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相关概念视频

Properties of Fourier Transform II01:24

Properties of Fourier Transform II

172
The Fourier Transform (FT) is an essential mathematical tool in signal processing, transforming a time-domain signal into its frequency-domain representation. This transformation elucidates the relationship between time and frequency domains through several properties, each revealing unique aspects of signal behavior.
The Frequency Shifting property of Fourier Transforms highlights that a shift in the frequency domain corresponds to a phase shift in the time domain. Mathematically, if x(t) has...
172
Passive Filters01:27

Passive Filters

521
Passive filters are utilized to shape the frequency spectrum of signals across a diverse array of applications. These filters, using only passive elements like resistors (R), inductors (L), and capacitors (C), are capable of selectively allowing or blocking certain frequency ranges without the need for external power sources.
Low-Pass Filters
Low-pass filters are designed to transmit signals with frequencies lower than the cutoff frequency, ωc, and attenuate those above it. The cutoff...
521
Properties of DTFT I01:24

Properties of DTFT I

367
In signal processing, Discrete-Time Fourier Transforms (DTFTs) play a critical role in analyzing discrete-time signals in the frequency domain. Various properties of the DTFTs such as linearity, time-shifting, frequency-shifting, time reversal, conjugation, and time scaling help understand and manipulate these signals for different applications.
The linearity property of DTFTs is fundamental. If two discrete-time signals are multiplied by constants a and b respectively, and then combined to...
367
Design Example01:23

Design Example

316
The innovation of touch-tone telephony revolutionized the telecommunications industry by replacing the traditional rotary dial with a dual-tone multi-frequency (DTMF) signaling system. This system uses a matrix-style keypad with buttons arranged in four rows and three columns, creating 12 distinct signals each assigned to a pair of frequencies. Each button press results in a simultaneous generation of two sinusoidal tones – one from a low-frequency group (697 to 941 Hz) and one from a...
316
Double Resonance Techniques: Overview01:12

Double Resonance Techniques: Overview

191
Double resonance techniques in Nuclear Magnetic Resonance (NMR) spectroscopy involve the simultaneous application of two different frequencies or radiofrequency pulses to manipulate and observe two distinct nuclear spins. One important application of double resonance is spin decoupling, which selectively suppresses coupling with one type of nucleus while observing the NMR signal from another nucleus, simplifying the spectrum and enhancing resolution.
Spin decoupling is usually achieved by...
191
Time and frequency -Domain Interpretation of Phase-lead Control01:24

Time and frequency -Domain Interpretation of Phase-lead Control

76
Phase-lead controllers are commonly used in various control systems to enhance response speed and stability. Adjusting the brightness on a television screen offers a practical example of phase-lead control. When contrast is enhanced, a phase-lead controller is employed. Mathematically, phase-lead control is identified when the first parameter is smaller than the second.
The design of phase-lead control involves the strategic placement of poles and zeros to balance steady-state error and system...
76

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相关实验视频

Updated: Jun 6, 2025

Tracking Infiltration Front Depth Using Time-lapse Multi-offset Gathers Collected with Array Antenna Ground Penetrating Radar
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分布式被动定位和分类方法用于多网络频率跳跃时间分割多访问信号多访问信号.

Jiaqi Mao1,2, Feng Luo1, Xiaoquan Hu2

  • 1National Key Laboratory of Radar Signal Processing, Xidian University, Xi'an 710071, China.

Sensors (Basel, Switzerland)
|November 27, 2024
PubMed
概括
此摘要是机器生成的。

这项研究引入了一种用于准确定位辐射源和分类来自多个站的信号的新方法,即使具有具有挑战性的宽带频率跳跃信号. 该方法提高了定位和分类性能,特别是在低信号对噪声条件下.

关键词:
这是一个TDMA信号.交叉模两可的功能 (CAF)改进了K-平均值方法.网络站 排序 分类 网络站被动定位是一种被动定位.

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相关实验视频

Last Updated: Jun 6, 2025

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科学领域:

  • 信号处理 信号处理
  • 电磁学 电磁学 电磁学 电磁学
  • 阵列信号处理 阵列信号处理

背景情况:

  • 目前的方法难以准确地定位和分类宽带辐射源,频率跳跃信号,特别是来自多个网络站的信号.
  • 挑战包括波形别名和快速频率跳跃,在复杂的信号环境中降低性能.

研究的目的:

  • 为宽带频率跳跃信号提出分布式被动定位和网络站分类方法.
  • 解决当前技术的局限性,以在具有挑战性的条件下准确地定位源和信号分类.

主要方法:

  • 采用两级参数估计和联合聚类方法.
  • 一个两阶段的过结构是为频率点控制过设计的.
  • 使用自适应值检测,交叉模糊函数 (CAF) 来估计到达时间差异 (TDOA) 和到达速度差异 (VDOA),以及改进的K-means集群.

主要成果:

  • 拟议的方法实现了宽带频率跳跃信号的准确定位和有效信号分类.
  • 与现有方法相比,在低信号对噪声 (SNR) 和低快照条件下表现出优异的性能.
  • 成功分类来自不同网络站的信号,使用分布式联合自向量和改进的K-平均值.

结论:

  • 开发的方法为复杂的电磁环境中的被动定位和信号分类提供了强大的解决方案.
  • 它显著提高了定位精度和信号分类效率,特别是在不利的SNR和数据限制下.
  • 这项工作提高了来自分布式网络站的信号管理和分析能力.