基于改进Jerk模型的高超声速滑翔目标跟踪

临近空间高超声速滑翔目标具有高速、高机动的运动特性,为了提高其跟踪精度,对现有的Jerk跟踪模型提出改进。首先将一阶AR模型的思想运用到模型参数的实时估计中,在目标状态方程和量测方程中引入了相关参数,然后构建了基于改进Jerk模型的参数自适应Kalman滤波算法,在目标状态估计的同时能够对模型参数进行自适应调整。最后基于HGT仿真轨迹对所提模型与传统的Jerk模型进行比较,仿真结果证明了改进Jerk模型对HGT跟踪的有效和优势。

Hypersonic Gliding Target Tracking Based on Improved Jerk Model

The near space hypersonic gliding target (HGT) is characteristics of high speed, high mobility motion. In order to improve its tracking accuracy, an improvement on the existing Jerk tracking model is made. In this paper, the idea of first order AR model is applied to the real-time estimation of model parameters. The relevant parameters are introduced in the target state equation and measurement equation. And then the parameter adaptive Kalman filter algorithm is constructed based on the improved Jerk model to make the target state, and the model parameters adaptively adjusted at the same time. Finally, based on the HGT simulation trajectory, the proposed model is compared with the traditional Jerk model, and the effectiveness and advantages of improving the Jerk model for HGT tracking are proved.