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31375

Comparison between Kalman Filter and PHD Filter in Multi-target Tracking

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Last updated: 04 Jan 2025

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Abstract

Tracking a maneuvering target weakens the performance of predictive-model-based Bayesian state estimators (Kalman Filter). Therefore, the Probability Hypothesis Density (PHD) filter was proposed to overcome this problem. In this paper, the performance of Kalman filter, modified Kalman filter, and PHD filter in tracking a highly maneuverable target is shown. All three algorithms to track a maneuverable target are applied. Monte Carlo simulation showed that the PHD filter provides promising performance compared to Kalman filter. In particular, the algorithm is capable of tracking multiple crossing maneuvering targets.

DOI

10.21608/iceeng.2012.31375

Keywords

Multi-target Tracking, Kalman filter, Probability Hypothesis Density (PHD Filter)

Authors

First Name

M.

Last Name

Nabil

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Affiliation

M.Sc. student, Military Technical College, Cairo, Egypt.

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Orcid

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First Name

H.

Last Name

Kamal

MiddleName

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Affiliation

Department of Radar staff (Ph.D.), Military Technical College, Cairo, Egypt.

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Orcid

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First Name

M.

Last Name

Hassan

MiddleName

-

Affiliation

Department of Radar staff (Ph.D.), Military Technical College, Cairo, Egypt.

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Volume

8

Article Issue

8th International Conference on Electrical Engineering ICEENG 2012

Related Issue

5272

Issue Date

2012-05-01

Receive Date

2019-05-08

Publish Date

2012-05-01

Page Start

1

Page End

14

Print ISSN

2636-4433

Online ISSN

2636-4441

Article File

ICEENG_Volume 8_Issue 8th International Conference on Electrical Engineering ICE….pdf

PDF . 248.1kB

Link

https://iceeng.journals.ekb.eg/article_31375.html

Detail API

https://iceeng.journals.ekb.eg/service?article_code=31375

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75

Type

Original Article

Type Code

833

Publication Type

Journal

Publication Title

The International Conference on Electrical Engineering

Publication Link

https://iceeng.journals.ekb.eg/

MainTitle

Comparison between Kalman Filter and PHD Filter in Multi-target Tracking

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Article

Created At

22 Jan 2023