混合体制雷达网弹道目标进动特征提取

Precession feature extraction of ballistic target based on hybrid-scheme radar network

针对同构组网雷达在提取弹道目标微动参数中存在的不足,提出了一种混合体制雷达网在获取目标散射中心数量不一致的条件下弹道目标进动特征提取方法.首先,对弹道目标进动和宽、窄带雷达信号进行了建模,分析了目标散射中心在窄带雷达和宽带雷达下的回波特性.根据目标散射中心的雷达回波特性,利用散射中心调制系数法实现了目标散射中心在不同雷达之间的匹配关联.然后,对宽带雷达获得的散射中心距离像信息进行分析,并利用广义Radon变换对距离像信息进行变换,通过变换关系求解得到了目标进动角.最后,构建宽窄带雷达微多普勒信息联合方程组,在求得进动角的基础上实现了雷达视角和结构参数的求解,接着采用二分法对三种求解组合得到的参数进行优化,进一步利用优化后的参数联立三维矢量求解方程组,求得了三维锥旋矢量.仿真结果表明,在信噪比大于5dB时,宽带雷达网参数求解精度与混合体制雷达网参数求解精度接近,且均比窄带雷达网参数求解精度高,从而验证了本文方法的有效性.

Because of the deficiency of the same type of radar in extracting micro-motion parameters of ballistic target,a method for precession feature extraction of ballistic target was proposed by using hybrid-scheme radar network under the circumstance that the numbers of the obtained scattering centers are different. First,a ballistic target precession model and a wide band and narrow band radar signal model were established,and the echoes characteristics of the target scattering centers under narrow band radar and wide band radar were analyzed. Based on the characteristics,each scattering center in different radar system echoes was matched and identified. Then the scattering center range information obtained by the wide band radar was analyzed,the range information was transformed by using generalized Radon transform,and the precession angle was solved by parameter transform relationship. The associated systems of equations of micro-Doppler information were further established,and the visual angle and structural parameters of radars were solved by the precession angle. Dichotomy was used to optimize the parameters obtained from the three solution combinations, and the obtained parameters were constructed to obtain three-dimensional cone rotation vector. Simulation results show that when the SNR was greater than 5 d B,the validity of the proposed method was close to that of the wide band network and both were higher than that of the narrow band network,which verified the effectiveness of the proposed method.