Underwater Acoustic Source Localization Based on Passive Sonar and Intelligent Processing

The work presents a distributed measuring system designed and implemented for underwater acoustic source detection and localization. The main part of the system is a sonar unit with three hydrophones connected to a conditioning block controlled by an acquisition, control and processing unit expressed by a real-time controller, a FPGA core and a set of I/O modules. The conditioned signals are acquired and processed at the real time controller level using wavelets filtering algorithms in order to extract the relative time delay information. An intelligent algorithm based on a neural network uses the time delays and the sonar structure azimuth as input values to calculate the range and bearing angle associated with the detected underwater acoustic source. Elements of software implementation that uses LabVIEWreal-time and LabVIEWFPGA modules, wavelet optimal filtering study and localization results are included in the paper.