基于相关性函数的多站微动特征分析与提取

针对多站雷达精度跨度大、难以有效进行融合识别的问题,提出了基于相关性函数的多站加权融合方法。首先建立了弹道目标滑动散射模型,通过时延相乘重构回波,并利用扩展Hough变换提取出距离像的曲线参数,从而建立方程组以求取微动信息。然后利用相关性函数对各雷达的支持度进行分析,最终对支持度高的观测数据进行融合识别。仿真结果表明该方法计算简单,能有效提高微动参数的估计精度,客观地反映各部雷达的可靠度。

Micro-motion Feature Analysis and Extraction in Multi-station Based on Correlation Function

To solve the problems of long-span precision in multi-station and difficult fusion identification,a method of weighted fusion in multi-station based on correlation function is proposed. Firstly,the model of sliding scattering center is established. The echo is reconstructed using half period delay multiplication,and parameters of the curve in time-range profile is extracted by extend Hough transform. Thus system of equations is built to obtain the radius and precession angle. Then the support degree of each radar is analyzed utilizing correlation function. At last the observed data with high support degree is identified by fusion. Simulation results show that this method needs less calculation, and can effectively enhance the estimation precision of micro-motion parameters as well as objectively reflect the reliability of each radar.