DoA Estimation for Hybrid Receivers: Full Spatial Coverage and Successive Refinement

IF 4.6 2区 工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC IEEE Transactions on Signal Processing Pub Date : 2024-09-12 DOI:10.1109/TSP.2024.3459422
Ali Abdelbadie;Mona Mostafa;Salime Bameri;Ramy H. Gohary;Dimple Thomas
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Abstract

We develop two novel algorithms for estimating the direction of arrival (DoA) of multiple sources in fully-connected and partially-connected hybrid analog/digital (HAD) receivers. The first algorithm is based on the observation that the analog combiner projects received signals on a particular subspace, causing the signals corresponding to particular DoAs to be heavily attenuated. Thus, an analog combiner defines spatial sectors, beyond which the DoAs are practically undetectable. To address this difficulty, we perform DoA estimation over an exhaustive set of analog combiners spanning distinct subspaces. To refine the estimates generated by this algorithm, we develop an exponentially-converging algorithm wherein the search window is successively narrowed until convergence. Cramér-Rao lower bounds on the root-mean-square error of the proposed algorithms are derived and the superiority of these algorithms over their existing counterparts is established through numerical simulations.
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混合接收器的 DoA 估算:全空间覆盖和连续细化
我们开发了两种新算法,用于估计全连接和部分连接模拟/数字混合(HAD)接收器中多个信号源的到达方向(DoA)。第一种算法基于以下观察结果:模拟合路器将接收到的信号投射到一个特定的子空间,导致与特定到达方向相对应的信号被严重衰减。因此,模拟合路器定义了空间扇区,超出该扇区的 DoAs 几乎无法检测。为了解决这一难题,我们在一组跨越不同子空间的详尽模拟合路器上执行 DoA 估计。为了完善该算法生成的估计值,我们开发了一种指数收敛算法,在该算法中,搜索窗口连续缩小,直至收敛。我们推导出了所提算法均方根误差的克拉梅尔-拉奥(Cramér-Rao)下限,并通过数值模拟证明了这些算法优于现有算法。
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来源期刊
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing 工程技术-工程:电子与电气
CiteScore
11.20
自引率
9.30%
发文量
310
审稿时长
3.0 months
期刊介绍: The IEEE Transactions on Signal Processing covers novel theory, algorithms, performance analyses and applications of techniques for the processing, understanding, learning, retrieval, mining, and extraction of information from signals. The term “signal” includes, among others, audio, video, speech, image, communication, geophysical, sonar, radar, medical and musical signals. Examples of topics of interest include, but are not limited to, information processing and the theory and application of filtering, coding, transmitting, estimating, detecting, analyzing, recognizing, synthesizing, recording, and reproducing signals.
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