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Related Concept Videos

Aliasing01:18

Aliasing

194
Accurate signal sampling and reconstruction are crucial in various signal-processing applications. A time-domain signal's spectrum can be revealed using its Fourier transform. When this signal is sampled at a specific frequency, it results in multiple scaled replicas of the original spectrum in the frequency domain. The spacing of these replicas is determined by the sampling frequency.
If the sampling frequency is below the Nyquist rate, these replicas overlap, preventing the original...
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¹³C NMR: ¹H–¹³C Decoupling01:04

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The probability of having two carbon-13 atoms next to each other is negligible because of the low natural abundance of carbon-13. Consequently, peak splitting due to carbon-carbon spin-spin coupling is not observed in spectra. However, protons up to three sigma bonds away split the carbon signal according to the n+1 rule, resulting in complicated spectra.
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Double Resonance Techniques: Overview01:12

Double Resonance Techniques: Overview

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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...
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Bandpass Sampling01:17

Bandpass Sampling

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In signal processing, bandpass sampling is an effective technique for sampling signals that have most of their energy concentrated within a narrow frequency band. This type of signal is known as a bandpass signal. The key principle of bandpass sampling involves sampling the signal at a rate that is greater than twice the signal's bandwidth to prevent aliasing.
A bandpass signal has a spectrum with a lower frequency limit, denoted as ω1, and an upper frequency limit, denoted as ω2....
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¹³C NMR: Distortionless Enhancement by Polarization Transfer (DEPT)01:20

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When proton-coupled carbon-13 spectra are simplified by a broadband proton decoupling technique, structural information about the coupled protons is lost. Distortionless enhancement by polarization transfer (DEPT) is a technique that provides information on the number of hydrogens attached to each carbon in a molecule. While the DEPT experiment utilizes complex pulse sequences, the pulse delay and flip angle are specifically manipulated. The resulting signals have different phases depending on...
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Removing False Targets for Cyclic Prefixed OFDM Sensing with Extended Ranging.

Kai Wu1, J Andrew Zhang1, Xiaojing Huang1

  • 1Global Big Data Technologies Centre (GBDTC), University of Technology Sydney (UTS), Sydney, NSW 2007, Australia.

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|November 26, 2022
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Summary
This summary is machine-generated.

This study addresses false targets in vehicular integrated sensing and communications (ISAC) using cyclic prefixed OFDM (CP-OFDM) waveforms. A new method effectively removes these false targets, reducing false alarms by over 50%.

Keywords:
OFDMcyclic prefix (CP)false targetsintegrated sensing and communications (ISAC)joint communications and sensing (JCAS)

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Area of Science:

  • Wireless communication
  • Signal processing
  • Radar sensing

Background:

  • Vehicular integrated sensing and communications (ISAC) increasingly uses cyclic prefixed Orthogonal Frequency Division Multiplexing (CP-OFDM) waveforms.
  • Recent advancements enable CP-OFDM sensing to exceed traditional communication limits.
  • A persistent challenge is the issue of false targets in CP-OFDM based sensing systems.

Purpose of the Study:

  • To investigate the root cause of false targets in CP-OFDM sensing.
  • To develop and validate a method for eliminating these false targets.
  • To improve the accuracy and reliability of ISAC systems.

Main Methods:

  • Analysis of CP-OFDM waveforms to identify the source of false targets.
  • Derivation of mathematical relationships between false and true target characteristics.
  • Development of a novel algorithm for false target removal.

Main Results:

  • False targets are definitively linked to the periodic nature of cyclic prefixes (CPs) in CP-OFDM waveforms.
  • The study establishes correlations between false target locations, strengths, and true targets.
  • The proposed solution demonstrates a significant reduction in false alarm rates.

Conclusions:

  • The periodic CPs in CP-OFDM are the cause of false targets in ISAC.
  • The developed method effectively mitigates false targets, enhancing sensing performance.
  • The proposed solution reduces false alarm rates by over 50% compared to existing methods, validating its effectiveness.