factors, the method adopts the adaptive updating calculation method to automatically update the interpolation factors, which gets rid of the problems that may arise from the pregiven interpolation factors and extends the scope of the method, and the corresponding heading angle calculation can be carried out for all the motion states, and finally, by combining the proposed heading angle estimation method with the high-precision step segmentation method and step length estimation method, a step-length heading-based positioning method is proposed, which achieves an average positioning accuracy of 0.3825 m. Moreover, only one MARG sensor fixed at the waist is used, and the cost of the device is very low at only U.S. 14.9, which satisfies the requirements of high accuracy and low cost at the same time.