三种虚拟阵元内插超分辨测向算法的性能对比

对比研究了基于虚拟阵元内插的三种超分辨测向算法.在对多个小孔径雷达阵列的观测数据进行相干处理的基础上,分别应用非线性最小二乘迭代(NLS,Nonlinear Least Squares)、基于最小熵的反卷积迭代(IDMEC,Iterative Deconvolution algorithm based on Minimum Entropy Criterion)和最小加权范数(MWN,Minimum Weighted Norm)等算法构造雷达阵列间的各个虚拟阵元,合成大的孔径阵列以提高测向分辨率.通过仿真,验证了三种虚拟阵元内插算法的有效性,分析和比较了它们的超分辨性能和运算量.结果表明MWN法不仅具有最小的虚拟阵元构造误差和运算量,且有最好的测向性能.因此,总体上MWN法优于NLS法和IDMEC法. 

Performance comparison among three super resolution direction finding algorithms based on virtual element interpolation

Three super resolution direction finding algorithms based on virtual element interpolation were studied.On the basis of mutually cohering the signals from multiple smaller arrays of different radars,three super resolution algorithms,namely,the nonlinear least squares(NLS) algorithm,the iterative deconvolution algorithm based on minimum entropy criterion(IDMEC),and the minimum weighted norm(MWN) algorithm were applied to interpolate the virtual elements between the physical radar arrays.As a result,the effec...