2011IEICE Transactions on CommunicationsRequires access

TDoA Localization Based on Particle Swarm Optimization in UWB Systems

Tan N. Le, Jaewoon Kim, Yoan Shin

Open publisher page 11 citations

Abstract

We propose an improved TDoA (Time Difference of Arrival) localization scheme based on PSO (Particle Swarm Optimization) in UWB (Ultra Wide Band) systems. The proposed scheme is composed of two steps: the re-estimation of TDoA parameters and the re-localization of tag position. In both steps, the PSO algorithm is employed to improve the performance. In the first step, the proposed scheme re-estimates the TDoA parameters obtained by traditional TDoA localization to reduce the TDoA estimation error. In the second step, the proposed scheme with the TDoA parameters estimated in the first step, re-localizes the tag to minimize the location error. Simulation results show that the proposed scheme achieves better location performance than the traditional TDoA localization in various channel environments.

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What this paper is about

We propose an improved TDoA (Time Difference of Arrival) localization scheme based on PSO (Particle Swarm Optimization) in UWB (Ultra Wide Band) systems. The proposed scheme is composed of two steps: the re-estimation of TDoA parameters and the re-localization of tag position. In both steps, the PSO algorithm is employed to improve the performance. In the first step, the proposed scheme re-estimates the TDoA parameters obtained by traditional TDoA localization to reduce the TDoA estimation error. In the second step, the proposed scheme with the TDoA parameters estimated in the first step, re-localizes the tag to minimize the location error. Simulation results show that the proposed scheme achieves better location performance than the traditional TDoA localization in various channel environments.

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Available abstract

We propose an improved TDoA (Time Difference of Arrival) localization scheme based on PSO (Particle Swarm Optimization) in UWB (Ultra Wide Band) systems. The proposed scheme is composed of two steps: the re-estimation of TDoA parameters and the re-localization of tag position. In both steps, the PSO algorithm is employed to improve the performance. In the first step, the proposed scheme re-estimates the TDoA parameters obtained by traditional TDoA localization to reduce the TDoA estimation error. In the second step, the proposed scheme with the TDoA parameters estimated in the first step, re-localizes the tag to minimize the location error. Simulation results show that the proposed scheme achieves better location performance than the traditional TDoA localization in various channel environments.

Key concepts: Multilateration, Computer science, Particle swarm optimization, FDOA, Scheme (mathematics), Algorithm, Time of arrival, Position (finance)

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