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Omar Cherrak
Institut Supérieur du Génie appliquée (IGA)
Computer Science & IT Electrical & Electronics Engineering

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Blind separation of complex-valued satellite-AIS data for marine surveillance: a spatial quadratic time-frequency domain approach Omar Cherrak; Hicham Ghennioui; Nadege Thirion Moreau; El Hossein Abarkan
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 3: June 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1396.173 KB) | DOI: 10.11591/ijece.v9i3.pp1732-1741

Abstract

In this paper, the problem of the blind separation of complex-valued Satellite-AIS data for marine surveillance is addressed. Due to the specific properties of the sources under consideration: they are cyclo-stationary signals with two close cyclic frequencies, we opt for spatial quadratic time-frequency domain methods. The use of an additional diversity, the time delay, is aimed at making it possible to undo the mixing of signals at the multi-sensor receiver. The suggested method involves three main stages. First, the spatial generalized mean Ambiguity function of the observations across the array is constructed. Second, in the Ambiguity plane, Delay-Doppler regions of high magnitude are determined and Delay-Doppler points of peaky values are selected. Third, the mixing matrix is estimated from these Delay-Doppler regions using our proposed non-unitary joint zero-(block) diagonalization algorithms as to perform separation.
Co-Authors El Hossein Abarkan Hicham Ghennioui Nadege Thirion Moreau