Abstract
This paper introduces a method for the range localization of a moving ship based on the vertical hydrophone line array. The main implementation steps of the proposed algorithm are as follows. First, the stable low-frequency line spectrum component of the broadband radiated noise from the moving ship was extracted through the Detection of Envelope Modulation on Noise (DEMON) spectrum analysis method. Second, the pressure difference between the two different ranges was derived, and the corresponding interference fringes were observed in the plane of time and time interval. Then, the radial velocity of the moving ship could be obtained based on the period of the pattern oscillations of the interference fringes. Further, we estimated the time and range information of the Closest Point of Approach (CPA) and computed the ship range versus time. Finally, each element of the vertical hydrophone line array was processed by the method proposed above, and data fusion technology was adopted to reduce the impact of ineffective elements and improve the range estimation accuracy. The results of the simulation and experiment of a 16-element vertical array performed in the South China Sea verified the effectiveness of the algorithm.
Highlights
Range localization is a significant component of the Sound Navigation and Ranging (SONAR)system in the field of underwater target detection
We propose a range localization method of a moving target based on a vertical hydrophone line array
Inaccurate range estimation results can be obtained by a low signal-to-noise ratios (SNR) signal, as shown in the 7th, 10th and 13th element, because the sound signals at different depths go through different paths, undergoing different reflections and scattering
Summary
Range localization is a significant component of the Sound Navigation and Ranging (SONAR). Cockrell [6] adopted the waveguide invariant technology to estimate the range of a broadband sound source by using a single hydrophone. This method requires only a little prior knowledge of the environment and acquires a higher estimation accuracy. The image processing technology was used to obtain the waveguide invariance and realize the range estimation of the target. Prasanna et al [19] adopted the Modified Gain Bearings only Extended Kalman filter (MGBEKF) algorithm to judge whether there were one or two targets This method made use of various sensors such as the structure-mounted array and towed array to perform the state vector fusion.
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