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RAR: Real-Time Acoustic Ranging in Underwater Sensor Networks
Kim, Yonghun,Noh, Youngtae,Kim, Kiseon IEEE 2017 IEEE communications letters Vol.21 No.11
<P>As a core component of underwater localization, accurate acoustic ranging is quite challenging because of the harsh characteristics of underwater environments (e.g., refraction and reflection). To enhance ranging accuracy, ranging schemes employing a ray tracing model and a sound speed profile have been proposed; however, the existing schemes require numerous ray tracing iterations to perform ranging estimation within a certain range of accuracy. This renders the solutions that they generate impractical for real-time localization. In this letter, we propose a novel ranging scheme called real-time acoustic ranging (RAR). To reduce computational overhead while maintaining reliable accuracy, RAR exploits the property of ray pattern locality, whereby spatially proximate rays exhibit similar patterns. The results revealed that RAR can ensure a better tradeoff between accuracy and computational overhead than a state-of-the-art solution.</P>
Eunchan Kim,Kiseon Kim IEEE 2010 IEEE signal processing letters Vol.17 No.6
<P>In large-scale sensor networks, localization with mobile beacons is one of the most efficient ways to deploy sensor nodes as well as locate them. Direct communication with mobile beacons has an advantage of improvement in location accuracy by enabling sensor nodes to measure distances to the mobile beacons. Thus, it is important to improve the accuracy in the distance for high accurate positioning. In this letter, we propose a distance estimation scheme with weighted least squares in mobile beacon-based localization. First, we model distance measurements to a beacon node moving along the given linear tracks. Given our measurement model, the proposed scheme uses weighted least squares to minimize errors in distance measurements. Additionally we analyze the lower bound of errors in our distance estimation based on the Cramer-Rao bound. Simulation results show that our scheme can provide improved accuracy in both distance estimation and position estimation.</P>
Mobile Beacon-Based 3D-Localization with Multidimensional Scaling in Large Sensor Networks
Eunchan Kim,Sangho Lee,Chungsan Kim,Kiseon Kim IEEE 2010 IEEE communications letters Vol.14 No.7
<P>Localization is essential in wireless sensor networks to handle the reporting of events from sensor nodes. For 3-D applications, we propose a mobile beacon-based localization using classical multidimensional scaling (MBL-MDS) by taking full advantage of MDS with connectivity and measurements. To further improve location performance, MBL-MDS adopts a selection rule to choose useful reference points, and a decision rule to prevent a failure case due to reference points placed on the same plane. Simulation results show improved performance of MBL-MDS in terms of location accuracy and computation complexity.</P>