Design And Implementation Of Signal Processing Algorithm For Underwater Target Detection Sonar

In recent years,with the rapid development of human economy and science and technology,the exploration of the marine environment is increasing,and the strategic position of the ocean is becoming more and more important.The efficient detection of underwater targets using underwater target detection sonar is one of the core issues in the field of modern national defense science and technology and marine construction.The main task of this paper is to distinguish whether the target signal is hidden or not and to estimate some parameters of the signal by processing the collected data.It is a key link in underwater target detection and the premise and basis of the tasks of tracking,recognizing and locating the sequential target.Firstly,the data collected are filtered in spatial domain by array signal processing.Then the signal detection algorithms based on short-time Fourier transform,instantaneous correlation integral and high-order cumulant,and the frequency estimation techniques based on Rife algorithm,M-Rife algorithm and iterative minimization sparse learning algorithm are studied respectively.Finally,the processing performance of the above algorithms under specific conditions is simulated and analyzed.Yes.According to the research results,this paper designs a set of complete signal processing flow and implements the software through the hardware platform of TMS320C6678,and tests the functions of the software in network interface,signal processing and other modules.Finally,the performance of the software is tested by the measured data of the pool.The experimental results show that the software designed in this paper is feasible in practical application.