Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Electronic Distance Measuring Instruments01:30

Electronic Distance Measuring Instruments

Electronic Distance Measuring Instruments (EDMs) are essential tools in modern surveying, offering precise distance measurements by emitting electromagnetic signals and calculating the time required for these signals to travel to a target and return. Two primary types of signals are used in EDMs — light waves and microwaves — each suited to specific environmental and distance requirements. Light-wave-based EDMs utilize either infrared or laser light, providing high accuracy over short distances...
Real-World Applications of Space Curves01:29

Real-World Applications of Space Curves

Modern aerospace navigation depends on the accurate prediction of motion in three-dimensional space. In defense applications, radar systems continuously track both interceptors and moving aerial targets to find whether their flight paths will result in a collision. These motions are modeled mathematically as space curves, which represent paths that change continuously with time. Each object’s position is described by a vector function that specifies its location in terms of time-dependent...

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Adaptive Multi-Sensor Joint Tracking Algorithm with Unknown Noise Characteristics.

Sensors (Basel, Switzerland)·2024
Same journal

RETRACTED: Zhang et al. A Novel Framework for Reconstruction and Imaging of Target Scattering Centers via Wide-Angle Incidence in Radar Networks. <i>Sensors</i> 2025, <i>25</i>, 6802.

Sensors (Basel, Switzerland)·2026
Same journal

Enhancing Unsupervised Multi-Source Domain Adaptation for Person Re-Identification via Mixture of Experts and Graph-Based Relation.

Sensors (Basel, Switzerland)·2026
Same journal

Development of an Instrumented Glove for Palmar Pressure Assessment in Kayakers.

Sensors (Basel, Switzerland)·2026
Same journal

Development and Experimental Validation of an Autonomous IoT-Based Monitoring System for Real-Time Water Quality Assessment in the Amazon River.

Sensors (Basel, Switzerland)·2026
Same journal

Semi-Supervised Adversarial Learning Framework for Controller Area Network Bus Intrusion Detection.

Sensors (Basel, Switzerland)·2026
Same journal

Smart Optimization Method for Safety Signs in Innovative Manufacturing Environments Integrating Industrial Field IoT Sensors and Knowledge Graphs.

Sensors (Basel, Switzerland)·2026
查看所有相关文章

相关实验视频

Updated: Jun 19, 2026

Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles
11:54

Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles

Published on: March 13, 2017

9.2K

一种基于无气味卡尔曼波器的自适应空间目标追踪方法.

Dandi Rong1, Yi Wang1

  • 1Nanjing Research Institute of Electronics Technology, Nanjing 210039, China.

Sensors (Basel, Switzerland)
|September 28, 2024
PubMed
概括
此摘要是机器生成的。

本研究引入了适应性噪声因子方法,以提高空间目标跟踪精度. 它增强了无香料卡尔曼波器处理时间变化的测量噪声,优于标准方法.

关键词:
没有香味的卡尔曼过器.适应性噪声因子适应性噪声因子基于太空的红外卫星和地面雷达的合作.空间目标跟踪 空间目标跟踪

更多相关视频

A Protocol for Real-time 3D Single Particle Tracking
10:16

A Protocol for Real-time 3D Single Particle Tracking

Published on: January 3, 2018

14.8K
A Method for Tracking the Time Evolution of Steady-State Evoked Potentials
12:03

A Method for Tracking the Time Evolution of Steady-State Evoked Potentials

Published on: May 25, 2019

8.4K

相关实验视频

Last Updated: Jun 19, 2026

Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles
11:54

Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles

Published on: March 13, 2017

9.2K
A Protocol for Real-time 3D Single Particle Tracking
10:16

A Protocol for Real-time 3D Single Particle Tracking

Published on: January 3, 2018

14.8K
A Method for Tracking the Time Evolution of Steady-State Evoked Potentials
12:03

A Method for Tracking the Time Evolution of Steady-State Evoked Potentials

Published on: May 25, 2019

8.4K

科学领域:

  • 航空航天工程 航空航天工程
  • 控制系统 控制系统
  • 信号处理 信号处理

背景情况:

  • 空间目标运动模型高度非线性,导致与传统卡尔曼波器的分歧.
  • 无气味卡尔曼波器 (UKF) 解决了非线性,但与时间变化或未知测量噪声作斗争,降低了跟踪精度.

研究的目的:

  • 开发一种适应性噪声因子方法,以增强无气味卡尔曼波器用于空间目标跟踪.
  • 为了减轻时间变化的测量噪声对跟踪精度和状态向量表示的影响.

主要方法:

  • 建议采用适应性噪声因子方法,与无香卡尔曼波器集成.
  • 该方法通过自适应性调整测量噪声共变矩阵.
  • 数字模拟使用来自太空红外卫星和地面雷达的测量模型.

主要成果:

  • 适应性噪声因子方法证明了适应时间变化的测量噪声的能力.
  • 与标准的无气味卡尔曼波器相比,在空间目标跟踪方面获得了更高的准确性.
  • 保持了空间目标状态向量的事后平均值和共变量的准确表示.

结论:

  • 拟议的自适应噪声因子方法有效地改善了在时间变化的测量噪声条件下空间目标跟踪.
  • 这种方法为测量噪声特征是动态或不确定的场景提供了可靠的解决方案.
  • 该方法提高了复杂环境中的目标追踪系统的可靠性和精度.