Efficient 3-dimensional imaging algorithm using PI extraction based RPM for quasi-far field UWB radars

S. Kidera, T. Kirimoto
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Abstract

Ultra-wide band (UWB) pulse radar has a definite advantage over optical ranging techniques in harsh optical environments, such as a dark smog or strong backlight. In security or rescue situations with blurry visibility, it is particularly promising for identifying human bodies. One of the most promising approaches for this type of application is the recently proposed range points migration (RPM) method, which is beneficial for non-parametric imaging and is robust in noisy or heavily interference situations. However, the original RPM requires a discretization of the direction of arrival (DOA) variables in its search operation. The resulting coarse discretization seriously degrades the imaging accuracy, particularly for 3-dimensional problems and quasi-far field observations (defined as more than 5 wavelengths). Then, in this approach, there is a severe trade-off between the amount of computation and accuracy. To overcome this difficulty, this paper proposes a more efficient RPM algorithm, where the extraction of the point of intersection (PI) of spheres is adopted. A distinct advantage of this method is that the accuracy is basically invariant to the observation range when avoiding the above discretization. Numerical simulations prove that our proposed RPM remarkably reduces the computation complexity while retaining imaging accuracy.
基于PI提取的准远场超宽带雷达快速三维成像算法
超宽带(UWB)脉冲雷达在恶劣的光学环境(如黑暗烟雾或强背光)中比光学测距技术具有明显的优势。在能见度模糊的安全或救援情况下,它特别有希望用于识别人体。这类应用中最有前途的方法之一是最近提出的距离点迁移(RPM)方法,该方法有利于非参数成像,并且在噪声或严重干扰的情况下具有鲁棒性。然而,原始RPM在其搜索操作中需要对到达方向(DOA)变量进行离散化。由此产生的粗离散化严重降低了成像精度,特别是对于三维问题和准远场观测(定义为超过5个波长)。然后,在这种方法中,在计算量和准确性之间存在严重的权衡。为了克服这一困难,本文提出了一种更有效的RPM算法,该算法采用球体交点的提取。该方法的一个明显优点是,在避免上述离散化的情况下,精度与观测范围基本不变。数值模拟结果表明,该方法在保持成像精度的同时显著降低了计算复杂度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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