Complexity-Reduced MUSIC Using Bicubic Interpolation to ISAC in Near-Field Region

Thiago Augusto Bruza Alves, Taufik Abrão, José Carlos Marinello, David William Marques Guerra

DOI: 10.14209/sbrt.2025.1571156550

Evento: XLIII Simpósio Brasileiro de Telecomunicações e Processamento de Sinais (SBrT2025)

Keywords: ISAC Localization

Abstract

Integrated sensing and communication (ISAC) systems rely on accurate localization algorithms, commonly implemented via computationally demanding methods such as the multiple signal classification (MUSIC) algorithm. Typically, finegrid searches required by MUSIC lead to high computational complexity, posing practical limitations for real-time implementations. This paper introduces bicubic interpolation applied to coarse-grid MUSIC pseudo-spectra to significantly reduce complexity without sacrificing localization accuracy. The search grid is initially defined over a uniformly spaced Cartesian coordinate system and subsequently transformed into polar coordinates to enable accurate steering vector evaluation within the MUSIC algorithm. This formulation allows for the direct application of interpolation techniques to the resulting pseudo-spectrum. The simulation results demonstrate that the proposed interpolation strategy substantially decreases the computational load while maintaining competitive precision compared to traditional finegrid MUSIC methods. Performance evaluations in terms of root mean square error (RMSE), computational time and computational complexity analysis (flops) support the effectiveness and potential application of the proposed approach in future ISAC deployments.

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