On the Performance of One-Bit DoA Estimation via Sparse Linear Arrays
Saeid Sedighi, M. R. Bhavani Shankar, Mojtaba Soltanalian, Bj\"orn, Ottersten

TL;DR
This paper explores the limits and proposes a new algorithm for direction of arrival estimation using one-bit measurements from sparse linear arrays, demonstrating improved performance over existing methods through theoretical analysis and simulations.
Contribution
It establishes identifiability conditions, derives a performance benchmark via a pessimistic CRB, and introduces a novel DoA estimation algorithm for one-bit SLA data.
Findings
The proposed algorithm outperforms existing methods in simulations.
A new performance benchmark for one-bit DoA estimation is established.
Identifiability conditions are linked to unquantized measurement cases.
Abstract
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…
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