Data Association for Multiple Sensor Types Using Fuzzy Logic

Stubberud, Stephen C.; Kramer, Kathleen A.

doi:10.1109/tim.2006.887037

Cited by 33 publications

(12 citation statements)

References 7 publications

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“…[71,72] describe a fuzzy association strategy augmented to accommodate a variable scale target location region. Information such as bathymetric data is used to describe the influence on location possibilities of a submarine or a ship.…”

Section: Data Associationmentioning

confidence: 99%

Context-based Information Fusion: A survey and discussion

2015

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This survey aims to provide a comprehensive status of recent and current research on context-based Information Fusion (IF) systems, tracing back the roots of the original thinking behind the development of the concept of ''context''. It shows how its fortune in the distributed computing world eventually per-meated in the world of IF, discussing the current strategies and techniques, and hinting possible future trends. IF processes can represent context at different levels (structural and physical constraints of the scenario, a priori known operational rules between entities and environment, dynamic relationships modelled to interpret the system output, etc.). In addition to the survey, several novel context exploita-tion dynamics and architectural aspects peculiar to the fusion domain are presented and discussed.

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Section: Data Associationmentioning

confidence: 99%

Context-based Information Fusion: A survey and discussion

2015

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“…At present, algorithm research studies for long-term vessel tracking mainly center on segment association, which can be divided into two categories: one is based on statistics [5][6][7][8][9]; the other is based on fuzzy mathematics [10][11][12][13]. The former takes the difference of the state estimation as the statistic, establishes the hypothesis, and then uses the given probability to accept or reject the hypothesis to determine whether the track is associated or not.…”

Section: Introductionmentioning

confidence: 99%

“…Ashraf et al [10] presented a fuzzy correlation approach on the basis of the fuzzy clustering means algorithm. Stubberud et al [11] proposed a straightforward fuzzy-logic-based association method based on the chi 2 metric. Shao et al [12] used fuzzy k-nearest neighbors and fuzzy C-means clustering to achieve track segment association.…”

Section: Introductionmentioning

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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“…The main objective of any tracking system is to estimate and predict the target tracks. This is of interest in both civilian applications, such as civilian air traffic control, and military applications, such as air defense systems [1,2]. When tracking multiple targets, data association decides which of the received measurements to use to update each target track.…”

Section: Introductionmentioning

confidence: 99%

A Measurement Weighting Method for Tracking Military Objects

Aziz

Moghazy

El-Bakly

et al. 2009

International Conference on Aerospace Sciences and Aviation Tec

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Prior methods for tracking multiple military objects include various optimal and suboptimal two-dimensional assignment algorithms which make nearest-neighbour measurement-to-track association. This method works reasonably well in case of small number of targets and high signal to noise ratio. Another method is to assign a weight for each measurement and use a weighted centroid of those measurements to update the track. This method of weighting the measurements is known as all-neighbour and overcomes the disadvantages of the nearest-neighbour data association. Unfortunately, the computational complexity of an optimal all-neighbour data association technique limits its practical realization using even the fastest computers available. For this reason, many different tracking techniques have been developed which sacrifice optimal performance for the sake of computational feasibility. This paper proposes a new computationally feasible measurement weighting method to the problem of multiple targets tracking in a noisy environment. Computer simulation results indicate that the proposed weighting method successfully tracks multiple targets with a lower computational complexity and a little prior knowledge.

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Data Association for Multiple Sensor Types Using Fuzzy Logic

Cited by 33 publications

References 7 publications

Context-based Information Fusion: A survey and discussion

Context-based Information Fusion: A survey and discussion

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

A Measurement Weighting Method for Tracking Military Objects

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