Smartphone-Based Indoor Localization System Using Inertial Sensor and Acoustic Transmitter/Receiver

A Loose-Coupled Fusion of Inertial and UWB Assisted by a Decision-Making Algorithm for Localization of Emergency Responders

“…Unlike the decision-making algorithm proposed in [16], the decision-making algorithm here proposed does not make assumptions on the user mobility. The proposed algorithm is suitable for all movements, runs in real-time, and has low computational requirements, making it a viable solution for IPSs for emergency responders.…”

“…Then, the UWB position is computed, and the data fusion algorithm is executed. Unlike the work in [16], the proposed method is not necessary to perform any additional validation on the UWB data. When the number of anchor nodes in the NLOS condition is less than two, the confidence on the estimated position is very high.…”

“…An EKF is also used in the works [14,15] to fuse inertial data with UWB measurements. Yang et al proposed an EKF to fuse the smartphone inertial sensors with the data of an acoustic localization system [16]. A finite impulse response (FIR) filter is proposed by Zhao et al to fuse inertial and UWB measurements [17].…”

“…For these reasons, in this work, a KF is used to combine the position information obtained from the UWB and PDR systems. Like the approach in [16], data fusion is performed in two stages. In the first stage, the UWB measurements are analyzed to determine the usability of the UWB position estimate.…”

A new method of hybrid indoor localization with inertial sensor

“…The most important reason for the error is that these algorithms may select the wrong reference point for localization. In order to reduce the localization error in the fingerprinting estimation due to dynamic environment, there is also some paper use the Wi-Fi tag to resolve above problems [7].…”