Separation of Mixtures of Complex Sinusoidal Signals with Independent Component Analysis

• KIRIMOTO Tetsuo

  University of Electro-Communications

• AMISHIMA Takeshi

  Mitsubshi Elcctric Corp.

• OKAMURA Atsushi

  Mitsubshi Elcctric Corp.

Abstract

ICA (Independent Component Analysis) has a remarkable capability of separating mixtures of stochastic random signals. However, we often face problems of separating mixtures of deterministic signals, especially sinusoidal signals, in some applications such as radar systems and communication systems. One may ask if ICA is effective for deterministic signals. In this paper, we analyze the basic performance of ICA in separating mixtures of complex sinusoidal signals, which utilizes the fourth order cumulant as a criterion of independency of signals. We theoretically show that ICA can separate mixtures of deterministic sinusoidal signals. Then, we conduct computer simulations and radio experiments with a linear array antenna to confirm the theoretical result. We will show that ICA is successful in separating mixtures of sinusoidal signals with frequency difference less than FFT resolution and with DOA (Direction of Arrival) difference less than Rayleigh criterion.

Journal

• IEICE Transactions on Communications

  IEICE Transactions on Communications E94-B (1), 215-221, 2011

  The Institute of Electronics, Information and Communication Engineers

Keywords

• independent component analysis
• fourth cumulant
• complex sinusoidal signals
• separation performance
• radar
• communication

Details

• CRID: 1390282679351712896
• NII Article ID: 10027983193
• NII Book ID: AA10826261
• DOI: 10.1587/transcom.e94.b.215
• ISSN: 17451345
• ISSN: 09168516
• Web Site: http://www.jstage.jst.go.jp/article/transcom/E94.B/1/E94.B_1_215/_pdf
• Text Lang: en
• Data Source:
  • JaLC
  • Crossref
  • CiNii Articles
• Abstract License Flag: Disallowed