Angular Parameter Estimation for Incoherently Distributed Sources With Single RF Chain

IF 4.6 2区 工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
Ziyu Guo;Tao Yang;Peng Chen;Jun Han;Xiaoyang Zeng;Bo Hu
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Abstract

In this paper, we consider the problem of estimating the angular parameters, i.e., the nominal angle-of-arrivals (AoAs) and angular spreads, of incoherently distributed sources using the phased-array equipped with a single RF chain. We first derive the approximate Fourier series of the received power. The coefficients can be expressed in closed form with the angular parameters. In the case of single source, this finding directly suggests the design of the low-complexity algorithm that performs spatial sampling and discrete Fourier transform to estimate the Fourier series coefficients, from which the nominal AoA and angular spread can be obtained successively. In the case of multiple sources, we focus on one source at one time, and the multiples sources are handled one by one. Based on the Fourier series expression, the power fitting approach is proposed to build the nonlinear least-squares problem. Then, the semi-exhaustive search algorithm is developed to find the solution, which gives the angular parameters of the target source. Additionally, the approximate Cramer-Rao bound is derived as benchmark. The numerical results demonstrate that in certain cases, the proposed methods can even outperform the existing method that uses fully-digital array.
使用单射频链的非相干分布源的角度参数估计
在本文中,我们考虑的问题是利用配备单射频链的相控阵估计非相干分布源的角度参数,即标称到达角(AoAs)和角度展宽。我们首先推导出接收功率的近似傅里叶级数。系数可以用角度参数的封闭形式表示。在单源情况下,这一发现直接建议设计低复杂度算法,通过空间采样和离散傅里叶变换来估算傅里叶级数系数,并由此连续获得标称视距和角展宽。在有多个信号源的情况下,我们一次只关注一个信号源,多个信号源则逐一处理。根据傅里叶级数表达式,提出了功率拟合方法来建立非线性最小二乘问题。然后,通过半穷举搜索算法求解,给出目标源的角度参数。此外,还得出了近似 Cramer-Rao 约束作为基准。数值结果表明,在某些情况下,所提出的方法甚至优于使用全数字阵列的现有方法。
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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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