针对单部雷达提取目标微动参数精度不高和难以实现三维重构的问题,提出了一种基于多视角微动信息自适应融合的三维重构新方法.首先,建立了组网雷达模型和锥体进动模型,在详细分析各散射点微距离变化关系的基础上,对不同视角下的锥顶散射点进行了匹配关联.然后,以每两部雷达的观测信息作为一个目标参数求解组合,采用基于估计方差最小的加权融合算法对各组合求得的参数进行优化处理.最后,利用优化后的参数求解出目标锥顶坐标和锥旋矢量,实现了锥体目标的三维重构.仿真结果表明该方法能有效实现高精度参数的提取和锥体目标的重构.%Aiming at the problem that single radar extracts micro-motion parameters inaccurately and has difficulty attaining 3D reconstruction,a novel 3D reconstruction algorithm based on the multi-aspect micro-motion information's adaptive fusion is proposed to extract the micro-motion parameters in this paper.Firstly,radar network model and cone-shaped precession model are established and different-aspect conic node scattering point is matched and identified based on analyzing the relation of each scattering point's micro-distance variation in detail.Then,regarding the observed information of every two radars as one solving unit and parameters from each unit are optimized by the weighed fusion array based on minimum variance estimating.Lastly,solving the coordinates of conic node and coning vector based on making use of optimizing parameters information.Moreover,cone attains 3D reconstruction based on the coordinates of conic node and coning vector.Simulation results prove that the proposed method can realize the extraction of high accuracy parameters and cone's reconstruction availably.
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