A real-time design of an acoustic signal detection algorithm using the AT&T DSP32 development system

Presents a real-time signal processing system which incorporates a pattern recognition system for detecting narrowband and broadband signals in the presence of noise. The system-based on the AT&T Bell Laboratories DSP32 microprocessor-detects and classifies signals by extracting parameters of the power spectrum. From the extracted shape description, decisions are made on the presence/no presence of narrowband and broadband signals. The system can either detect signals from user defined parameters or from a time sequence sample of the desired sequence. The system was tested on real data 0-4 kHz. Using unshaped and shaped white noise the system successfully detected narrowband signals down to -28 dB SNR (broadband noise dominate) and -32 dB SNR (narrowband noise dominate) respectively