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  1. 首页
  3. 一种用于分布式雷达拓优化的增强mopso方法.
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一种用于分布式雷达拓优化的增强MOPSO方法.

Lin Cao1,2, Shengwu Qi1,2, Zongmin Zhao1,2

  • 1Center for Target Cognition Information Processing Science and Technology, Beijing Information Science and Technology University, Beijing 100101, China.

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|March 14, 2026

在PubMed 上查看摘要

概括
此摘要是机器生成的。

这项研究优化了分布式雷达拓,以改进到达时间差 (TDOA) 定位. 这种新方法通过平衡节点位置并最大限度地减少精度的几何稀释 (GDOP) 来提高定位精度和监控覆盖率.

关键词:
在TDOA的本地化.分布式雷达是指分布式雷达.精度的几何稀释精度的几何稀释.多目标优化多目标优化拓优化优化拓学的优化

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科学领域:

  • 雷达系统工程 雷达系统工程
  • 信号处理 信号处理
  • 优化算法 优化算法

背景情况:

  • 时间差距到达 (TDOA) 定位提供了高精度,但对雷达节点拓敏感.
  • 现有的研究往往优先考虑本地化准确性,而不是几何布局和覆盖范围的影响.

研究的目的:

  • 为分布式雷达系统提出拓优化方法,以提高本地化性能.
  • 通过考虑几何布局和监控覆盖范围来解决当前TDOA定位的局限性.

主要方法:

  • 开发了分布式TDOA雷达系统的几何定位模型.
  • 制定了三个优化目标:尽量减少精度的几何稀释 (GDOP),最大限度地覆盖目标,并改善几何平衡.
  • 采用了改进的非主导排序多目标粒子群优化 (NS-MOPSO) 算法,并增强了选择和多样性策略.

主要成果:

  • 优化的拓导致根平均平方位置错误 (RMSPE) 减少了6.4%.
  • 与现有方法相比,在高质量的本地化区域实现了4.3%的增长.
  • 在模拟和现实世界的实验中证明了更快的融合,更好的稳定性和更强大的稳定性.

结论:

  • 拟议的拓优化方法有效地提高了TDOA定位的准确性,并扩大了监控覆盖范围.
  • 基于NS-MOPSO的方法为分布式雷达系统设计提供了强大而稳定的解决方案.
  • 优化雷达节点几何是最大限度地提高系统性能和实现可靠的定位至关重要.