Imaging of a compact range using autoregressive spectral estimation

E. Walton, A. Moghaddar
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引用次数: 5

Abstract

An estimation technique based on the autoregressive (AR) modeling of field probe data is used to locate and quantify spurious signals in a compact range. In this technique, the probe aperture is divided into a number of overlapping subapertures such that the far-field criterion for each subaperture is satisfied. Then the subaperture data are modeled as an AR process, and the AR parameters are derived using the principal component forward-backward linear prediction technique. Directions of the incident signals relative to each subaperture are then determined from the poles of the prediction filters. Using a series of subapertures, the locations of the scatterers are estimated by triangulation. After estimation of the spatial frequencies of the probe data for any subaperture, the magnitude of each component is determined by a least squares algorithm. Examples of probe measurements and analysis for the Ohio State University compact range are given.<>
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使用自回归光谱估计的紧凑范围成像
采用基于自回归(AR)建模的现场探测数据估计技术对小范围内的杂散信号进行定位和量化。在该技术中,探头孔径被划分为多个重叠的子孔径,从而满足每个子孔径的远场准则。然后将子孔径数据建模为AR过程,利用主成分正反向线性预测技术推导AR参数。然后从预测滤波器的极点确定入射信号相对于每个子孔径的方向。利用一系列的子孔径,通过三角测量估计散射体的位置。在对任意子孔径的探测数据的空间频率进行估计后,通过最小二乘算法确定每个分量的大小。给出了俄亥俄州立大学紧凑型量程的探头测量和分析实例。
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