The authors propose a hybrid l-shapedarray composed of two sparse scalararrays and a single triangular spatially-spread electromagnetic-vector-sensor (SS-EMVS) for two-dimensional (2D) direction-of-arrival (DOA) est...
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The authors propose a hybrid l-shapedarray composed of two sparse scalararrays and a single triangular spatially-spread electromagnetic-vector-sensor (SS-EMVS) for two-dimensional (2D) direction-of-arrival (DOA) estimation. These two sparse but uniform scalararrays are placed along the x-axis and y-axis, respectively, which constitute two arms of the l-shapedarray. These two arms are connected by an SS-EMVS, which consists of a spatially-spread dipole-triad plus a spatially-spread loop-triad. Further, the inter-dipole/loop spacings of SS-EMVS follow a coprime relationship with the inter-sensor spacings of the l-shaped scalar array. In proposed DOA estimation algorithm, they first perform the vector-cross-product algorithm to SS-EMVS to obtain a high-accuracy but ambiguous direction cosine estimation;they then apply the ESPRIT algorithm to the scalararray on each arm to get another high-accuracy but cyclically ambiguous direction cosine estimation;finally, they adopt the Chinese Remainder Theorem to disambiguate the ambiguous estimations. Because the authors' proposed array has 2D array aperture extension, it can achieve a high angular estimation performance. Moreover, one component of triangular SS-EMVS rather than an SS-EMVS is used as the array unit of two scalararrays;thus, the whole array cost decreases dramatically. Simulation results validate the array configuration and the developed algorithm.
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