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A Joint Angle and Spectrum Estimation Algorithm for Uniform Linear Array
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DOI：10.1109/JSEN.2022.3188687.png)
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摘要
En 中文
The two-dimensional spectrum sensing that jointly acquires angular locations and frequency responses of multiple emitters is an important issue for cognitive radio. This paper presents a two-step algorithm to address this issue for the uniform linear array. In the coarse sensing step, we first apply fast Fourier transform to the mixed signal of each antenna. Then the mixed responses occupying the same frequency grid are collected from different antennas for roughly estimating spatial angles and the corresponding frequency magnitudes, where we resort to the harmonic analysis and explores spatial angles over the continuum. In the refined estimation step, the obtained angle-frequency data pairs are screened to eliminate false-alarm ones, based on which the spatial angles and the relevant spectrums are jointly regulated. Compared with the current works, the number of emitters is not a mandatory information for the proposed design, and it can be also well-suited to the correlated sources and the data-starving scenario. Numerical simulations demonstrate the merits of proposed algorithm, which can considerably improve the sensing accuracy with low computational burden.
Keyword:
Sensors
Estimation
Time-frequency analysis
Multiple signal classification
Cost function
Wideband
Time-domain analysis
Spectrum sensing
spatial angle estimation
uniform linear array (ULA)
Bayesian information criterion (BIC)
orthogonal matching pursuit
期刊
IF:
4.5
论文数:
2.2W
被引数:
7.3W
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Advances on Spectrum Sensing for Cognitive Radio Networks: Theory and Applications认知无线电网络频谱感知研究进展: 理论与应用
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