Array shape self-calibration using particle swarm optimization and decaying diagonal loading
Array shape self-calibration using particle swarm optimization and decaying diagonal loading
- Author(s): Shuang Wan ; Pei-Jung Chung ; B. Mulgrew
- DOI: 10.1049/ic.2010.0238
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- Author(s): Shuang Wan ; Pei-Jung Chung ; B. Mulgrew Source: Sensor Signal Processing for Defence (SSPD 2010), 2010 page ()
- Conference: Sensor Signal Processing for Defence (SSPD 2010)
- DOI: 10.1049/ic.2010.0238
- ISBN: 978-1-84919-617-8
- Location: London, UK
- Conference date: 29-30 Sept. 2010
- Format: PDF
Calibration of array shape error is a key issue for most existing direction finding algorithms. In this paper, we propose a new procedure that employs particle swarm optimization (PSO) and decaying diagonal loading (DDL) techniques to optimize the unconditional maximum likelihood (UML) function for array self-calibration. The proposed method is able to self- calibrate large array shape error. Moreover, it outperforms previous ones in terms of mean squared error that attains Cramer-Rao bound. An example of 5-sensor and 3-source geometry is used to demonstrate the efficacy of the proposed method. (5 pages)
Inspec keywords: particle swarm optimisation; maximum likelihood estimation; calibration; sensor arrays; array signal processing; direction-of-arrival estimation
Subjects: Other topics in statistics; Sensing devices and transducers; Signal processing and detection; Optimisation techniques; Optimisation techniques; Other topics in statistics; Signal processing theory
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