Imaging Algorithm And System For The Underwater Sonar With Sparse Senor Array

The research and design of sensor array underwater imaging system is an important subject of underwater sonar imaging.Sensor array underwater imaging refers to the process that the sonar system transmits the signal to the whole underwater detection scene,receives the echo signal of the detected object through the plane sensor array,and uses the beam forming and imaging.In beamforming,excessively high sidelobe level can affect imaging quality.The higher the sidelobe level,the lower the contrast,and the more artifacts surrounding the imaging of underwater targets.This dissertation addresses the above issues and conducts the following research work:(1)Based on the model of uniform plane sensor array,a sidelobe suppression algorithm based on improved genetic algorithm is proposed.The algorithm first encodes the excitation weights of the elements,takes the expected peak sidelobe level as the objective function,then flexibly selects the probability of crossover and mutation according to the fitness function of the current population,and finally retains the optimal excitation weights and generates the ideal beam pattern.Simulation results show that the algorithm can effectively suppress the peak sidelobe level when the echo signal comes from different directions.(2)In order to suppress the peak sidelobe level of the beam and improve the imaging quality,a low sidelobe beamforming imaging algorithm is proposed,which can be imaged by only one transmit receive signal process.The algorithm uses convex optimization algorithm to efficiently solve the excitation weights of array elements that meet the constraint conditions.The excitation weights are formed into a 3D apodization function,which acts on the received signals of each array element in the way of apodization.The received signals of each array element after apodization are formed and imaged by delay summation wave beam.The simulation results show that the 3D apodization function method based on convex optimization can effectively suppress the peak sidelobe level of the beam,and the proposed imaging algorithm can improve the imaging contrast and reduce the artifacts around the target imaging.(3)The sparse array imaging system designed by the research group is studied and analyzed.In order to ensure the load capacity of the system,some parameters of the transmitting circuit are improved,and the system is successfully built and debugged.The low sidelobe beamforming imaging algorithm is applied to sparse array imaging system for underwater target imaging in natural waters.The experimental results show that the proposed imaging algorithm can complete the imaging of an underwater geometric target through a single transmit receive signal process,which has practical engineering significance.