Optimization And Design Of Sparse Array For Underwater Acoustic Imaging

Underwater acoustic imaging is a hot issue in the field of detection and underwater acoustic sensor array type imaging is an important direction. However, this array imaging technology still has many problems such as complex system, high cost, imaging and low frame. In reducing the system complexity and cost of construction, there is one way to solve this which is using sparse sensor based on array constitute a MIMO array. This paper in sparse array optimization in depth research and the results of research are as follows.A method to design a sparse array called convex optimization arrays synthesis method which always be used in radar field. This sparse array is according to the requirement of underwater acoustic imaging system. To receive the object function by setting the size of the array and the side lobe level and then doing a number of iterations to optimize the most ideal sparse array. The next step is to simulate the image of the optimization of the basic array. At the end of the result, we will get an image which has about 3cm of the longitudinal resolution and 9.2 degree angle resolution. According to this system can both achieve the veracity of judge a goal and the purpose of reducing the cost.the method of virtual array element is adopted to realize the optimization design based on the square array, reasonable setting of the position of the transmitting array element and the receiving element, the effect of the target array is realized with the minimal transmit and receive elements, and the coupling between the array elements is reduced, combined with the transmit signal with good performance can be achieved a launch for imaging purposes, to improve the imaging frame rate. The results of the imaging simulation of point target and the target geometry show that the target display vertical resolution of about 3cm and 5° angle resolution, geometric object's features and structural details are obvious, including the recognition and judgment of the object shape, the sparse matrix meets the requirements of the imaging, but also reduces the complexity and cost of the system.To compare these two imaging results which designed by two different methods we get the results are in followed. First of all, two kinds of optimized matrix can both achieve imaging results. The convex optimization method to optimize the array design in detecting distance to the virtual array method of sparse array has the similar resolution, but the angular resolution more worse because the change of the array-element influence the results. Therefore the convex optimization method of the array resolution still needs to be improved.