Accurate Indoor Navigation System Based on IMU/LP-MM Integrated Method Using Kalman Filter Algorithm

Authors

Abdullah Mohammed Bahasan, Hadramout universityFollow

Abstract

Abstract

The demand for navigation systems is rapidly increasing, especially in indoor environments which the signal of GPS is not available. Therefore the Inertial Measurement Unit (IMU) system is a suitable navigation system in such indoor environments. It usually consists of three accelerometers and three gyroscopes to determine position, velocity and attitude information, respectively, without need of any external source. But this type of navigation systems has errors growth with time due to accelerometers and gyroscopes drifts. This paper introduces indoor navigation system based on integrated IMU navigation system with proposed system called Landmarks Points-Map Matching (LP-MM) system using Kalman Filter (KF) algorithm to reduce and correct errors of IMU navigation system. The proposed LP-MM navigation system is based on determine several landmark points on edges of required indoor environment. These landmark points are used as reference landmark points. The KF algorithm is used to estimate and correct errors of IMU system depending on the reference landmark points that putting on edges of indoor environment. The proposed navigation system was tested on indoor reference trajectories. its results was compared with other solutions that used the IMU system only. The comparison showed a significant improvement in position accuracy comparison to using the IMU system only (no aiding). This proposed method also introduces a reliable, low cost and small size navigation solution making it a suitable system for lot of autonomous an indoor navigation applications.

Recommended Citation

Bahasan, Abdullah Mohammed (2022) "Accurate Indoor Navigation System Based on IMU/LP-MM Integrated Method Using Kalman Filter Algorithm," Hadhramout University Journal of Natural & Applied Sciences: Vol. 19: Iss. 2, Article 1.
Available at: https://digitalcommons.aaru.edu.jo/huj_nas/vol19/iss2/1