基于多模型加权的高速弹丸目标落点预测方法研究

Landing Point Prediction Method for High-Speed Projectile Target Based on Multi-Model Weighting Theory

中文关键词:  高速弹丸  无迹卡尔曼滤波  多模型加权  最优组合估计  精度

英文关键词:high-speed projectile  traceless Kalman Filter  multi-model weighting  optimal combination estimation  accuracy

中文摘要:

      针对目前高速弹丸目标海上试验末段弹道外推及落点预测方法单一，模型复杂和适应性差等问题，提出一种基于多模型加权组合的弹道重构及落点计算方法。利用无迹卡尔曼滤波技术对雷达测量数据参数估计，基于多模型理论，采用非线性加权平均最优组合估计方法，将运动学和动力学建模外推弹道加权组合，并对外推弹道及落点计算精度进行了试验验证。试验数据表明：该方法可以有效降低单一模型带来的误差和参数误差，极大地提高数学建模的适应性，通用性强，且落点计算精度优于同类方法，具有推广应用价值。

英文摘要:

      For the ballistic extrapolation and landing point prediction at the end of the current high-speed projectile in sea test,a method of ballistic reconstruction and landing point calculation based on weighted combination of multiple models is proposed aiming at the problems of single method ,complicated model and poor adaptability.The parameters of radar measurement data are estimated using unscented Kalman Filter technology.Based on the multi-model theory and nonlinear weighted average optimal combination estimation method,the kinematics and dynamics modeling trajectory are weighted and combined,and the calculation accuracy of extrapolated trajectory and landing point is verified by experiments.The experimental data shows that this method can effectively reduce the error and parameter error caused by a single model,greatly improve the adaptability of mathematical modeling,has strong versatility,and has a better calculation accuracy of landing points than similar methods,and has the value of popularization and application.