An Approach to Adaptive Transient Detection
نویسنده
چکیده
This paper describes a detection method that adapts to unknown characteristics of the underlying transient signal, such as location, length, and time-frequency content. It applies a set of embedded detectors tuned to a number of signal partitions. The detectors are based on the general wavelet theory whereby two different techniques are examined, (1) the local Fourier transform (LFT) and (2) the discrete wavelet transform (DWT). The detection statistics are computed so as to enable prewhitening of unknown coloured noise and to allow for a constant false-alarm rate (CFAR) detection. An adapted segmentation of the signal is next obtained with a goal of finding the largest detection statistics within each segment of the partition. The detectors are tested using several underwater acoustic transient signals buried in ambient sea noise.
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