Coprime beamforming: fast estimation of more sources than sensors. Issue 11 (1st November 2019)

• Record Type: Journal Article
• Authors: Baxter, William; Nosrati, Hamed; Aboutanios, Elias
• Is Part Of: IET radar, sonar & navigation. Volume 13:Issue 11(2019)
• Page Start: 1956
• Page End: 1962
• Publication Date: 2019-11-01
• Subjects: iterative methods -- fast Fourier transforms -- interpolation -- array signal processing -- computational complexity -- direction‐of‐arrival estimation; coprime beamforming -- fast estimation -- sensing array -- significant hardware computational savings -- coprime‐pair configuration -- degrees of freedom -- virtual array -- VA -- subspace‐based algorithms -- DOA -- subspace techniques -- spatial smoothing -- fast iterative interpolated beamformer -- FIIB -- computational complexity -- single estimate -- lag estimates -- estimation performance -- source separation -- high‐fidelity frequency estimates -- high‐resolution subspace‐based methods -- computational cost -- fast Fourier transform; Signal processing -- Periodicals; Radar -- Periodicals; Sonar -- Periodicals; Electronics in navigation -- Periodicals; Navigation -- Periodicals; 621.3848
• DOI: 10.1049/iet-rsn.2018.5647
• Languages: English
• ISSNs: 1751-8784

Abstract

Abstract : In radar, the minimisation of redundancies within the sensing array can lead to significant hardware computational savings. Arrays with a coprime‐pair configuration enjoy increased degrees of freedom and can detect more sources than sensors. To achieve this, a virtual array (VA) consisting of the full complement of lags is usually constructed and subspace‐based algorithms are then employed to obtain the direction‐of‐arrival (DOA) or frequency estimates. However, the application of the subspace techniques to the VA incurs a significant computational cost and requires spatial smoothing. The authors propose and analyse the application of the fast iterative interpolated beamformer (FIIB) to the coprime DOA estimation problem. The FIIB enjoys a computational complexity of the same order as the fast Fourier transform and does not require spatial smoothing. They consider two implementations that construct the VA differently with the first selecting a single estimate for each lag and the other employing averaged values of the lag estimates. They present a comprehensive study of the estimation performance as a function of signal‐to‐noise ratio, number of snapshots and source separation. The results clearly show that the FIIB delivers high‐fidelity frequency estimates that consistently outperform the high‐resolution subspace‐based methods.