Array error calibration methods in downward-looking linear-array three-dimensional synthetic aperture radar

Abstract

, "Array error calibration methods in downward-looking linear-array three-dimensional synthetic aperture radar," J. Appl. Remote Sens. 10(2), 025010 (2016), doi: 10.1117/1.JRS.10.025010. Abstract. In order to achieve high-precision three-dimensional (3-D) imaging with an airborne downward-looking linear-array 3-D synthetic aperture radar (LA-3D-SAR), a uniform virtual antenna array can be obtained by aperture synthesis of the cross-track sparse multiple-inputmultiple-output array. However, the actual 3-D imaging quality is unavoidably degraded by array errors such as the multichannel amplitude-phase errors due to the nonideal antenna characteristics, and the virtual element position errors due to vibrations and motion measurement deviations. We investigate the effects of these errors on the forms and the degrees of image quality degradation and consider the use of corresponding calibration methods to eliminate the effects of errors. For the multichannel amplitude-phase errors, the target response is subject to an integrated sidelobe level increase introduced by the phase error, which can be calibrated based on external (parallel or point target) calibrators, as proposed in the paper. For the virtual element position errors, they mainly the result of contrast degradation and noise in the image along the cross-track direction and have little impact on the range and along-track directions. The imaging performance is more sensitive to the error component in the height direction as compared to other components, the precision requirement of which should be established as the calibration reference. A calibration method based on time-divided active calibrators is proposed to estimate and correct the virtual element position errors. Both numerical simulations and real data experiments have shown the validity of the analyses as well as the effectiveness of the proposed calibration methods.

Matrix Completion-Based Channel Estimation for MmWave Communication Systems With Array-Inherent Impairments

“…The two dictionary matrices A r and A t are commonly constructed using array response vectors [3]. Vectorizing (11) leads to…”

“…The above CS scheme assumes the array response vector is known so that the channel can be modeled as (11), which is sparse on the basis built as (13). However, when phase errors and gain errors exist, it is the effective channel H eff rather than H to be estimated.…”

“…Conventional channel estimators, such as the least square (LS) estimator, demand a large number of training resources, which can be impractical for hybrid systems. In the meantime, adopting large-scale antenna array usually needs online calibration because of the array-inherent impairments due to mutual coupling, manufacture flaws, etc [10], [11], [12]. Such impairments are typically timevarying, e.g., due to temperature changes or hardware aging [12].…”

Downward-Looking Linear Array Three-Dimensional SAR Imaging Based on the Two-Dimensional Mismatch Compensation

“…To acquire the cross-track super-resolution with the uniform linear array, an imaging algorithm based on fast Fourier transform and multiple signal classification (MUSIC) is proposed, which transforms the cross-track imaging process into the problem of spectral estimation [16]. Moreover, a calibration method based on time-divided active calibrators is proposed to estimate and correct the virtual element position errors [17]. Besides the super-resolution imaging, it is an important problem to reduce the number of antenna elements on the linear array to simplify the hardware of DLLA 3-D SAR.…”

“…For DLLA 3-D SAR cross-track reconstruction, the measurement matrix is mainly determined by the configuration of the antenna phase centers and the grids discretization strategy of the imaging region, which means that the sparse signal must be represented on predefined discretized grids [16][17][20][21][22]. However, for a practical scene, the scatterers are scarcely located on the exact grids, which will cause the problem of basis mismatch [23][24].…”