Adaptive maneuvering target tracking with 2-HFSWR multisensor surveillance system

Zhang, Ling; Jiang, Yi; Li, Yingshuai; Li, Gangsheng; Ji, Yonggang

doi:10.1109/maes.2017.170033

Cited by 8 publications

(3 citation statements)

References 20 publications

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“…It means that the radar resolution varies with the radial distance. Each maneuver was randomly spread in the radar coverage to handle this variation by taking into account the Monte Carlo (MC) simulation as done in the work of Zhang et al [11]. Te MC simulation generated random initial positions and the heading of the ship.…”

Section: Methods Of Performancementioning

confidence: 99%

“…Secondly, the theoretical tracks produced by a specifc mathematical model are used to test the performance of the tracking algorithm [10]. An efort to include ship maneuvers has been proposed by Zhang et al with the assumption of constant velocity and constant turn of ship motion [11]. Te theoretical data are more controllable and provide a more exact ship position but a less natural characteristic of ship maneuvers.…”

Section: Introductionmentioning

confidence: 99%

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An Evaluation Method of Ship-Tracking Algorithms for High-Frequency Surface Wave Radar considering High Maneuvers Generated by the MMG Model

Iswandi

Hidayat

Wibowo

2023

Journal of Engineering

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Thelong-distance coverage of high-frequency surface wave radar (HFSWR) has promoted it as an enormous means for ship monitoring on the country’s maritime territory. Since it is a primaryradar, noncooperative targets can also be detected. However, this radar also has a shortcoming of low spatial and temporal resolutions due to the narrow available bandwidth in the HF band. This limitation can reduce the performance of ship detection and tracking, especially for highly maneuvering ships. This paper proposes a new method to assess the tracking algorithm for a high-maneuvering ship. The absence of a high-maneuvering plot in the AIS data and existing analytical models are replaced by the MMG model run on MANSIM software. The linear, turning, and zigzag motions are generated and used to evaluate the tracking algorithms. The Monte Carlo simulation was conducted regarding the degradation of spatial resolution in the higher radial range. The tracking performance was analyzed by calculating the RMSE of four parameters, i.e., absolute position, radial range, bearing angle, and speed. For a trial case, four tracking algorithms were evaluated, i.e., Kalman filter (KF), extended Kalman filter (EKF), unscented Kalman filter (UKF), and particle filter (PF). The evaluation results showed that the EKF tracker had a minor error for the linear track with RMSE of absolute position, radial range, bearing angle, and speed being 1.368 km, 0.526 km, 1.550°, and 0.005 m/s, respectively. Otherwise, the UKF performed slightly better than EKF for the high maneuver targets. The RMSE of absolute position, radial range, bearing angle, and speed were 1.649 km, 0.639 km, 1.919°, and 0.165 m/s, respectively. The results also ensure the applicability of the MMG model to evaluate the tracking algorithm’s performance in HFSWR.

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Section: Methods Of Performancementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An Evaluation Method of Ship-Tracking Algorithms for High-Frequency Surface Wave Radar considering High Maneuvers Generated by the MMG Model

Iswandi

Hidayat

Wibowo

2023

Journal of Engineering

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“…In this paper, we examine the vessel target tracking for stereoscopic HFSWR [22], which is shown in Figure 1. We consider the T-R/R mode, with one transmitting station and two receiving radar stations working independently along the coast.…”

Section: System Modelmentioning

confidence: 99%

Continuous Tracking of Targets for Stereoscopic HFSWR Based on IMM Filtering Combined with ELM

et al. 2020

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High frequency surface wave radar (HFSWR) plays an important role in marine surveillance on account of its ability to provide wide-range early warning detection. However, vessel target track breakages are common in large-scale marine monitoring, which limits the continuous tracking ability of HFSWR. The following are the possible reasons for track fracture: highly maneuverable vessels, dense channels, target occlusion, strong clutter/interference, long sampling intervals, and low detection probabilities. To solve this problem, we propose a long-term continuous tracking method for multiple targets with stereoscopic HFSWR based on an interacting multiple model extended Kalman filter (IMMEKF) combined with an extreme learning machine (ELM). When the trajectory obtained by IMMEKF breaks, a new section of the track will start on the basis of the observation data. For multiple-target tracking, a number of broken tracks can be obtained by IMMEKF tracking. Then the ELM classifies the segments from the same vessel by extracting different features including average velocity, average curvature, ratio of the arc length to the chord length, and wavelet coefficient. Both the simulation and the field experiment results validate the method presented here, showing that this method can achieve long-term continuous tracking for multiple vessels, with an average correct track segment association rate of over 91.2%, which is better than the tracking performance of conventional algorithms, especially when the vessels are in dense channels and strong clutter/interference area.

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Track Matching Based on ELM for HFSWR

Zhang

Wang

Niu

et al. 2019

2019 Chinese Automation Congress (CAC)

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Adaptive maneuvering target tracking with 2-HFSWR multisensor surveillance system

Cited by 8 publications

References 20 publications

An Evaluation Method of Ship-Tracking Algorithms for High-Frequency Surface Wave Radar considering High Maneuvers Generated by the MMG Model

An Evaluation Method of Ship-Tracking Algorithms for High-Frequency Surface Wave Radar considering High Maneuvers Generated by the MMG Model

Continuous Tracking of Targets for Stereoscopic HFSWR Based on IMM Filtering Combined with ELM

Track Matching Based on ELM for HFSWR

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