ballistic tracking

Reentry ballistic trajectory tracking is the core issue of ballistic missile defense system. Tracking system performance will directly affect the success rate for ballistic missile interception.

再入弹道目标跟踪是弹道导弹防御系统的核心问题，跟踪系统性能的优劣直接影响着对弹道导弹的拦截成功率。

Ballistic Missile Tracking Based on a Swarm Intelligent Particle Filter

基于集群智能粒子滤波的弹道导弹跟踪

The simulation result showed the good performance of the filter for the ballistic target tracking with fast convergence, high tracking accuracy and strong tracking stability.

通过仿真试验比较，验证了本文提出了基于弹道目标跟踪的非线性扩展卡尔曼滤波器具有良好的性能。仿真结果表明，该滤波器具有收敛速度快，跟踪精度高，跟踪稳定性强等特点。

Ballistic Missile Tracking Algorithm with Anti-Jamming Capability in Spherical Coordinates

球坐标系下具有抗干扰能力的弹道导弹跟踪算法

In this paper, the ballistic missile is the specific study object and the problem of the ballistic missile re-entry tracking is studied.

本文以弹道式导弹为具体对象，研究了弹道导弹再入段的跟踪问题，主要采用EKF算法和UKF算法两种非线性滤波算法弹道导弹的再入段飞行轨迹进行跟踪研究，并对跟踪系统进行仿真分析。

Track breakage is common issue in multiple ballistic targets tracking scenario with high speed, high density and large measurement error.

多弹道目标跟踪伴随着速度快、密集程度高以及测量误差大等因素，在跟踪过程中发生航迹中断是一个很普遍的现象。

In this paper, research on particle filter algorithm for ballistic target tracking is carried on under the main background of nonlinearity, non-Gaussian noise.

本论文以非线性、非高斯噪声环境下的目标跟踪为主要背景，研究弹道导弹目标粒子滤波算法。

The precision tracking and quick discrimination is the basis of the missile interception, Reentry ballistic target tracking and discrimination is one of the kernel missions for ballistic defense system.

弹道目标的跟踪和识别是弹道导弹防御系统的核心任务之一，是后续进行有效目标拦截的基础。