A Small Targets Detection Method Under Background of Large Targets in Air Domain Based on Sparse Reconstruction
In modern warfare,there are often collaborative operations between large and small platforms,such as manned-unmanned formation collaborative operations.During such operations,it's difficult to detect both the large and small targets simultaneously since the echo side lobe of large targets often obscures the echo of small targets,which poses a serious challenge to the commander's judgment of the battlefield situation.To solve the above problem,a method for separating large and small targets based on compressed sensing sparse reconstruction is proposed,which utilizes the high-resolution characteristics of compressed sensing sparse reconstruction algorithm to achieve the separation of large and small targets in the airspace and eliminate the influence of large targets on small targets.Firstly,asparse reconstruction method based on virtual transformation is proposed to address the conflict between the reconstruction accuracy and computational efficiency in traditional sparse reconstruction methods.The simulation analysis results show that the proposed method realizes a better separation accuracy of big and small targets compared to traditional Orthogonal Matching Projection(OMP)methods,and it achieves an improvement of 16％in computational efficiency compared to traditional convex optimization reconstruction methods.
collaborative operationtarget detectionlarge and small targetssparse reconstruction
万方数据
维普
