Multiple Hypothesis Tracking Algorithm Based on Amplitude-Phase Measurement Information Assistance

In range gate pull off (RGPO) jamming scenarios, conventional multiple target tracking algorithm can not effectively distinguish the RGPO deception from real target measurements, resulting in track mis-initialization, increased tracking error, and tracking discontinuity. This paper proposes an information-assisted multiple hypothesis tracking (IA-MHT) algorithm to solve the above problems. The IA-MHT algorithm utilizes amplitude and phase information of radar measurements to distinguish between true and false measurements of targets. Furthermore, the algorithm adjusts the calculation method of global association hypothesis probabilities and track scores, which improves the tracking performance under clutter and RGPO interferences. Simulation results show that the IA-MHT algorithm can effectively distinguish the RGPO deception measurements and obtain superior data association performance compared to the conventional MHT algorithm.

Institutions

Publication Details

Journal
SHILAP Revista de lepidopterología
Published
2024-10-01
DOI
https://doi.org/10.12132/issn.1673-5048.2024.0078
Primary Topic
Target Tracking and Data Fusion in Sensor Networks
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Multiple Hypothesis Tracking Algorithm Based on Amplitude-Phase Measurement Information Assistance

SHILAP Revista de lepidopterología
Target Tracking and Data Fusion in Sensor Networks
article

Multiple Hypothesis Tracking Algorithm Based on Amplitude-Phase Measurement Information Assistance

article en

Abstract

In range gate pull off (RGPO) jamming scenarios, conventional multiple target tracking algorithm can not effectively distinguish the RGPO deception from real target measurements, resulting in track mis-initialization, increased tracking error, and tracking discontinuity. This paper proposes an information-assisted multiple hypothesis tracking (IA-MHT) algorithm to solve the above problems. The IA-MHT algorithm utilizes amplitude and phase information of radar measurements to distinguish between true and false measurements of targets. Furthermore, the algorithm adjusts the calculation method of global association hypothesis probabilities and track scores, which improves the tracking performance under clutter and RGPO interferences. Simulation results show that the IA-MHT algorithm can effectively distinguish the RGPO deception measurements and obtain superior data association performance compared to the conventional MHT algorithm.

SHILAP Revista de lepidopterología
Air Force Engineering University (CN)
Peace, Justice and strong institutions
Openalex Percentile: Top 64%
Target Tracking and Data Fusion in Sensor Networks
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.