标题： 一种基于成功跳跃的穷举搜索方法以寻找最优鲁棒最小冗余阵列（RMRAs）：传感器数量11到20的新阵列配置 显示英文标题

标题： A Leap-on-Success Exhaustive Search Method to Find Optimal Robust Minimum Redundancy Arrays (RMRAs): New Array Configurations for Sensor Counts 11 to 20

摘要： 双重冗余稀疏阵列（TFRAs）旨在即使在单个传感器故障的情况下也能保持精确的方向估计，利用设计中注入的有意共阵列冗余。鲁棒最小冗余阵列（RMRAs）是TFRAs的一个专门类别，通过优化这种冗余，以给定的传感器数量实现最大的可能孔径。然而，寻找最优的RMRA配置是一个NP难问题，先前的研究仅报告了最多十个传感器阵列的最优解。本文提出了11到15尺寸阵列的新发现的最优RMRA配置，这些配置是使用一种新颖的“成功跳跃”穷举搜索算法找到的，该算法通过在找到最优解时终止搜索来有效减少计算工作量。这些阵列在所有单元素故障场景下通过MATLAB仿真进行了验证，证实了它们相比一些在特定传感器位置易受故障影响的现有TFRAs具有优越的鲁棒性。此外，还报告了16到20尺寸阵列的近最优配置，突显了所提出方法在足够计算资源条件下对于更大阵列设计的潜在适用性。这项工作不仅推进了RMRA设计的最先进技术，还引入了一种有效的搜索方法，可用于未来阵列配置优化的探索。 显示英文摘要

摘要： Two-fold redundant sparse arrays (TFRAs) are designed to maintain accurate direction estimation even in the event of a single sensor failure, leveraging the deliberate coarray redundancy infused into their design. Robust Minimum Redundancy Arrays (RMRAs), a specialized class of TFRAs, optimize this redundancy to achieve the maximum possible aperture for a given number of sensors. However, finding optimal RMRA configurations is an NP-hard problem, with prior research reporting optimal solutions only for arrays of up to ten sensors. This paper presents newly discovered optimal RMRA configurations for array sizes 11 to 15, identified using a novel Leap-on-Success exhaustive search algorithm that efficiently reduces computational effort by terminating the search upon locating optimal solutions. The robustness of these arrays was validated under all single-element failure scenarios using MATLAB simulations, confirming their superior resilience compared to some existing TFRAs vulnerable to failures at specific sensor positions. Furthermore, near-optimal configurations for array sizes 16 to 20 are also reported, highlighting the potential applicability of the proposed method for larger array designs given sufficient computational resources. This work not only advances the state-of-the-art in RMRA design but also introduces an effective search methodology that can be leveraged for future explorations in array configuration optimization.