An Efficient Multi-Path Multitarget Tracking Algorithm for Over-The-Horizon Radar

Huang, Yuan; Shi, Yi Fang; Song, Taek Lyul

doi:10.3390/s19061384

Cited by 14 publications

(4 citation statements)

References 25 publications

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“…Traditional MTT algorithms suffer from high computational loads in such environments, as they must list all possible joint measures-to track assignments taking into account the measurement paths. To competently track multi-target in multiple detection environments, authors in [16] have proposed a new approach, named multipath linear multi-target integrated probabilistic data association (MP-LM-IPDA), instead of engendering all possible joint assignment scenarios.…”

Section: • Relatedworkmentioning

confidence: 99%

Improved multi-target tracking crossing paths in MIMO FMCW 8 × 16 radar system using a new hybrid AMC-JPDAF algorithm

Zarai

Abdallah

Cherif

2023

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This paper addresses the multi-target tracking problem in a multiple-input multiple-output radar system. Different tracking sensor measurements often encounter complex data as well correlation problems. Our goal is to solve this dilemma, which appears to be a new technical challenge; fix object-tracking scenarios while avoiding divergence. Once the cross-path phenomenon occurs, the target measurement assignment process in MIMO radar systems becomes more complicated. Therefore, this interference phenomenon can disturb the received signal and miss the state estimation process. To avoid all the mentioned problems, we have improved a new hybrid algorithm based on the particle filter; Adaptive Monte Carlo has been used in conjunction with the Joint Probabilistic Data Association Filter to substitute the classical extended KALMAN filter combined with JPDAF known as EKF-JPDAF. Experimental results of our MIMO-FMCW radar system with AMC-JPDAF converge to a more accurate state estimate while avoiding divergence. Using MATLAB software development framework, the designed system meets the goals originally set by AMC-JPDAF by referring to the experimental database obtained from the MIMO-FMCW 8x16 radar system.

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Section: • Relatedworkmentioning

confidence: 99%

Improved multi-target tracking crossing paths in MIMO FMCW 8 × 16 radar system using a new hybrid AMC-JPDAF algorithm

Zarai

Abdallah

Cherif

2023

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“…Because of the special detection mechanism of OTHR, the real measured data often has the multipath effect [29]. In the radar range-Doppler image, such as Fig.…”

Section: ) Multi-aircraft Formation Simulationmentioning

confidence: 99%

Multi-Aircraft Formation Recognition Method of Over-the-Horizon Radar Based on Deep Transfer Learning

Liang¹,

Zhou²,

Li³

et al. 2022

IEEE Access

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Over-the-horizon radar (OTHR) is an important equipment for the ultralong-range early warning in the military, but the use of constant false-alarm rate (CFAR), which is a traditional detection method, makes it difficult in multiaircraft formation recognition. To solve this problem, a multi-aircraft formation recognition method based on deep transfer learning in OTHR is proposed. First, the range-Doppler images of aircraft formation in OTHR are simulated, which are composed of four categories of samples. Secondly, a recognition model based on Convolutional Neural Network (CNN) and CFAR detection technology is constructed, whose training method is designed as a two-step transfer. Finally, the trained model can well distinguish the spectral characteristics of aircraft formation, and then recognize the aircraft number of a formation. Experiments show that the proposed method is better than the traditional CFAR detection method, and can detect the number of aircraft more accurately in the formation with the same false alarm rate. INDEX TERMS multi-aircraft formation; range-Doppler image; OTHR; deep transfer learning

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“…The approaches in the first group assumed that each layer of the ionosphere is an ideal mirror, and the VIH of each layer is a known constant. Focusing on the multipath data association problem caused by the multilayer structure of the ionosphere, these approaches include the multipath probabilistic data association (MPDA) [4], the multiple detection multiple hypothesis tracker (MD-MHT) [7], the expectationmaximization (EM)-based joint multipath data association and state estimation (JMAE) [8], the multipath Bernoulli filter (MPBF) [9], the multidetection probability hypothesis density (MD-PHD) filter [10,11], and the multipath linear multitarget integrated probabilistic data association (MP-LM-IPDA) [12].…”

Section: Introductionmentioning

confidence: 99%

OTHR multitarget tracking with a GMRF model of ionospheric parameters

Guo

Wang

Lan

et al. 2020

Preprint

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The ionosphere is the propagation medium for radio waves transmitted by an over-the-horizon radar (OTHR). Ionospheric parameters, typically, virtual ionospheric heights (VIHs), are required to perform coordinate registration for OTHR multitarget tracking and localization. The inaccuracy of ionospheric parameters has a significant deleterious effect on the target localization of OTHR. Therefore, to improve the localization accuracy of OTHR, it is important to develop accurate models and estimation methods of ionospheric parameters and the corresponding target tracking algorithms. In this paper, we consider the variation of the ionosphere with location and the spatial correlation of the ionosphere in OTHR target tracking. We use a Gaussian Markov random field (GMRF) to model the VIHs, providing a more accurate representation of the VIHs for OTHR target tracking. Based on expectation-conditional maximization and GMRF modeling of the VIHs, we propose a novel joint optimization solution, called ECM-GMRF, to perform target state estimation, multipath data association and VIHs estimation simultaneously. In ECM-GMRF, the measurements from both ionosondes and OTHR are exploited to estimate the VIHs, leading to a better estimation of the VIHs which improves the accuracy of data association and target state estimation, and vice versa. The simulation indicates the effectiveness of the proposed algorithm.

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An Efficient Multi-Path Multitarget Tracking Algorithm for Over-The-Horizon Radar

Cited by 14 publications

References 25 publications

Improved multi-target tracking crossing paths in MIMO FMCW 8 × 16 radar system using a new hybrid AMC-JPDAF algorithm

Improved multi-target tracking crossing paths in MIMO FMCW 8 × 16 radar system using a new hybrid AMC-JPDAF algorithm

Multi-Aircraft Formation Recognition Method of Over-the-Horizon Radar Based on Deep Transfer Learning

OTHR multitarget tracking with a GMRF model of ionospheric parameters

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