带宽限制和混合网络攻击对无人地面车辆的运动状态估计:一个弹性集成会员过框架
Ziyang Wang1, Peng Lou1, Yudong Wang1
1College of Mechanical and Electrical Engineering, Qingdao Agricultural University, Qingdao 266109, China.
Sensors (Basel, Switzerland)
|November 9, 2024
概括
这项研究使用二进制编码方案 (BCS) 增强无人地面车辆 (USV) 运动估计,以应对网络攻击和带宽限制. 新的算法确保了准确的速度估计,尽管不确定性和干扰.
科学领域:
- 机器人和控制系统 机器人和控制系统
- 网络系统安全 网络系统安全
- 信号处理 信号处理
背景情况:
- 无人驾驶地面车辆 (USV) 需要强大的运动状态估计,以进行导航和控制.
- 无线传感器网络在USV面临诸如带宽限制和网络攻击等挑战,降低估计性能.
- 现有的估计算法与混合网络攻击和有限的通信能力作斗争.
研究的目的:
- 为使用二进制编码方案 (BCS) 的USV转向系统开发一个改进的集合成员状态估计算法.
- 提出一个强大的弹性过框架,解决未知但有界 (UBB) 噪声,模型不确定性和估计器增益干扰.
- 在复杂的操作条件下,准确估计USV的摇摆,曲折和滚动速度.
主要方法:
- 提出了基于BCS的改进的集合成员状态估计算法.
- 一个强大的弹性过框架旨在处理UBB噪声,模型不确定性和增益干扰.
- 用数学归纳推导来推导估计器存在的足够条件,通过线性矩阵不等式获得的收益.
- 一个递归优化算法用于最佳估计性能.
主要成果:
- 拟议的算法部分减轻了混合网络攻击和带宽限制造成的性能下降.
- 精确估计摇摆,曲折和滚动速度,即使在并发的网络攻击,容量限制,UBB噪音,模型不确定性和增强干扰的情况下也可以实现.
- 模拟实验验证了拟议的估计算法的有效性.
结论:
- 开发的基于BCS的集合成员估计算法和强大的弹性过框架显著提高了USV运动状态估计.
- 提出的方法在具有网络攻击和不确定性的具有挑战性的网络环境中提供准确可靠的USV速度估计.
- 这项研究有助于推进安全和有弹性的自主海运系统.
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