Synthetic Aperture Imaging Based On Compressed Sensing In Underwater Detection

With the development of the marine industry in our country and the increasing requirements of the underwater imaging quality, the synthetic aperture sonar equipment with high resolution imaging ability gradually becomes the research hotspot. A large number of echo data need to be collected to obtain images with high resolution. This will bring a great challenge to the corresponding hardware devices, such as the A/D converter and the communication system of measurement data transmission. Therefore, the research on how to reduce the amount of data required but making sure the imaging quality will make an important practical significance.The compressed sensing theory can reduce the sampling requirement less than the Nyquist frequency and reconstructed the signal without distortion using the sparse characteristic of the signal. Two Sonar imaging algorithms based on compressed sensing are studied in this paper. Due to the sparse Sonar signals located in complex domain, one method of reconstruction algorithm in complex field directly is studied in this paper. The performance of the algorithms will be shown through the point targets’simulation experiments. The main work of thesis is divided into the following parts:(1) The basic theory of compressed sensing is researched including the sparse representation, the nonlinear measurement and signal reconstruction. The synthetic aperture Sonar imaging principle and the classical range Doppler algorithm is studied and the four point target imaging simulation is completed.(2) The distance imaging algorithm preserving phase information is studied to solve the large number data in the range. Good imaging effect can be obtained with only20%original data in the distance. It can also suppress side lobe effects and has well anti noise performance. The two dimensional down sampling compressed sensing imaging algorithm is studied, it can further reduce the amount of data while ensuring the imaging quality at the same time.(3) The reconstruction algorithm in complex domain is explored. They are the complex domain reconstruction forms of the classical algorithm and the SPGL1algorithm. The latter one can save the storage computer space and the reconstruction error is small.