Batch Processing through Particle Swarm Optimization for Target Motion Analysis with Bottom Bounce Underwater...

Area of Science:

• Acoustics and Signal Processing
• Oceanography and Marine Technology

Background:

• Underwater acoustic signals exhibit multi-path propagation, leading to varying elevation angles.
• Traditional target motion analysis (TMA) using horizontal line arrays interprets signals as azimuth angles, neglecting conical angle effects.
• Bottom bounce paths in underwater acoustics can cause significant inaccuracies in target localization if not accounted for.

Purpose of the Study:

• To investigate the impact of conical angle on bearings-only target motion analysis (BO-TMA).
• To develop and validate a novel BO-TMA method capable of resolving angular ambiguity in underwater environments.

Main Methods:

• Simulated target conical angle using a ray tracing method in a modeled underwater environment.
• Proposed a particle swarm optimization (PSO) based approach for batch processing of acoustic data.
• Implemented the PSO-TMA method to address angular ambiguity issues.

Main Results:

• Demonstrated that conical angles, arising from multi-path propagation, introduce significant angular ambiguity in TMA.
• The proposed PSO-based BO-TMA method effectively resolves the angular ambiguity caused by conical angles.
• Accurate target localization was achieved by considering the conical angle in the analysis.

Conclusions:

• The conical angle is a critical factor in underwater acoustic target tracking that must be addressed.
• The developed particle swarm optimization method offers a robust solution for bearings-only target motion analysis with angular ambiguity.
• This research enhances the precision of underwater target localization systems.