Micro-motion Characteristic Analysis and Parameters Estimation for Blunt-nosed Chamfered Cone Based on HRRP Sequence
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摘要: 合适的弹头结构建模是正确估计弹头参数的基础。该文提出一种描述弹头的钝头倒角锥模型,该模型将球冠散射中心和倒角散射中心看作是滑动散射中心,并引入锥体侧面遮挡效应对散射中心位置的影响,给出散射中心位置变化的一般形式;接着分析了钝头倒角锥模型各个散射中心的微动特性;在此基础上,提出了一种估计目标运动参数和结构参数的非线性优化的方法;最后,仿真结果验证了该文模型的正确性及参数估计方法的有效性。Abstract: Appropriate warhead structure modeling is the basis for warhead parameters estimation. In this paper, the warhead is modeled by the blunt-nosed chamfered cone model, which regards the spherical center and the chamfer scattering centers as the sliding centers and takes the influence of the side of the cone into account, the general form of the position of the scattering centers is given based on the model. Then, the micro-motion of the scattering centers in the blunt-nosed chamfered cone model is derived. Based on this, a nonlinear optimization method is proposed to estimate the target's motion parameters and structural parameters. Finally, simulation results verify the correctness of the model and the effectiveness of the parameter estimation method.
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表 1 不同
$\text{β}$ 角下的散射中心位置矢量视角I
$0 < \beta < \alpha $视角II
$\alpha < \beta < {\text{π}}/2 - \alpha $视角III
$ {\text{π}}/2 - \alpha < \beta < {\text{π}}/2$视角IV
$ {\text{π}}/2 < \beta < {\text{π}} - \alpha $视角V
$ {\text{π}} - \alpha < \beta < {\text{π}}$A ${{\text{r}}_{{\rm{AU}}}}\left( t \right)$ ${{\text{r}}_{{\rm{AU}}}}\left( t \right)$ ${{\text{r}}_{{\rm{AS}}}}\left( t \right)$ ${{\text{r}}_{{\rm{AS}}}}\left( t \right)$ – B ${{\text{r}}_{{\rm{BS1}}}}\left( t \right)$ ${{\text{r}}_{{\rm{BS1}}}}\left( t \right)$ ${{\text{r}}_{{\rm{BU}}}}\left( t \right)$ ${{\text{r}}_{{\rm{BU}}}}\left( t \right)$ ${{\text{r}}_{{\rm{BU}}}}\left( t \right)$ C ${{\text{r}}_{{\rm{CS1}}}}\left( t \right)$ – – ${{\text{r}}_{{\rm{CS2}}}}\left( t \right)$ ${{\text{r}}_{{\rm{CS2}}}}\left( t \right)$ 表 2 目标参数估计结果对比
$H({\rm{m}})$ $R({\rm{m}})$ ${R_{\rm A}}({\rm{m}})$ ${R_{\rm B}}({\rm{m}})$ $\gamma {(^ \circ })$ $\varphi {(^ \circ })$ 真实值 2.0000 0.4000 0.1000 0.1000 40.0000 10.0000 本文模型 2.0384 0.3885 0.0968 0.0952 40.3328 9.9964 文献[4]模型 1.6001 0.5183 0.0000 0.0000 38.3837 8.2801 -
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