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Simulation Of Vessel Broadband Signatures For Sonar System Training

A sea-going vessel emits characteristic signals as it operates, commonly called its signature. This paper presents two methods for simulating the broadband component of a vessel's signature. One method consists of a Pseudo-Random Number (PRN) generator producing inputs to a digital shaping filter. Three DSP techniques are examined for the digital shaping filter: frequency sampling, IIR filter bank, and linear prediction. Results indicate that frequency sampling is the best approach in systems where the coefficients are calculated in real-time while linear prediction is more efficient in cases where coefficients are pre-calculated and stored. The second method examined is an Inverse Fast Fourier Transform (IFFT) approach. The difficulties encountered due to large sample size requirements are discussed. In general, the first method appears to offer adequate modeling for considerably less computational complexity.