A multilinear direction finding (DF) approach for a sensor-array with multiple scales of invariance
In this paper, we introduce a novel direction finding algorithm for a multi-scale sensor-array, that is, an array presenting multiple scales of invariance. We show that the collected data can be represented as a Candecomp/Parafac (CP) model, for which we analyze the identifiability properties. A two-stage algorithm for direction-of-arrival (DOA) estimation with such an array is also proposed. This approach generalizes the results given in [Sidiropoulos et al., 2000] to an array that presents an arbitrary number of spatial invariances. We illustrate, on a particular array geometry, that our method outperforms the ESPRIT-based approach introduced in [Wong and Zoltowski, 1998]. Moreover, we show that the single-snapshot case can be handled by our method, provided that the array includes at least three scale-levels.