Radar Angle-of-Arrival Estimation

AbstractIn the context of this research work, we study the so-called problem of full snapshot reconstruction in hybrid antenna array structures that are utilized in mmWave communication systems. It enables the recovery of the snapshots that would have been obtained if a conventional (non-hybrid) uniform linear antenna array was employed. The problem is considered at the receiver side where the hybrid architecture exploits in a novel way the antenna elements of a uniform linear array. To this end, the recommended scheme is properly designed so as to be applicable to overlapping and non-overlapping architectures. Moreover, the full snapshot recoverability is addressed for two cases, namely for time-varying and constant signal sources. Simulation results are also presented to illustrate the consistency between the theoretically predicted behaviors and the simulated results, and the performance of the proposed scheme in terms angle-of-arrival estimation, when compared to the conventional MUSIC algorithm and a recently proposed hybrid version of MUSIC (H-MUSIC).

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Towards Robust Multiple Blind Source Localization Using Source Separation and Beamforming

Sensors ◽

10.3390/s21020532 ◽

2021 ◽

Vol 21 (2) ◽

pp. 532

Author(s):

Henglin Pu ◽

Chao Cai ◽

Menglan Hu ◽

Tianping Deng ◽

Rong Zheng ◽

...

Keyword(s):

Source Localization ◽

Sound Source ◽

Indoor Localization ◽

Weighting Function ◽

Signal To Noise Ratio ◽

Source Separation ◽

Sound Source Localization ◽

Angle Of Arrival ◽

Sound Sources ◽

Localization Algorithms

Multiple blind sound source localization is the key technology for a myriad of applications such as robotic navigation and indoor localization. However, existing solutions can only locate a few sound sources simultaneously due to the limitation imposed by the number of microphones in an array. To this end, this paper proposes a novel multiple blind sound source localization algorithms using Source seParation and BeamForming (SPBF). Our algorithm overcomes the limitations of existing solutions and can locate more blind sources than the number of microphones in an array. Specifically, we propose a novel microphone layout, enabling salient multiple source separation while still preserving their arrival time information. After then, we perform source localization via beamforming using each demixed source. Such a design allows minimizing mutual interference from different sound sources, thereby enabling finer AoA estimation. To further enhance localization performance, we design a new spectral weighting function that can enhance the signal-to-noise-ratio, allowing a relatively narrow beam and thus finer angle of arrival estimation. Simulation experiments under typical indoor situations demonstrate a maximum of only 4∘ even under up to 14 sources.

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