Localization Research Based on Low Cost Sensor

Abstract

With the increasing demand for indoor navigation applications, indoor navigation has become a research hotspot in many technical fields. High-precision sensors are expensive, and they are often used in industrial and aerospace applications. Low-cost sensors can cause severe drift and noise. This paper uses a simple, low-cost Inertial measurement unit (IMU) and effectively evaluates the precise position of pedestrians. This paper designs a pedestrian position estimation based on low-cost inertial sensors. To solve the problem of inertial sensing noise and accumulated errors during the movement, based on the EKF algorithm, a multi-condition threshold detection method is proposed, and then a zero-speed update, an angular speed update, and a yaw angle update are designed. In the measurement state, the proposed measurement error vector effectively eliminates the cumulative error during walking. Finally, using this algorithm to perform straight and rectangular walking routes, corresponding experiments were performed on the effectiveness of the method used. The proposed method for estimating the inertial navigation of pedestrians has an error within 3.8%. This basic research is of great significance in rehabilitation training and somatosensory play.