A Multiscale Sparse Array of Spatially Spread Electromagnetic-Vector-Sensors for Direction Finding and Polarization Estimation

IEEE Access

卷:6

Minglei Yang¹  Baixiao Chen¹  Jin Ding²  Xin Yuan² 

[1] National Laboratory of Radar Signal Processing, Xidian University, Xi&x2019;

[2] an, China;

关键词: Sensor arrays;    direction-of-arrival (DOA) estimation;    polarization estimation;    direction finding;    sparse array;    nested array;   

DOI  :  10.1109/ACCESS.2018.2799905

来源: DOAJ

【 摘 要 】

In this paper, a multiscale sparse array, which is composed of spatially-spread electromagnetic-vector-sensors (SS-EMVSs), is proposed to estimate the direction-of-arrivals (DOA) and polarizations of multiple sources. The SS-EMVS is composed of three orthogonally oriented but spatially noncollocated dipoles to measure the electric field and three orthogonally oriented but spatially noncollocated loops to measure the magnetic field, simultaneously. In this paper, an array of SS-EMVSs is placed along the y-axis, and this sparse array is composed of two sub-arrays, i.e., the first n₁ SS-EMVSs with inter-sensor spacing D₁, and the last n2 SS-EMVSs with inter-sensor spacing D₂, with D₂ = mD1; m ₁ is an integer and D₁ is larger than a half-wavelength of the incident signal. Thereby, a multiscale sparse array is constructed, which is capable of providing high accuracy estimates of DOA and polarizations of multiple sources. The vector-cross-product algorithm is used to obtain the unambiguous but low-accuracy estimations of direction cosines, and the different inter-sensor spacings are used to estimate high-accuracy but ambiguous estimations of direction cosines. Following this, a multiscale disambiguation algorithm is developed to obtain highaccuracy and unambiguous estimations of direction cosines, thus the elevation angles, azimuth angles, as well as the polarization parameters of multiple sources. Simulation results verify the superior performance of the proposed multiscale SS-EMVS array.

【 授权许可】

Unknown