Abstract
Antenna array calibration methods and narrowband direction finding (DF) techniques will be outlined and compared for a uniform circular array. DF is stated as an inverse problem, which solution requires a parametric model of the array itself. Because real arrays suffer from mechanical and electrical imperfections, analytic array models are per se not applicable. Mitigation of such disturbances by a global calibration matrix will be addressed, and methods to estimate this calibration matrix will be recapped from literature. Also, a novel method will be presented, which circumvents the problem of a changed noise statistic due to calibration. Furthermore, local calibration, where array calibration measurements are incorporated in the DF algorithm, is considered as well. Common DF algorithms will be outlined, their assumptions regarding array properties will be addressed, and required preprocessing steps such as the beam-space transformation will be presented. Also, two novel DF techniques will be proposed, based on the Capon beamformer, but with reduced computational effort and higher resolution for bearing estimation. Simulations are used to exemplary compare calibration and DF methods in conjunction with each other. Furthermore, measurements with a single and two coherent sources are considered. It turns out that global calibration enables computational efficient DF algorithms but causes biased estimates. Furthermore, resolution of two coherent sources necessitates array calibration.
Highlights
Direction finding (DF) is a task which occurs in several applications of surveillance, reconnaissance, radar, or sonar
Theoretical array models typically assume omnidirectional sensors and an ideal array geometry, which cannot be assured for real arrays
The goal of this paper is to jointly investigate array calibration methods and narrowband direction finding (DF) techniques
Summary
Direction finding (DF) is a task which occurs in several applications of surveillance, reconnaissance, radar, or sonar. Solving the inverse problem requires a parametric model of the array output in terms of the parameters of interest: azimuth of arrival (AoA) φ and elevation of arrival (EoA) θ, which together define the direction of arrival (DoA). Theoretical array models typically assume omnidirectional sensors and an ideal array geometry, which cannot be assured for real arrays. Apart from these assumptions, real arrays suffer from disturbances as, e.g., mutual coupling between the sensors or the support structure of the array, unknown sensor gain, and phase or mechanical imperfections [1]. DoA estimation performance degrades, because the assumed array model does not coincide with the real array characteristics.
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