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相关概念视频

Errors in Global Positioning System01:26

Errors in Global Positioning System

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Global Positioning System (GPS) technology has revolutionized navigation and positioning, but its accuracy is often compromised by various errors. These errors, stemming from environmental, satellite, and receiver-related factors, require careful mitigation to ensure reliable performance across applications.Atmospheric ErrorsGPS signals travel through the Earth’s ionosphere and troposphere, introducing delays which affect accuracy. The ionosphere is strongly influenced by charged particles,...
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Field Application of Global Positioning System01:28

Field Application of Global Positioning System

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The Global Positioning System (GPS) has become an indispensable tool in fieldwork, offering unparalleled precision and efficiency for surveying, navigation, and infrastructure development. By harnessing signals from a constellation of satellites, GPS receivers determine the location of objects with remarkable speed and accuracy, often completing calculations within a second.Advantages of Modern GPS TechnologyContemporary GPS receivers are designed to meet the practical demands of field...
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Linear Approximation in Frequency Domain01:26

Linear Approximation in Frequency Domain

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Linear systems are characterized by two main properties: superposition and homogeneity. Superposition allows the response to multiple inputs to be the sum of the responses to each individual input. Homogeneity ensures that scaling an input by a scalar results in the response being scaled by the same scalar.
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear....
91
Linear Approximation in Time Domain01:21

Linear Approximation in Time Domain

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Nonlinear systems often require sophisticated approaches for accurate modeling and analysis, with state-space representation being particularly effective. This method is especially useful for systems where variables and parameters vary with time or operating conditions, such as in a simple pendulum or a translational mechanical system with nonlinear springs.
For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length,...
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IR Spectrum Peak Splitting: Symmetric vs Asymmetric Vibrations01:08

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Identical bonds within a polyatomic group can stretch symmetrically (in-phase) or asymmetrically (out-of-phase). Similar to hydrogen bonding, these vibrations also influence the shape of the IR peak. Generally, asymmetric stretching frequencies are higher than symmetric stretching frequencies. For example, primary amines exhibit two distinct IR peaks between 3300–3500 cm−1 corresponding to the symmetric and asymmetric N-H stretching, while secondary amines exhibit a single...
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Signal processing techniques are essential for accurately converting continuous signals to digital formats and vice versa. When a continuous signal is sampled with a period T, the resulting sampled signal exhibits replicas of the original spectrum in the frequency domain, spaced at intervals equal to the sampling frequency. To handle this sampled signal, a zero-order hold method can be applied, which creates a piecewise constant signal by retaining each sample's value until the next...
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Updated: Jul 9, 2025

Tracking Infiltration Front Depth Using Time-lapse Multi-offset Gathers Collected with Array Antenna Ground Penetrating Radar
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基于数组信号子空间的自定位确定,适用于多路径环境下.

Zhongkang Cao1, Pan Li1, Wanghao Tang1

  • 1College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China.

Sensors (Basel, Switzerland)
|December 9, 2023
PubMed
概括
此摘要是机器生成的。

这项研究引入了一种新的阵列信号子空间配合方法,可以使用信号数据准确估计车辆位置,即使在具有挑战性的多路径环境中. 该方法有效地抑制非视线错误,提高定位精度和减少计算负载.

关键词:
阵列信号处理 阵列信号处理多路径环境 多路径环境不合作的信号信号.自定位确定自定位确定.

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科学领域:

  • 信号处理 信号处理
  • 导航系统 导航系统
  • 阵列信号处理 阵列信号处理

背景情况:

  • 车辆定位传统上依赖于卫星导航,但在多路径环境中面临挑战.
  • 现有的阵列自我定位确定方法由于多路径干扰而容易发生故障.

研究的目的:

  • 为强大的车辆定位提出一个阵列信号子空间安装方法.
  • 为了抑制信号接收中的多路径效应和非视线 (NLOS) 组件.
  • 为了提高定位准确性和减少计算复杂性.

主要方法:

  • 使用增强的空间平滑和根多个信号分类 (Root-MUSIC) 估计信号发生角度.
  • 使用K-means集群来区分非视线 (NLOS) 信号与多路径组件.
  • 使用带有 P 矩阵的信号子空间拟合 (SSF) 函数来减轻 NLOS 错误并缩小搜索区域.

主要成果:

  • 与C矩阵,斜投影,ISF,MUSIC和SSF相比,提出的方法表明NLOS组件的抑制优越.
  • 实现了至少7.64dB的计算复杂度降低.
  • 在多路径条件下,估计精度比聚类算法提高3.10dB,比MUSIC,ISF和SSF提高11.77dB.

结论:

  • 开发的阵列信号子空间安装方法为多路径环境中的车辆定位提供了增强的性能.
  • 整合K-means集群和SSF显著提高了准确性和效率.
  • 这种方法为卫星导航提供了一种可靠的替代方案,用于精确定位车辆.