Some 2q-th (q ≥ 2) order extensions of the MUSIC method, exploiting the information contained in the 2q-th (q ≥ 2) order statistics of the data and called 2q-MUSIC methods, have been proposed recently for direction finding of non Gaussian signals. These methods are asymptotically robust to a Gaussian background noise whose spatial coherence is unknown and offer increasing resolution and robustness to modeling errors jointly with an increasing processing capacity as q increases. However, 2q-MUSIC methods have been mainly developed for arrays with space diversity only and cannot put up with arrays of sensors diversely polarized. The purpose of this paper is to introduce, for arbitrary values of q (q ≥ 1), three extensions of the 2q-MUSIC methods able to put up with arrays having polarization diversity, which gives rise to the so-called PD-2q-MUSIC (Polarization Diversity 2q-MUSIC) algorithms. These algorithms are shown to increase resolution, robustness to modeling errors and processing capacity of 2q-MUSIC methods in the presence of diversely polarized sources from arrays with polarization diversity.
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