In this work, 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.

Download and view the paper in IEEE Xplore:
https://doi.org/10.1109/ACSSC.2018.8645216

Download and view the paper in ResearchGate:
https://www.researchgate.net/publication/330761858_ADAPTIVE_MULTI-TRACE_...