Research On Detection Method Of Unknown Pulse Signal In Target Simulator

When detecting sonar for submarine training and testing,if real submarine targets are used,manpower and material resources are invested,and organization is difficult.Using target simulators to simulate submarines has the advantages of low cost,simplicity,and so on.This thesis focuses on the detection and parameter estimation of the pulse signal emitted by the active sonar in the active sonar target simulator based on the small UUV platform.First of all,the detection technology of the deterministic pulse signal of unknown parameters is researched to detect the existence of the target signal.In order to achieve better detection performance,the k-rank detection algorithm is improved according to the different frequency diversity selection methods.In the thesis,the theoretical formulas of three detection methods,single-point detection,continuous detection,and arbitrary detection are derived,and the detection performance of different pulse signals is simulated and compared,and verified by sea trial data.Secondly,the parameter estimation of the deterministic pulse signal with unknown parameters is studied,and the frequency and start and end time information of the target signal are estimated.Based on the improved k-rank detection,the second-level threshold is introduced,and the frequency of the three signals is roughly estimated by selecting different diversity numbers,and compared with the theoretical frequency and start and end time of the signal,and the appropriate algorithm is selected to realize the coarse frequency of different signals.Estimate and start and end time estimates.In order to meet the further demand for precise frequency estimation,the Rife algorithm,the improved Rife algorithm,and the parabolic algorithm are used to estimate the frequency of the single-frequency pulse signal;the least square method is used to estimate the frequency of the chirp signal and the influence factors are simulated..Finally,estimate the frequency of sea trial data.Finally,an improved k-rank detection algorithm is implemented on the signal processing platform.The processing chip of the hardware platform selected TI’s TMS320C6416,a real-time data acquisition program and an improved k-rank detection algorithm program were written,the performance of the program was tested,and the DSP detection results were compared with simulation to verify the correctness of the detection results.