Research On Technologies Of Beamforming And Sparse Array For Real-time Phased-array Three-dimentional Imaging Sonar

To start the processing of the3D imaging, the real-time phased-array three-dimensional (3D) imaging sonar system transmits an acoustic pulse to insonify the scene of interest under narrow-band. A large scale planar transducer array gathers he backscattered signals and beamforms in more than then thousands of steering directions. This thesis investigates the research on new techniques of beamforming and sparse array to overcome the huge computational load and the complicated hardware system.Chapter1demonstrates the background of the research, presents the current status of the relevant techniques in different contries, and lists the main content of the thesis.Chapter2proposes a beamforming algorithm worked in far field:Distributed and Parallel Subarray (DPS) Beamforming. The full array is subdivided into two distributed subarrays and the parallel beamforming is implemented in two-stage subarrays. First, the DPS beamforming process is described and a data-path is illustrated. Second, the computational requirements are compared among DPS, DM and FFT beamforming. Third, the algorithm is simulated and the experimental results verify that the DPS beamforming achieves a similar beam pattern performance with lower computational and memory requirements.In Chapter3, the near-field time-delay parameters are optimized based on the Fresnel Approximation and the Taylor Series Expansion first. Second, the DPS beamforming algorithm is extended to the near field condition and the optimized time-delay is applied to compensate the phase shift and focus in a point. Finally, the near-field DPS beamforming algorithm is simulated in Matlab. The experimental results demonstrate that the algorithm can not only maintain the mainlobe width and the sidelobe energy, but also reduce the memory and computational requirements.In Chapter4, the DPS beamforming algorithm is combined with the simulated annealing algorithm in order to thin and weight the transducers of the receiving array. First, a new energy function is defined based on the DPS. Second, the simulated annealing algorithm with the new energy function is applied to design the sparse array. Finally, the optimized algorithm is employed on a target array and the experimental results demonstrate that:The optimized algorithm can achieve the similar beam pattern with less transducers and a lower CTR.Chapter5combines the theory and the engineering applications. A prototype is designed based on the DPS beamforming algorithm. First, considering the costs, computational requirements and the image quality, the parameters of the receiving array are chosen based on the approximations, constraints and the range validity of the coefficients in DPS. Second, the detail of the signal processor is described. Finally, the prototype is tested in lake and sea and it can image the scene with a high resolution and20frames per second.The last chapter concludes the innovation points of the research in this thesis. The prospect of the future research is also described.