Multitarget multisensor closed-loop tracking

Sanders-Reed, John N.

doi:10.1117/12.542932

Cited by 7 publications

(6 citation statements)

References 31 publications

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“…Studies that specifically address closed-loop target tracking are gaining renewed interest from the research community [1][2][3]. Sanders-Reed [4] examined integration issues of a multitarget tracking system using video sensors and sensor-pointing commands to close the feedback loop. A more recent work by O'Rourke and Swindlehurst [5] demonstrated a closed feedback loop approach for multitarget tracking with the use of RF/EO sensors.…”

Section: Literature Reviewmentioning

confidence: 99%

Controlled tracking in urban terrain: Closing the loop

Barbosa

Sarkale

Chong

et al. 2019

Asian Journal of Control

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We investigate the challenging problem of integrating detection, signal processing, target tracking, and adaptive waveform scheduling with lookahead in urban terrain. We propose a closed-loop active sensing system to address this problem by exploiting three distinct levels of diversity: (1) spatial diversity through the use of coordinated multistatic radars; (2) waveform diversity by adaptively scheduling the transmitted waveform; and (3) motion model diversity by using a bank of parallel filters matched to different motion models. Specifically, at every radar scan, the waveform that yields the minimum trace of the one-step-ahead error covariance matrix is transmitted; the received signal goes through a matched-filter, and curve fitting is used to extract range and range-rate measurements that feed the LMIPDA-VSIMM algorithm for data association and filtering. Monte Carlo simulations demonstrate the effectiveness of the proposed system in an urban scenario contaminated by dense and uneven clutter, strong multipath, and limited line-of-sight.

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Section: Literature Reviewmentioning

confidence: 99%

Controlled tracking in urban terrain: Closing the loop

Barbosa

Sarkale

Chong

et al. 2019

Asian Journal of Control

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“…Sanders-Reed examined integration issues of a multitarget tracking system using video sensors and sensor-pointing commands to close the feedback loop. 7 Computational aspects of how Matlab/Simulink can be used to develop a closed-loop image-based tracker of airborne targets were the focus of Robinson and Sasaki. 8 An overview of systems-level modeling for the performance evaluation of closed-loop tracking systems for naval applications was given by Beeton and Hall.…”

Section: Introductionmentioning

confidence: 99%

Multitarget-multisensor tracking in an urban environment: a closed-loop approach

et al. 2008

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When compared to tracking airborne targets, tracking ground targets on urban terrains brings a new set of challenges. Target mobility is constrained by road networks, and the quality of measurements is affected by dense clutter, multipath, and limited line-of-sight. We investigate the integration of detection, signal processing, tracking, and scheduling by exploiting distinct levels of diversity: (1) spatial diversity through the use of coordinated multistatic radars; (2) waveform diversity by adaptively scheduling the transmitted radar waveform according to the scene conditions; and (3) motion model diversity by using a bank of parallel filters, each one matched to a different maneuvering model. Specifically, at each scan, the waveform that yields the minimum one-step-ahead error covariance matrix determinant is transmitted; the received signal is then matched-filtered, and quadratic curve fitting is applied to extract range and azimuth measurements that are input to the LMIPDA-VSIMM algorithm for data association and filtering. Monte Carlo simulations are used to demonstrate the effectiveness of the proposed system on a realistic urban scenario. A more traditional open-loop system, in which waveforms are scheduled on a round-robin fashion and with no other modes of diversity available, is used as a baseline for comparison. Simulation results show that our closed-loop system significantly outperforms the baseline system, presenting both a reduction on the number of lost tracks, and a reduction on the volume of the estimation uncertainty ellipse. The interdisciplinary nature of this work highlights the challenges involved in designing a closed-loop active sensing platform for next-generation urban tracking systems.

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“…2 It is inaccurate when the target velocity is low relative to the ATP system. In this paper, we define the target frontal by combining the moving direction and the angle of the target principal axis.…”

Section: Stable Tracking Point Extractionmentioning

confidence: 99%

“…1,2 Many attempts have been made to improve the stability of the tracking point extraction, especially for the extended target. [3][4][5] For targets that extend beyond the track gate, the leading edge tracking algorithm is a robust approach that can quickly find and settle on the target nose.…”

Section: Introductionmentioning

confidence: 99%

Stable tracking point extraction for infrared extended target based on contour smoothing and minimal inscribed circle

et al. 2013

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Abstract. An approach is proposed to reduce the tracking jitter of the extended target in boost phase for plume tracker in a photoelectric acquisition, tracking, and pointing system. The characteristics of the vehicle imaging are analyzed and the causes of jitters are identified. The target moving direction and its principal axis are combined to calculate the optimal frontal direction. A contour smoothing method based on the chord-arc ratio filtering is introduced to obtain a preliminary extraction point with lower jitters. Then a fine tracking point extraction method based on the minimal inscribed circle of contour after filtering is presented. Experimental results confirm that the proposed method significantly improves the tracking precision and stability. © The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

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Multitarget multisensor closed-loop tracking

Cited by 7 publications

References 31 publications

Controlled tracking in urban terrain: Closing the loop

Controlled tracking in urban terrain: Closing the loop

Multitarget-multisensor tracking in an urban environment: a closed-loop approach

Stable tracking point extraction for infrared extended target based on contour smoothing and minimal inscribed circle

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