Bistatic Target Classification using Low-Cost Unmanned Marine Vehicles in Shallow Water

Erin Fischell | Woods Hole Oceanographic Institution

MR18-1443

Objective

The objective of this research is to investigate acoustic characterization techniques for seabed targets that are scalable to multiple low-cost autonomous vehicles fitted with simple hydrophone arrays and sources in response to the “detection, classification, and remediation of military munitions underwater” statement of need. Specifically, the research will address the identification of features of bistatic and multistatic scattering fields from seabed targets for autonomous target localization and characterization using unmanned marine vehicles (UMVs). The concept of the bistatic or multistatic approach is that multiple low-cost, low-power receiver vehicles may be used to cover an area and come up with basic target contact information (e.g. location, geometry) using a single acoustic source vehicle.

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Technical Approach

When a seabed target is insonified by an acoustic source, the time delayed echoes interfere in the frequency domain to produce a three-dimensional (3D) spatial radiation pattern. This field changes based on the target aspect angle, target geometry, composition, size, and other factors. In this approach, an acoustic data collection payload including a hydrophone array is located on a UMV and a time-synchronized acoustic source is mounted on a separate UMV or at a fixed location. As the receiver vehicle progresses through the environment, the acoustic reflections from seabed targets are captured in time-synchronized acoustic data collection on the receiving array. Two techniques will be addressed for using this data: bistatic imaging and multistatic radiation pattern classification (Fig. 1). In bistatic imaging, a fixed source insonifies a target, and a UMV with a low-cost linear hydrophone array circles the target. The acoustic data is used to form an image using modified synthetic array processing techniques, with the goal of identifying features that indicate shape and composition. In multistatic radiation pattern characterization, a source is located on one UMV and the receiver on another. The received scattering strength of the target is recorded as source and receiver move around or past the target, and the resulting dependence of scattering strength versus source-target-receiver geometry is used for estimating target characteristics using machine learning. Algorithms will be developed using simulated scattering data, and tested in real-world scattering experiments using UMVs.

MR18-1443_graphic

Bistatic target classification using low-cost unmanned marine vehicles in shallow water (left) and multistatic mission with target-circling UMV-mounted source and UMV-mounted receiver (right). Multiple UMV-mounted receiver may be used to scale up target characterization over larger areas.

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Benefits

This work will result in novel experimental bistatic and multistatic scattering data sets that will improve understanding of target scattering physics, critical to the development of advanced munition detection and mine countermeasures missions for the DoD.   Bistatic or multistatic target scattering-based seabed object classification would be scalable to multiple low-cost, low-power unmanned underwater and unmanned surface vehicles with the objective of more rapid coverage of large areas compared to the current technology.

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Points of Contact

Principal Investigator

Erin Fischell

Wood Hole Oceanographic Institution

Phone: 732-299-6650

Program Manager

Munitions Response

SERDP and ESTCP

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