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Detection–Localization Algorithms in the Around-the-Corner Radar Problem

机译:拐角雷达问题中的检测定位算法

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摘要

Detection and localization in urban environments is a very recent radar problem. In this paper, we investigate the possibility of detecting and locating targets not in direct line of sight (NLOS) areas with a single portable radar by exploiting multipath returns. We propose two algorithms, which handle the information provided by multipath returns in different ways to detect and estimate the NLOS target position. We also present an original method to select the number of paths to take into account in the algorithms in order to maximize detection probabilities. Numerical results show good efficiency of the proposed algorithms for problems of both detection and localization. We show that applying these algorithms improves detection performance compared to a classic matched filter in a typical urban scenario. Experimental results on a real dataset allow us to validate our multipath model in urban environments, and in particular to show that it is possible to retrieve the target location even with rough knowledge of the scene geometry.
机译:城市环境中的检测和本地化是最近的雷达问题。在本文中,我们通过利用多径返回来调查与单个便携式雷达的直接视线(NLOS)区域的检测和定位目标的可能性。我们提出了两个算法,该算法以不同的方式处理多路径返回的信息,以检测和估计NLOS目标位置。我们还提出了一种原始方法来选择在算法中考虑的路径数量,以最大化检测概率。数值结果显示了良好的检测和定位问题的算法。我们表明,与典型城市场景中的经典匹配过滤器相比,应用这些算法可以提高检测性能。实验结果在真实数据集上允许我们在城市环境中验证我们的多径模型,尤其表明也可以通过对场景几何形状的粗略知识来检索目标位置。

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