基于修正LCMV的对流层散射波束域测向算法

利用微波在对流层的散射现象进行电磁侦测是实现超视距雷达辐射源探测的有效手段之一.随着探测威力、分辨力要求的提高，对于散射多径引起的衰落相关导致接收协方差矩阵秩亏损，令多重信号分类(multiple signal classification，MUSIC)等基于特征分解的超分辨类测向算法失效，以及散射机制下大型分布式源产生的相位扩散导致接收阵列流形失配等问题，文章根据近期建立的散射衰落相关模型设计相互独立的多波束排布，并相应地提出一种修正的线性约束最小方差(linearly constrained minimum variance，LCMV)方法补偿相位扩散影响，将接收信号由受衰落相关影响的阵元域变换到独立的波束域，并在波束域进行超分辨测向.仿真结果验证了测向算法在散射多径衰落条件下的有效性，对600 km目标散射信号积累300快拍能达到0.5°的估角精度.

Beamspace DOA estimation method based on modified LCMV for troposcatter

Over-the-horizon(OTH) reconnaissance of radiation sources as radar can be realized by the troposcatter propagation of microwave signals. With the improving requirements of the detection coverage and resolution, the dependence among received covariance matrix caused by the troposcatter multipath fading correlation, and the receiving array manifold mismatch caused by the huge distributed scattering source are two inevitable problems. Therefore, this paper firstly provides a mutual independent multibeams arrangement according to an recently established troposcatter fading correlation model, and then proposes a modified linearly constrained minimum variance(LCMV) to compensate the diffusion phases within the array manifold, transforms the received snaps to the mutual independent beamspace and finally a beamspace direction-of-arrival (DOA) estimation method is conducted respectively. The proposed beamspace DOA estimation method is verified by the simulation results under the troposcatter multipath fading conditions.