论文部分内容阅读
适当的运动模型和估计方法是提高再入目标跟踪性能的关键。选择机动再入动力学模型,将再入目标跟踪问题转化为状态和参数的联合估计问题,并利用试验数据分析了再入模型状态和参数的相关性。针对原始双重酉滤波算法的确定性系统输入假设造成信息损失的局限性,提出了一种基于随机性系统输入假设的改进双重酉滤波算法,并从理论上分析了该算法的估计精度。仿真实验验证了新算法的适用性、估计精度和不完全处理能力。
Appropriate motion models and estimation methods are the key to improving re-entry tracking performance. The maneuvering reentry dynamics model is selected, the re-entry target tracking problem is transformed into the joint estimation problem of state and parameters, and the correlation between the reentry model state and parameters is analyzed by using the experimental data. Aiming at the limitation of information loss caused by the deterministic system input hypothesis of the original dual unitary filtering algorithm, an improved dual unitary filtering algorithm based on the input hypothesis of stochastic system is proposed, and the estimation accuracy of the algorithm is theoretically analyzed. Simulation experiments verify the applicability of the new algorithm, estimation accuracy and incomplete processing capability.