Adaptive Multi-Trace Carving Based on Dynamic Programming

Qiang Zhu, Mingliang Chen, Chau-Wai Wong, Min Wu

Abstract: In this paper, we study the problem of tracking multiple frequency components in a noisy signal using a spectrogram-based method. Previous approaches such as image processing based or hidden Markov model based methods may not be capable of tracking multiple frequency components, may require extensive training, and may be time-consuming. To address these issues, we propose an accurate and efficient method named Adaptive Multi-Trace Carving (AMTC) for tracking multiple frequency traces by iterative forward and backward dynamic programming and adaptive trace compensation. Experimental results reveal that the proposed method outperforms the state-of-the-art methods especially under low SNR conditions.