Multiple Peak Count Analysis, a Spectral Resolution Enhancement Method Using A-priori Information

In applications for acoustic Doppler profiling, the back scattering signal from small entrained water bubbles and other particles is used to predict the volume velocity. The velocity vector is calculated using multiple beams, pointing in different directions. By analyzing the Doppler frequency variation in the backscattering signal, it is possible to calculate the mean vector current versus depth. Turbulence in the water can create simultaneous currents and the water current my be different on the other side of salinity or temperature layers. These multiple current phenomenon has been difficult to analyze. The transmitted pulse is very short, and the volume where the current should be estimated is typically small. By using a non-linear filtering method based on a-priori information, the so called Multiple Peak Count Analysis, these current effects can become visible. The method shows superior performance as compared to classical methods, presenting a 3-dimensional spectral plots of the data often by using an FFT. A non-linear pre-filtering method has been developed where the peaks are extracted in the data. A short-time FFT has been used to find the spectral content. The paper describes this new method and compares the result with a classical analysis. Advantages with this new method, and suggestions where the method can perform better are also discussed.