Image-enhanced tracking

Sworder, David D.; Hutchins, R.G.

doi:10.1109/7.42087

Cited by 75 publications

(16 citation statements)

References 6 publications

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“…9. In the tracking problem discussed here, the focus is on the orientation states and the manner in which the filter responds to the observed changes in these states, where there is a single target in the field of view.…”

Section: Filter Equations For the Imaging Datamentioning

confidence: 99%

Image fusion algorithms for tracking maneuvering targets

Hutchins

Sworder

1992

Journal of Guidance, Control, and Dynamics

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Evasive target maneuvers create problems for traditional state-space filtering and tracking algorithms because maneuver accelerations are frequently abrupt and are not well modeled by wideband noise processes. Earlier work has suggested the use of an imaging sensor to determine target orientation, from which the likely direction of a maneuver acceleration can be inferred. This paper examines the issues that arise when an image-based orientation measurement is used in conjunction with a traditional sensor/filter for enhanced detection of maneuvering accelerations and for prediction of target location.

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Section: Filter Equations For the Imaging Datamentioning

confidence: 99%

Image fusion algorithms for tracking maneuvering targets

Hutchins

Sworder

1992

Journal of Guidance, Control, and Dynamics

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“…Early attempts utilized such sensors as digital cameras to measure a target's orientation or attitude for maneuver detection [10,14]. Recently, the use of pose-sensitive classifiers based on range profiles from an HRR radar was proposed for this purpose [17].…”

Section: Introductionmentioning

confidence: 99%

A Net Track Solution to Pose-Angular Tracking of Maneuvering Targets in Clutter with HRR Radar

Yang¹,

Blasch

Garber³

et al. 2007

2007 Conference Record of the Forty-First Asilomar Conference on Signals, Systems and Computers

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Maintaining track continuity is a challenging task for large area persistent surveillance with high target density, rapid target maneuvering, and low target-to-clutter ratio. When the sensor revisit interval is long, measurement-to-track association becomes rather difficult. Although maneuvering targets can be discriminated via Doppler processing, clutter still masks moving targets at certain aspect angles. This creates a blind zone for GMTI (ground moving target indicator) radar, which may extend as large as 25% of the azimuth angles. For high-value targets that may undergo evasive maneuvers, a net track solution coordinating multiple looks from a netted set of sensors is set forth in this paper to ensure continuous monitoring. Target visibility therefore needs to be factored into netted radar platform coordination and sensor systems management. For ground targets, their heading is mostly aligned with the longitudinal axis. The target pose thus carries kinematic information about the direction of velocity vector that can be used to assist tracking of maneuvering targets. In this paper, the range profiles of high range resolution (HRR) radar are used for pose angular estimation of maneuvering targets in clutter. A pose-sensitive classifier provides matching scores that are converted into likelihoods and updated over time in a probabilistic manner. Pose angular tracking from individual sensors in the network is fused to cover the blind zone encountered by individual sensors. A software simulation environment that produces range profiles based on the RF signatures of moving targets is used in the study. Simulation results for pose angular tracking in clutter are presented to illustrate the net track solution concept and its performance.

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“…Synthetic Aperture Radar (SAR) image data can be processed to estimate target orientation that is used as additional information to estimate the target maneuvers [23]. Target orientation estimation from image data is presented in [24]. In [25], target orientation observations acquired from an image seeker and used for short-range air-to-air missile guidance problem.…”

Section: Introductionmentioning

confidence: 99%

Improved target tracking using kinematic measurements and target orientation information

Sutharsan

Kirubarajan

2009

SPIE Proceedings

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This paper discusses a target tracking system that provides improved estimates of target states using target orientation information in addition to standard kinematic measurements. The objective is to improve state estimation of highly maneuverable targets with noisy kinematic measurements. One limiting factor in obtaining accurate state estimates of highly maneuvering targets is the high level of uncertainty in velocity and acceleration. The target orientation information is helpful in alleviating this problem to accurately determine the velocity and acceleration components. However, there is no sensor that explicitly measures target orientation. In this paper, the Observable Operator Model (OOM) is used together with multiple sensor information to estimate target orientation measurement. This is done by processing the sensor feature measurements from different aspect angles and the estimated target orientation measurement is used in conjunction with kinematic measurements to conclusively estimate target states. Simulation results show that the incorporation of target orientation can enhance the tracking performance in the presence of fast moving and/or maneuvering targets. In addition, the Posterior Cramer-Rao lower bound (PCRLB) that quantifies the achievable performance is derived. It is shown that the proposed estimator meets the PCRLB.

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Image-enhanced tracking

Cited by 75 publications

References 6 publications

Image fusion algorithms for tracking maneuvering targets

Image fusion algorithms for tracking maneuvering targets

A Net Track Solution to Pose-Angular Tracking of Maneuvering Targets in Clutter with HRR Radar

Improved target tracking using kinematic measurements and target orientation information

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