Automatic Detection of the Number of Raypaths in a Shallow-Water Waveguide

Correct identification and tracking of stable raypaths are critical for shallow-water acoustic tomog-raphy. According, separating raypaths using high resolution methods is presented to improve resolution ability based on the prior knowledge of the number of raypaths. It is clear that the precise knowledge of the number of raypaths largely determines the separation performance. Therefore, a noise-whitening exponential fitting test (NWEFT) using short-length samples is proposed in this paper to automatically detect the number of raypaths in a shallow-water waveguide. Two information theoretic criteria are introduced as comparative methods. Their performances are tested with simulation data and real data obtained at small scale. The experimental results show that the noise-whitening exponential fitting test can provide satisfactory detection compared to the two classic information theoretic criteria — the Akaike information criterion (AIC) and the minimum description length (MDL). Referring to the performance of AIC and MDL, MDL is asymptotically consistent while AIC overestimates even if analyzed asymptotically