一种系统框架，用于测试三重冗余稀疏阵列对两个传感器故障的鲁棒性及若干前所未有的发现
A Systematic Framework to Identify Hidden Vulnerabilities in Three-Fold Redundant Sparse Arrays Under Dual Sensor Failures
AI总结：
本文提出系统框架评估三重冗余稀疏线性阵列对两个传感器故障的鲁棒性，发现现有阵列存在隐藏脆弱性，并提供MATLAB程序供社区使用。
摘要：
随着稀疏阵列领域的发展，人们提出了众多阵列设计，重点关注更大的孔径和更高的自由度（DOFs），从而产生了最大经济型稀疏阵列（MESAs），这些阵列以最少的传感器数量提供给定孔径，同时确保无孔洞差分共阵列（DCA）。因此，MESAs对传感器故障的鲁棒性最差，甚至无法承受单个传感器的故障。多重冗余稀疏阵列（MFRSAs）通过确保阵列包含足够的传感器对以多次产生每个空间滞后，为稀疏阵列中的传感器故障问题提供了实用解决方案。凭借这一特性，β重冗余阵列能够承受至少β-1个传感器同时故障，而不会失去无孔洞DCA特性。然而，MFRSAs也容易受到隐藏依赖关系的影响，这些依赖关系阻碍其完全鲁棒。在本工作中，我们提出了一个系统框架，用于评估三重冗余稀疏线性阵列（TRSLAs）对所有可能的两个传感器故障的鲁棒性。在详细阐述所提方法后，我们展示了现有文献中代表性TRSLAs的故障分析。研究发现，现有TRSLAs在应对某些特殊传感器对故障时存在隐藏的脆弱性。我们提供了相应的MATLAB程序和数值模拟，供阵列处理社区评估和使用。所提方法具有重要的存档价值，因为它可以通过客观手段评估任何现有或未来TRSLAs的鲁棒性。
英文摘要：
As the field of sparse arrays progressed, numerous array designs have been introduced with a focus on larger apertures and higher degrees of freedom (DOFs), resulting in maximally economic sparse arrays (MESAs) that operate with the least number of sensors required to provide a given aperture while ensuring a hole-free difference coarray (DCA). Consequently, MESAs are least robust to sensor failures and cannot afford the failure of even a single sensor. Multifold redundant sparse arrays (MFRSAs) provide a practical solution to the problem of sensor failures in sparse arrays by making sure that the array contains enough sensor pairs necessary to produce each spatial lag multiple times. Owing to this property, a \b{eta}-fold redundant array can withstand simultaneous failure of at least \b{eta}-1 sensors without losing the hole-free DCA property. Nevertheless, MFRSAs are also prone to hidden dependencies that prevent them from being fully robust. In this work, we present a systematic framework to evaluate the robustness of triple redundant sparse linear arrays (TRSLAs) against all possible two-sensor failures. After detailing the proposed approach, we present the failure analysis of representative TRSLAs available in existing literature. It is found that existing TRSLAs have some hidden vulnerabilities against the failure of some peculiar sensor pairs. Corresponding MATLAB programs and numerical simulations are provided for evaluation and use by the array processing community. The proposed approach has a great archival value as it can evaluate the robustness of any present or future TRSLAs through objective means.
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