由雷达测量数据求解脱靶量算法研究

【作者】 袁俊；

【导师】 陆锦辉；

【作者基本信息】 南京理工大学 ， 通信与信息系统， 2003， 硕士

【摘要】 在靶场试验中，脱靶量对鉴定导弹的性能起着至关重要的作用。本文将以靶场雷达测量得到的导弹和靶标的位置数据为基础，重点研究脱靶量的求解算法。 本文首先以自适应输入模型和“当前”统计Jerk模型为目标模型，采用转换坐标卡尔曼滤波算法对雷达测量数据进行滤波；然后提出了一种交互式多模型自适应滤波算法，在该算法中常速度模型、常加速度模型和自适应输入模型并行工作，目标状态估计是这三种模型交互作用的结果。在实际情况中，当导弹与靶标遭遇时，雷达不能分辨；本文将利用雷达对导弹和靶标的前一段测量数据进行轨迹外推，并根据外推的结果估计出遭遇点的脱靶量。仿真表明，本文提出的脱靶量测量方法能够较好的满足实际应用中所需的精度要求。更多还原

【Abstract】 The miss distance between the missile and target is very important for people to judge the performance of a missile on the target drone. This thesis mainly discusses the measurements of miss distance based on the data of the missile and target obtained by radar detecting and capturing.Combining Debiased Statistics of 3-dimensional Converted Measurements, Two filtering algorithms for data processing are developed based on the Adaptive Input Statistics Model and "Current" statistical Jerk Model. Besides a new Interacting Multiple Model Adaptive Filtering Algorithm is presented. In this algorithm, constant velocity model, constant acceleration model and adaptive input staticatics model are running in parallel. Target status estimation is the result of interacting of these three models. During the course of the intersection between the missile and target, it is difficult for radar to distinguish them. But we can estimate the coordinate of the intersection point by extrapolation technique based on the foregoing data of the missile and target obtained by radar detecting, consequently the miss distance can be estimated. The results of simulations demonstrate that the method of this thesis can meet the demands in accuracy of practical use.更多还原