在杂乱中使用范围和距离测量的被动雷达跟踪
Asma Asif1, Sithamparanathan Kandeepan1, Robin J Evans2
1School of Engineering, RMIT University, Melbourne 3000, Australia.
Sensors (Basel, Switzerland)
|July 8, 2023
概括
这项研究引入了一种带有概率数据关联 (UKF-PDA) 的无气味卡尔曼波器,用于在被动双向雷达中增强3D目标跟踪. UKF-PDA方法有效地减少了偏差,并提高了跟踪准确性,即使轴承数据有限.
科学领域:
- 雷达系统工程 雷达系统工程
- 信号处理 信号处理
- 估计理论 估计理论
背景情况:
- 精确的3D目标跟踪对于被动双向式雷达系统至关重要.
- 传统的扩展卡尔曼波器 (EKF) 方法表现出缺少或不良轴承数据的偏差.
- 无线性非线性在被动比斯塔特雷达跟踪需要先进的过技术.
研究的目的:
- 开发一个强大的3D目标跟踪算法,用于被动双向雷达.
- 为了减轻传统EKF方法在具有不完整轴承信息的场景中引入的偏差.
- 通过范围和距离率测量,在混乱的环境中提高跟踪性能.
主要方法:
- 实施无气味卡尔曼波器 (UKF) 来解决3D跟踪中的非线性问题.
- 将概率数据协会 (PDA) 算法与UKF集成,以管理环境杂乱.
- 使用范围和范围率测量用于状态估计.
主要成果:
- 拟议的UKF-PDA框架成功地减少了估计偏差.
- 通过模拟,在3D目标跟踪准确度方面取得了显著的改进.
- 该方法显示了在处理缺失或低质量的轴承数据方面的增强能力.
结论:
- UKF-PDA方法为被动比斯塔特雷达跟踪提供了一个优越的替代传统EKF.
- 这一框架显著提升了被动比斯塔特雷达目标追踪能力的最先进状态.
- 拟议的方法提供了一个强大的解决方案,用于在具有挑战性的雷达环境中准确的3D跟踪.
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