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has been cited by the following article:

• TITLE: Accurate Angle-of-Arrival Measurement Using Particle Swarm Optimization

  AUTHORS: Minghui Li, Kwok Shun Ho, Gordon Hayward

  KEYWORDS: Array Signal Processing, Angle-of-Arrival (AOA) Estimation, Location Positioning, Particle Swarm Optimization, Smart Antennas

  JOURNAL NAME: Wireless Sensor Network, Vol.2 No.5, May 27, 2010

  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.