DOAJ Open Access 2025

Evaluating Gaussian processes for matched-field processing localization using minimum mean squared error criterion

Shanru Lin Haiqiang Niu Peter Gerstoft Zhenglin Li Yonggang Guo

Lihat Sumber DOI

Abstrak

Gaussian processes (GPs) can densify and denoise sparsely sampled signals and have been applied in matched-field processing (MFP) localization to improve localization accuracy and robustness. Given a known true field, the minimum mean squared error criterion is proposed to evaluate the performance of GP interpolation and its application in MFP localization. This approach allows for the performance comparison of different kernel functions and likelihood functions, assisting in identifying the optimal hyperparameters, interpolation results, and localization outcomes. It also highlights possible challenges faced by existing GP methods under limited data conditions while establishing a performance upper bound for GPs-MFP.

Topik & Kata Kunci

Acoustics. Sound

Penulis (5)

Shanru Lin

Haiqiang Niu

Peter Gerstoft

Zhenglin Li

Yonggang Guo

Format Sitasi

APA MLA BibTeX

Lin, S., Niu, H., Gerstoft, P., Li, Z., Guo, Y. (2025). Evaluating Gaussian processes for matched-field processing localization using minimum mean squared error criterion. https://doi.org/10.1121/10.0041792

Akses Cepat

Lihat di Sumber doi.org/10.1121/10.0041792

Informasi Jurnal

Tahun Terbit: 2025
Sumber Database: DOAJ
DOI: 10.1121/10.0041792
Akses: Open Access ✓