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Accurate Angle-of-Arrival Measurement Using Particle Swarm Optimization

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DOI: 10.4236/wsn.2010.24047    6,138 Downloads   11,344 Views   Citations

ABSTRACT

As one of the major methods for location positioning, angle-of-arrival (AOA) estimation is a significant technology in radar, sonar, radio astronomy, and mobile communications. AOA measurements can be exploited to locate mobile units, enhance communication efficiency and network capacity, and support location-aided routing, dynamic network management, and many location-based services. In this paper, we propose an algorithm for AOA estimation in colored noise fields and harsh application scenarios. By modeling the unknown noise covariance as a linear combination of known weighting matrices, a maximum likelihood (ML) criterion is established, and a particle swarm optimization (PSO) paradigm is designed to optimize the cost function. Simulation results demonstrate that the paired estimator PSO-ML significantly outperforms other popular techniques and produces superior AOA estimates.

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

M. Li, K. Ho and G. Hayward, "Accurate Angle-of-Arrival Measurement Using Particle Swarm Optimization," Wireless Sensor Network, Vol. 2 No. 5, 2010, pp. 358-364. doi: 10.4236/wsn.2010.24047.

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