TY - GEN
T1 - Spatio-Temporal Reverberation Suppression Method Based on Itakura Distance Segmental Pre-Whitening and Progressive Adaptive Binary SVD
AU - Cao, Yuan
AU - Zhang, Qunfei
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - In underwater acoustic signal processing, the overlapping presence of reverberation and target echoes within the time-frequency domain poses formidable challenges for target detection in active detection scenarios conducted from moving platforms. Responding to the demand for low Signal to Reverberation Ratio(SRR) in echo detection, this paper proposes a novel approach based on Itakura distance segmental pre-whitening technique and progressive adaptive binary Singular Value Decomposition (SVD) strategy, which effectively suppresses reverberation and significantly improves echo detection performance. Leveraging Itakura distance as a metric, the method evaluates and adjusts the pre-whitening process of autoregressive models, rendering it suitable for diverse reverberation environments. Furthermore, the progressive adaptive binary SVD refines signal characteristics by adapting decomposition paths to match signal properties, thus achieving efficient signal separation and target detection. Simulation experiments, incorporating factors such as multipath propagation and platform motion, validate the efficacy of the proposed method, demonstrating a 10dB increase in SRR.
AB - In underwater acoustic signal processing, the overlapping presence of reverberation and target echoes within the time-frequency domain poses formidable challenges for target detection in active detection scenarios conducted from moving platforms. Responding to the demand for low Signal to Reverberation Ratio(SRR) in echo detection, this paper proposes a novel approach based on Itakura distance segmental pre-whitening technique and progressive adaptive binary Singular Value Decomposition (SVD) strategy, which effectively suppresses reverberation and significantly improves echo detection performance. Leveraging Itakura distance as a metric, the method evaluates and adjusts the pre-whitening process of autoregressive models, rendering it suitable for diverse reverberation environments. Furthermore, the progressive adaptive binary SVD refines signal characteristics by adapting decomposition paths to match signal properties, thus achieving efficient signal separation and target detection. Simulation experiments, incorporating factors such as multipath propagation and platform motion, validate the efficacy of the proposed method, demonstrating a 10dB increase in SRR.
KW - Adaptive processing
KW - Itakura distance
KW - Pre-whitening
KW - Reverberation Suppression
KW - SRR
KW - SVD
UR - http://www.scopus.com/inward/record.url?scp=85214912589&partnerID=8YFLogxK
U2 - 10.1109/ICSPCC62635.2024.10770414
DO - 10.1109/ICSPCC62635.2024.10770414
M3 - 会议稿件
AN - SCOPUS:85214912589
T3 - 2024 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2024
BT - 2024 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 14th IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2024
Y2 - 19 August 2024 through 22 August 2024
ER -