New developments in multibeam technology now permit MBES to collect and record acoustic data not only from the strongest return (normally the seabed), but also echo returns from the complete travel paths of the acoustic pulse through the water column. This now allows they are established as standard tools for the remote detection of targets in the water column, such as gas bubbles leaking from pipeline. In this study, a multibeam sonar operating at 300kHz is used to detect the gas leakage of pipeline based on acoustic backscatter imagery. Some behavioural traits of the leakage gas bubbles have been discussed, such as shape, distribution pattern and contour centroid characteristics. Firstly, an adaptive beamforming algorithm is applied to sonar imaging for suppressing background noise and side lobe interference. And then these features are extracted by mathematic morphological processing of image sequences. Finally, a tank test with different leakage scales caused by leakage pressures, amounts and sizes has verified the validity and stability of the characteristics of gas bubbles. The proposed method is feasible to make a qualitative assessment for AUV pipeline detection surveys.
Terrain-aided navigation (TAN) is a promising technique to determine the location of underwater vehicle by matching terrain measurement against a known map. The particle filter (PF) is a natural choice for TAN because of its ability to handle non-linear, multimodal problems. However, the terrain measurements are vulnerable to outliers, which will cause the PF to degrade or even diverge. Modification of the Gaussian likelihood function by using robust cost functions is a way to reduce the effect of outliers on an estimate. The authors propose to use the Huber function to modify the measurement model used to set importance weights in a PF. They verify their method in simulations of multi-beam sonar in a real underwater digital map. The results demonstrate that the proposed method is more robust to outliers than the standard PF (SPF).
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