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

You might also read

Related Articles

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

Sort by
Same author

Self-Powered, Broadband, and Polarization-Sensitive Photodetector Based on the ReSe<sub>2</sub>/Ta<sub>2</sub>NiSe<sub>5</sub> van der Waals Heterojunction.

ACS applied materials & interfaces·2026
Same author

PatientEvent: An Event-Based Ontology for Patient-Initiated Portal Communication.

medRxiv : the preprint server for health sciences·2026
Same author

Letter to the editor regarding "Romosozumab versus teriparatide and risk of all-cause mortality in patients with osteoporosis: a real-world propensity score-matched cohort study".

Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA·2026
Same author

Kushenol E alleviates sepsis-associated cognitive dysfunction via microglial indoleamine 2,3-dioxygenase 1 inhibition.

Phytomedicine : international journal of phytotherapy and phytopharmacology·2026
Same author

Interface Engineering and Substitutional Doping in In<sub>2</sub>Ge<sub>2</sub>Te<sub>6</sub> for High-Performance 2D p-Type FETs and CMOS Devices.

Small (Weinheim an der Bergstrasse, Germany)·2026
Same author

Physicochemical Properties, Volatile Components, and Biological Evaluation on Lavender Monofloral Honey From Xinjiang, China.

Journal of food science·2026
Same journal

A tri-axis optomechanical accelerometer with plasmonic MIM waveguide and structural direction-dependent optical signatures.

Scientific reports·2026
Same journal

Holographic leaky-wave antennas with independently controlled multiple counter-rotating vortex beams.

Scientific reports·2026
Same journal

Differential associations of longitudinal hearing and vision trajectories with dementia and mild cognitive impairment in older adults.

Scientific reports·2026
Same journal

Abdominal obesity and leisure-time sedentary behavior in relation to gastroesophageal reflux disease risk: a prospective cohort study from the UK Biobank.

Scientific reports·2026
Same journal

Effect of nitrogen-rich COF incorporation on the structure and separation performance of polyamide nanofiltration membranes.

Scientific reports·2026
Same journal

Withanolide A inhibits hIAPP aggregation: An In silico, biophysical, and drosophila-based In vivo validation.

Scientific reports·2026
See all related articles

Related Experiment Video

Updated: Jul 1, 2025

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

14.9K

Radar nonlinear multi-target tracking method with parallel PHD filter.

Jin Tao1,2, Defu Jiang3,4, Jialin Yang5,6

  • 1School of Computer and Information, Hohai University, Nanjing, 210098, China. taojin@hhu.edu.cn.

Scientific Reports
|March 4, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces a parallel Probability Hypothesis Density (PHD) filter for radar multi-target tracking (MTT). The method reduces estimation errors caused by differing target sampling times with lower computational cost.

More Related Videos

Tracking Infiltration Front Depth Using Time-lapse Multi-offset Gathers Collected with Array Antenna Ground Penetrating Radar
07:14

Tracking Infiltration Front Depth Using Time-lapse Multi-offset Gathers Collected with Array Antenna Ground Penetrating Radar

Published on: May 1, 2018

7.8K
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

8.5K

Related Experiment Videos

Last Updated: Jul 1, 2025

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

14.9K
Tracking Infiltration Front Depth Using Time-lapse Multi-offset Gathers Collected with Array Antenna Ground Penetrating Radar
07:14

Tracking Infiltration Front Depth Using Time-lapse Multi-offset Gathers Collected with Array Antenna Ground Penetrating Radar

Published on: May 1, 2018

7.8K
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

8.5K

Area of Science:

  • Engineering
  • Computer Science
  • Signal Processing

Background:

  • Probability Hypothesis Density (PHD) filters are prevalent in radar multi-target tracking (MTT) due to their avoidance of explicit data association.
  • Existing PHD filters often assume uniform sampling times for all targets, which conflicts with radar's beam width limitations.
  • This uniform sampling can cause data mismatch, reducing the accuracy of radar MTT.

Purpose of the Study:

  • To propose a novel radar nonlinear multi-target tracking method using a parallel PHD filter.
  • To address and eliminate estimation errors arising from diverse target sampling times in radar MTT.
  • To achieve this with reduced computational expense and improved real-time performance.

Main Methods:

  • A parallel PHD filter approach is developed for radar nonlinear multi-target tracking.
  • The measurement area is spatially partitioned into subspaces based on radar antenna beam width.
  • The PHD is computed in parallel across these subspaces, incorporating multi-feature radar echo information.

Main Results:

  • The proposed method effectively eliminates estimation errors caused by sampling time diversity in radar MTT.
  • The parallel PHD filter demonstrates reduced computational cost compared to existing methods.
  • Enhanced real-time performance and tracking accuracy were observed, particularly in cluttered environments.

Conclusions:

  • The parallel PHD filter offers a computationally efficient solution for radar multi-target tracking.
  • This approach mitigates accuracy degradation stemming from asynchronous target sampling.
  • The method shows significant promise for improving radar MTT, especially under challenging conditions.