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A scheme to improve the indoor localization by estimating heading orientation and step detection is proposed for smartphones. The accuracy can be improved with weighting factors to the accelerometer and gyroscope using the motion estimator.
This paper proposes an indoor navigation technique for a smartphone using WiFi. An improved Kalman filter (IKF) is proposed to navigate in dynamic indoor environments with the fingerprinting technique. The results indicate that the IKF shows improved accuracy when compared to the conventional Kalman filter in a real-time scenario.
This paper presents an effective way for indoor navigation using inertial measurement unit (IMU) in conjunction with a quick response (QR) code. Usage of QR codes helps to compensate the errors from the IMU thereby providing accurate navigation. This technique involves very less cost and can be implemented in a straight forward manner.
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