{"ID":2832363,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2512.05355","arxiv_id":"2512.05355","title":"Noise Suppression for Time Difference of Arrival: Performance Evaluation of a Generalized Cross-Correlation Method Using Mean Signal and Inverse Filter","abstract":"This paper proposes a novel generalized cross-correlation (GCC) method, termed GCC-MSIF, to improve time difference of arrival (TDOA) estimation accuracy in noisy environments. Conventional GCC methods often suffer from performance degradation under low signal-to-noise ratio (SNR) conditions, particularly when the signal bandwidth is unknown. GCC-MSIF introduces a \"mean signal\" estimated from multi-channel inputs and an \"inverse filter\" to virtually reconstruct the source signal, enabling adaptive suppression of out-of-band noise. Numerical simulations simulating a small-scale array demonstrate that GCC-MSIF significantly outperforms conventional methods, such as GCC-PHAT and GCC-SCOT, in low SNR regions and achieves robustness comparable to or exceeding the maximum likelihood (GCC-ML) method. Furthermore, the estimation accuracy improves scalably with the number of array elements. These results suggest that GCC-MSIF is a promising solution for robust passive localization in practical blind environments.","short_abstract":"This paper proposes a novel generalized cross-correlation (GCC) method, termed GCC-MSIF, to improve time difference of arrival (TDOA) estimation accuracy in noisy environments. Conventional GCC methods often suffer from performance degradation under low signal-to-noise ratio (SNR) conditions, particularly when the sign...","url_abs":"https://arxiv.org/abs/2512.05355","url_pdf":"https://arxiv.org/pdf/2512.05355v1","authors":"[\"Hirotaka Obo\",\"Yuki Fujita\",\"Masahisa Ishii\",\"Hideki Moriyama\",\"Ryota Tsuchiya\",\"Yuta Ohashi\",\"Kotaro Seki\"]","published":"2025-12-05T01:45:46Z","proceeding":"eess.SP","tasks":"[\"eess.SP\",\"eess.AS\"]","methods":"[]","has_code":false}