Target Motion Parameters Estimation by Full-Plane Hyperbola-Warping Transform with a Single Hydrophone

In this paper, to counteract the sensitivity of the traditional Hough transform to noise and the fluctuations in parameter estimation, we propose a hyperbolic warping transform that integrates all interference fringes in the time–frequency domain to accurately estimate the motion parameters of a single hydrophone. This method can accurately estimate the target motion parameters, including the time of closest point of approach (tCPA), the ratio of the nearest distance to the speed (b=rCPA/v), and the waveguide invariant (β). The two algorithms are compared by simulation and sea trial experiments. Hyperbola-warping improves the noise immunity performance by 10 dB in simulation experiments, increases the detection range by 20% in sea trial experiments, and demonstrates that the method proposed in this paper has better noise resistance and practicality.