Direction of Arrival (DoA) estimation using Sparse Linear Arrays (SLAs) has recently gained considerable attention in array processing thanks to their capability to provide enhanced degrees of freedom in resolving uncorrelated source signals. Additionally, deployment of one-bit Analog-to-Digital Converters (ADCs) has emerged as an important topic in array processing, as it offers both a low-cost and a low-complexity implementation. In this paper, we study the problem of DoA estimation from one-bit measurements received by an SLA. Specifically, we first investigate the identifiability conditions for the DoA estimation problem from one-bit SLA data and establish an equivalency with the case when DoAs are estimated from infinite-bit unquantized measurements. Towards determining the performance limits of DoA estimation from one-bit quantized data, we derive a pessimistic approximation of the corresponding Cram\'{e}r-Rao Bound (CRB). This pessimistic CRB is then used as a benchmark for assessing the performance of one-bit DoA estimators. We also propose a new algorithm for estimating DoAs from one-bit quantized data. We investigate the analytical performance of the proposed method through deriving a closed-form expression for the covariance matrix of the asymptotic distribution of the DoA estimation errors and show that it outperforms the existing algorithms in the literature. Numerical simulations are provided to validate the analytical derivations and corroborate the resulting performance improvement.

翻译：使用 Sprassy 线性线性线性阵列( SLAs) 的抵达方向估计最近在阵列处理中引起了相当的注意,因为它们有能力提供更高程度的自由以解决与非气候相关的源信号。此外,在阵列处理中,部署单位对数字转换器(ADCs)已成为一个重要的主题,因为它既提供了低成本,也提供了低度的复合性实施。在本文件中,我们从一个SLA收到的一比位测量中研究了 DoA估计问题。具体地说,我们首先从一比的SLA数据中调查DoA估计问题可识别性条件,并在DoAs从无穷度的未分化测量中估算出一个类似的情况。我们从一个位数的量化数据估算中得出一个悲观的近似值,而现在的Cram\ {r-r-Rao Bound (CRB) 则是用于评估单位分析性分析性平面性分析性能的新的基准。我们从一个比位的 DoA 平面性分析算法中提出了通过一个演示式的模拟模拟模拟模拟模拟的模拟。