Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Upsampling01:22

Upsampling

568
Managing signal sampling rates is essential in digital signal processing to maintain signal integrity. A decimated signal, characterized by a reduced frequency range due to its lower sampling rate, can be upsampled by inserting zeros between each sample. This upsampling process expands the original spectrum and introduces repeated spectral replicas at intervals dictated by the new Nyquist frequency. To refine this zero-inserted sequence, it is passed through a lowpass filter with a cutoff...
568
Aliasing01:18

Aliasing

523
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...
523
Reconstruction of Signal using Interpolation01:10

Reconstruction of Signal using Interpolation

661
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...
661
Sampling Theorem01:15

Sampling Theorem

1.2K
In signal processing, the analysis of continuous-time signals, denoted as x(t), often involves sampling techniques to convert these signals into discrete-time signals. This process is essential for digital representation and manipulation. A critical component in sampling is the train of impulses, characterized by the sampling interval and the sampling frequency. The relationship between these parameters and the original signal's properties dictates the success of the sampling process.
1.2K
Bandpass Sampling01:17

Bandpass Sampling

457
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....
457
Linear Approximation in Frequency Domain01:26

Linear Approximation in Frequency Domain

329
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....
329

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Consensus in Motion: Real-Time Insights From the SICCMII/ISASS 2025 Symposium on Endoscopic Spine Surgery.

International journal of spine surgery·2026
Same author

Isolation of the YB strain of canine distemper virus from Yanbian, China: analysis of JAK2-STAT3 signaling and NLRP3 inflammasome activation in infected cells.

The Journal of veterinary medical science·2026
Same author

Identification of anoikis-related subtypes in hepatocellular carcinoma and construction of prognostic model: Construction of prognostic model.

Medicine·2026
Same author

PPP1CC Suppresses Preadipocyte Differentiation in Chickens at Least Partly by Regulating NRF1 Expression.

Genes·2026
Same author

Neu1 inhibition restrains BCoV replication and modulates ZBP1-dependent PANoptosis.

Veterinary research·2026
Same author

Development and internal validation of a clinical prediction model for venous thromboembolism in patients with renal insufficiency.

Scientific reports·2026
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
See all related articles

Related Experiment Video

Updated: Jan 9, 2026

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform
06:25

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform

Published on: February 12, 2014

8.8K

High-Resolution Low-Sidelobe Waveform Design Based on HFPFM Coding Model for SAR.

Yu Gao1, Guodong Jin1,2, Xifeng Zhang1

  • 1Key Laboratory of Radar Imaging and Microwave Photonics, Ministry of Education, Nanjing University of Aeronautics and Astronautics, Nanjing 211116, China.

Sensors (Basel, Switzerland)
|December 11, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces an optimized High-Freedom Parameterized Frequency Modulation (HFPFM) waveform for synthetic aperture radar (SAR) systems. The new waveform significantly reduces sidelobes, improving target imaging without sacrificing resolution or signal-to-noise ratio.

Keywords:
HFPFM coding modelSAR imaginggradient descenthigh-resolutionlow-sidelobewaveform optimization design

More Related Videos

A Multimodal Wide-Field Fourier-Transform Raman Microscope
06:46

A Multimodal Wide-Field Fourier-Transform Raman Microscope

Published on: December 30, 2025

16
Real-time Monitoring of High Intensity Focused Ultrasound HIFU Ablation of In Vitro Canine Livers Using Harmonic Motion Imaging for Focused Ultrasound HMIFU
07:38

Real-time Monitoring of High Intensity Focused Ultrasound HIFU Ablation of In Vitro Canine Livers Using Harmonic Motion Imaging for Focused Ultrasound HMIFU

Published on: November 3, 2015

10.4K

Related Experiment Videos

Last Updated: Jan 9, 2026

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform
06:25

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform

Published on: February 12, 2014

8.8K
A Multimodal Wide-Field Fourier-Transform Raman Microscope
06:46

A Multimodal Wide-Field Fourier-Transform Raman Microscope

Published on: December 30, 2025

16
Real-time Monitoring of High Intensity Focused Ultrasound HIFU Ablation of In Vitro Canine Livers Using Harmonic Motion Imaging for Focused Ultrasound HMIFU
07:38

Real-time Monitoring of High Intensity Focused Ultrasound HIFU Ablation of In Vitro Canine Livers Using Harmonic Motion Imaging for Focused Ultrasound HMIFU

Published on: November 3, 2015

10.4K

Area of Science:

  • Radar systems engineering
  • Signal processing
  • Electromagnetics

Background:

  • Synthetic aperture radar (SAR) traditionally uses linear frequency modulation (LFM) waveforms.
  • Window functions used with LFM degrade signal-to-noise ratio (SNR) and resolution for sidelobe suppression.
  • Nonlinear frequency modulation (NLFM) waveforms offer sidelobe suppression without SNR loss but can still cause resolution loss.

Purpose of the Study:

  • To develop an advanced waveform design for SAR systems that overcomes the limitations of LFM and NLFM.
  • To optimize radar waveforms for enhanced sidelobe suppression without compromising mainlobe width, resolution, or SNR.
  • To introduce a novel High-Freedom Parameterized Frequency Modulation (HFPFM) coding model for waveform optimization.

Main Methods:

  • Constructed a waveform sidelobe optimization model based on the HFPFM coding model.
  • Applied constraints to prevent mainlobe widening during optimization.
  • Solved the optimization model using a gradient descent method.
  • Utilized matrix multiplication and fast Fourier transform (FFT)/inverse fast Fourier transform (IFFT) for efficient parameter optimization.

Main Results:

  • The optimized HFPFM waveform achieved over 9 dB of sidelobe reduction compared to LFM waveforms.
  • The optimization successfully avoided mainlobe widening, preserving resolution.
  • The method simultaneously mitigated resolution and SNR losses typically associated with window function weighting.
  • SAR point target imaging simulations demonstrated the ability to clearly image weak targets near strong targets.

Conclusions:

  • The proposed HFPFM waveform optimization method effectively enhances SAR imaging performance.
  • This approach provides a superior alternative to traditional LFM and NLFM waveforms by improving sidelobe suppression and maintaining resolution and SNR.
  • The optimized waveform enables clearer imaging of complex targets, proving the method's practical effectiveness.