Simultaneous Velocity Ambiguity Resolution and Noise Suppression for Multifrequency Coherent Doppler Sonar

Abstract

Abstract Coherent Doppler sonar is a useful tool for noninvasive measurement of ocean currents, sediment transport, and turbulence in coastal environments. Various methods have been proposed to separately address two of its inherent limitations: velocity ambiguity and measurement noise. However, in energetic turbulent flows, both factors may be present simultaneously. The presence of measurement noise complicates velocity ambiguity resolution, and conversely velocity ambiguity presents a challenge for existing noise suppression methods. A velocity estimator based on maximum a posteriori (MAP) estimation has been developed to resolve velocity ambiguity and suppress measurement noise simultaneously rather than separately. The estimator optimally combines measurements from multiple acoustic carrier frequencies and multiple transducers. Data fusion is achieved using a probabilistic approach, whereby measurements are combined numerically to derive a velocity likelihood function. The MAP velocity estimator is evaluated using a high-fidelity coherent Doppler sonar simulation of oscillating flow and data from a towing tank grid turbulence experiment where both velocity ambiguity and backscatter decorrelation were present. Time series and spectra from MAP velocity estimation are compared to those obtained with conventional Doppler signal processing. In addition to robustly resolving velocity ambiguity, the MAP velocity estimator is shown to reduce high-frequency noise in turbulence spectra.