In this letter, a novel factor graph approach to target localization in distributed MIMO radars is proposed. To achieve robust localization in the presence of outliers, target localization can be formulated as a least absolute deviation (LAD) problem, which, however, is difficult to solve. We then reformulate the LAD problem as a reweighted least square (LS) one, which is converted to a product of some functions, enabling the use of factor graph techniques. Based on a factor graph representation, a highly efficient message passing algorithm is developed, where the target location is estimated in an iterative way. Comparisons with state-of-the-art methods show that the proposed method is superior in terms of computational complexity, robustness and accuracy.

中文翻译：

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存在异常值的分布式 MIMO 雷达中基于消息传递的鲁棒目标定位

在这封信中，提出了一种用于分布式 MIMO 雷达中目标定位的新型因子图方法。为了在存在异常值的情况下实现稳健的定位，可以将目标定位表述为最小绝对偏差 (LAD) 问题，但是这很难解决。然后，我们将 LAD 问题重新表述为重新加权的最小二乘 (LS) 问题，将其转换为某些函数的乘积，从而能够使用因子图技术。基于因子图表示，开发了一种高效的消息传递算法，其中以迭代方式估计目标位置。与最先进的方法的比较表明，所提出的方法在计算复杂度、鲁棒性和准确性方面具有优越性。