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Closed-form Inverses for the Mixed Pixel/Multipath Interference Problem in AMCW Lidar

机译:AMCW激光雷达中混合像素/多径干扰问题的闭式逆

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We present two new closed-form methods for mixed pixel/multipath interference separation in AMCW lidar systems. The mixed pixel/multipath interference problem arises from the violation of a standard range-imaging assumption that each pixel integrates over only a single, discrete backscattering source. While a numerical inversion method has previously been proposed, no close-form inverses have previously been posited. The first new method models reflectivity as a Cauchy distribution over range and uses four measurements at different modulation frequencies to determine the amplitude, phase and reflectivity distribution of up to two component-returns within each pixel. The second new method uses attenuation ratios to determine the amplitude and phase of up to two component returns within each pixel. The methods are tested on both simulated and real data and shown to produce a significant improvement in overall error. While this paper focusses on the AMCW mixed pixel/multipath interference problem, the algorithms contained herein have applicability to the reconstruction of a sparse one dimensional signal from an extremely limited number of discrete samples of its Fourier transform.
机译:我们提出了两种用于AMCW激光雷达系统中混合像素/多径干扰分离的闭合形式新方法。混合像素/多径干扰问题是由于违反了标准范围成像假设而产生的,即每个像素仅在单个离散的反向散射源上积分。尽管先前已经提出了一种数值反演方法,但是之前没有提出任何封闭形式的反演。第一种新方法将反射率建模为整个范围内的柯西分布,并在不同的调制频率下使用四个测量值来确定每个像素内最多两个分量返回的幅度,相位和反射率分布。第二种新方法使用衰减率来确定每个像素内最多两个分量返回的幅度和相位。这些方法在模拟数据和真实数据上均经过测试,结果表明可显着改善总体误差。尽管本文着重于AMCW混合像素/多径干扰问题,但此处包含的算法适用于从数量极少的傅立叶变换离散样本重建稀疏的一维信号。

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