The Covariance Matrix Analysis for Near Field Sources Localization Model

The Covariance Matrix Analysis and Statistics for Near-field Sources Localization Model

“…The decomposition of W into the steering-localization matrix A and the signal sources matrix C in the noncoherent situation for the far and near-field situation can be performed via the same known algorithms (i.e. Beamforming or MUSIC) [1,2]. Defined parameters for the sampling frequency and the number of the samples gave satisfactory results.…”

“…The basis for the localization in near-field model is Hertzian dipole theory. The general condition for this model is that the distance between sources and the planar equidistant sensor array is in radiative near-field region defined in [1]. The l-th source is described by its coordinates [x l ,y l ,z l ] and its dipole moment p0 l with components [px l ,py l ,pz l ] and the condition is z l = 0 and pz l = 0.…”

“…The decomposition of W into A and C in non-coherent situation for the far and near-field situation can be performed via known algorithms (i.e. maximum beamforming or MUSIC) [1,2]. Coherent situation in far-field model can be solved with the same algorithms after "spatial smoothing" pre-processing, under specific periodical W structure condition [6,8].…”

“…This paper is an extension of work originally presented in New Trends in Signal Processing 2018 [1]. The original article was focused on the sensors signal covariance matrix analysis of near-field region and on similarities and differences between nearand far-field models based on the "harmonics parameters retrieval" and consequences to the signal source parameters estimation.…”