基于稀疏重构的前视声纳成像方法OACSTPCD

The DOA estimation algorithm based on sparse reconstruction can obtain higher-resolution spatial spectrum estimation by strengthening the sparsity of the representation,which is helpful to realize the differentiation of adjacent targets,and a sonar imaging method with sparse reconstruction at each distance is proposed.This method uses the sparsity of the target itself in sonar imaging and the norm constraint in the sparse reconstruction algorithm to obtain higher resolution and ultimately achieve the im-provement of imaging effect.In the simulation and pool experiments,the performance of l1-SVD and SpSF sparse reconstruction algorithms is compared with the traditional azimuth estimation methods MUSIC,CBF,SFW-L21 and NN-SpSF,and the experi-mental results show that the l1-SVD algorithm and SpSF algorithm are better than the traditional methods,with narrower main lobes and lower side lobes,and have a certain suppression effect on background noise.At the same time,two targets that are close to each other can also be well distinguished,indicating a higher resolution.