An Information Geometry-Based Track-Before-Detect Algorithm for Range-Azimuth Measurements in Radar Systems

The detection of weak moving targets in heterogeneous clutter backgrounds is a significant challenge in radar systems. In this paper, we propose a track-before-detect (TBD) method based on information geometry (IG) theory applied to range-azimuth measurements, which extends the IG detectors to multi...

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Main Authors: Jinguo Liu, Hao Wu, Zheng Yang, Xiaoqiang Hua, Yongqiang Cheng
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Entropy
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Online Access:https://www.mdpi.com/1099-4300/27/6/637
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author Jinguo Liu
Hao Wu
Zheng Yang
Xiaoqiang Hua
Yongqiang Cheng
author_facet Jinguo Liu
Hao Wu
Zheng Yang
Xiaoqiang Hua
Yongqiang Cheng
author_sort Jinguo Liu
collection DOAJ
description The detection of weak moving targets in heterogeneous clutter backgrounds is a significant challenge in radar systems. In this paper, we propose a track-before-detect (TBD) method based on information geometry (IG) theory applied to range-azimuth measurements, which extends the IG detectors to multi-frame detection through inter-frame information integration. The approach capitalizes on the distinctive benefits of the information geometry detection framework in scenarios with strong clutter, while enhancing the integration of information across multiple frames within the TBD approach. Specifically, target and clutter trajectories in multi-frame range-azimuth measurements are modeled on the Hermitian positive definite (HPD) and power spectrum (PS) manifolds. A scoring function based on information geometry, which uses Kullback–Leibler (KL) divergence as a geometric metric, is then devised to assess these motion trajectories. Moreover, this study devises a solution framework employing dynamic programming (DP) with constraints on state transitions, culminating in an integrated merit function. This algorithm identifies target trajectories by maximizing the integrated merit function. Experimental validation using real-recorded sea clutter datasets showcases the effectiveness of the proposed algorithm, yielding a minimum 3 dB enhancement in signal-to-clutter ratio (SCR) compared to traditional approaches.
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publishDate 2025-06-01
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spelling doaj-art-fe71f4eda8f945f5a4ccef979661c6fa2025-08-20T03:27:07ZengMDPI AGEntropy1099-43002025-06-0127663710.3390/e27060637An Information Geometry-Based Track-Before-Detect Algorithm for Range-Azimuth Measurements in Radar SystemsJinguo Liu0Hao Wu1Zheng Yang2Xiaoqiang Hua3Yongqiang Cheng4College of Electronic Science and Technology, National University of Defense Technology, Changsha 410073, ChinaCollege of Electronic Science and Technology, National University of Defense Technology, Changsha 410073, ChinaCollege of Electronic Science and Technology, National University of Defense Technology, Changsha 410073, ChinaCollege of Electronic Science and Technology, National University of Defense Technology, Changsha 410073, ChinaCollege of Electronic Science and Technology, National University of Defense Technology, Changsha 410073, ChinaThe detection of weak moving targets in heterogeneous clutter backgrounds is a significant challenge in radar systems. In this paper, we propose a track-before-detect (TBD) method based on information geometry (IG) theory applied to range-azimuth measurements, which extends the IG detectors to multi-frame detection through inter-frame information integration. The approach capitalizes on the distinctive benefits of the information geometry detection framework in scenarios with strong clutter, while enhancing the integration of information across multiple frames within the TBD approach. Specifically, target and clutter trajectories in multi-frame range-azimuth measurements are modeled on the Hermitian positive definite (HPD) and power spectrum (PS) manifolds. A scoring function based on information geometry, which uses Kullback–Leibler (KL) divergence as a geometric metric, is then devised to assess these motion trajectories. Moreover, this study devises a solution framework employing dynamic programming (DP) with constraints on state transitions, culminating in an integrated merit function. This algorithm identifies target trajectories by maximizing the integrated merit function. Experimental validation using real-recorded sea clutter datasets showcases the effectiveness of the proposed algorithm, yielding a minimum 3 dB enhancement in signal-to-clutter ratio (SCR) compared to traditional approaches.https://www.mdpi.com/1099-4300/27/6/637multi-frame detectioninformation geometrytrack before detectdynamic programmingrange-azimuth measurementsKullback–Leibler divergence
spellingShingle Jinguo Liu
Hao Wu
Zheng Yang
Xiaoqiang Hua
Yongqiang Cheng
An Information Geometry-Based Track-Before-Detect Algorithm for Range-Azimuth Measurements in Radar Systems
Entropy
multi-frame detection
information geometry
track before detect
dynamic programming
range-azimuth measurements
Kullback–Leibler divergence
title An Information Geometry-Based Track-Before-Detect Algorithm for Range-Azimuth Measurements in Radar Systems
title_full An Information Geometry-Based Track-Before-Detect Algorithm for Range-Azimuth Measurements in Radar Systems
title_fullStr An Information Geometry-Based Track-Before-Detect Algorithm for Range-Azimuth Measurements in Radar Systems
title_full_unstemmed An Information Geometry-Based Track-Before-Detect Algorithm for Range-Azimuth Measurements in Radar Systems
title_short An Information Geometry-Based Track-Before-Detect Algorithm for Range-Azimuth Measurements in Radar Systems
title_sort information geometry based track before detect algorithm for range azimuth measurements in radar systems
topic multi-frame detection
information geometry
track before detect
dynamic programming
range-azimuth measurements
Kullback–Leibler divergence
url https://www.mdpi.com/1099-4300/27/6/637
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