Blind separation of complex-valued satellite-AIS data for marine surveillance: a spatial quadratic time-frequency domain approach

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 cyclicfrequencies, 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.
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Omar Cherrak, Hicham Ghennioui, Nadège Thirion-Moreau, El Hossein Abarkan. Blind separation of complex-valued satellite-AIS data for marine surveillance: a spatial quadratic time-frequency domain approach. International Journal of Electrical & Computer Engineering (2088-8708) , 2019, 9 (3), pp.1732-1741. ⟨10.11591/ijece.v9i3.pp1732-1741⟩. ⟨hal-02057520⟩

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