An alpha‐beta tracking filter combined with maneuver‐driven circular prediction

Kawase, T.; Tsurunosono, Hideshi; Ehara, Naoki; Sasase, Iwao

doi:10.1002/(sici)1520-6424(199710)80:10<1::aid-ecja1>3.3.co;2-y

Cited by 3 publications

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“…On the other hand, Interacting Multiple-Model with Input Estimator (IMMIE) has been proposed [13]. IMMIE employs multiple Kalman filters that have different acceleration parameters and take account of parallel and vertical acceleration vectors to the velocity vector.…”

Section: Introductionmentioning

confidence: 99%

A Kalman tracker with a turning acceleration estimator

Kawase

Tsurunosono

Ehara

et al. 2000

Electron. Comm. Jpn. Pt. I

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In tracking systems using phased array antennas, the simple Kalman filter has been employed due to the development of high‐speed computers in recent years. The Kalman filter performs almost perfect tracking when a target takes a straight course. However, the quality of the Kalman filter degrades significantly for maneuvering targets since the statistics of acceleration are assumed to be a white Gaussian process in the filter. The Kalman tracker with a simple input estimator and the two‐stage Kalman estimator have been proposed for maneuvering target tracking that uses the residuals to estimate the target acceleration and that requires no a priori information of the magnitude of the maneuver. However, the estimate of the acceleration might not be accurate in the case that the residues increase dramatically such as the circular turn. In this paper, a Kalman tracker with a turning acceleration estimator is proposed that estimates the turning acceleration directly from the feature of the maneuvering target trajectory. A computer simulation is performed for various target profiles to show the effectiveness of the proposed tracker as compared with conventional trackers. © 2000 Scripta Technica, Electron Comm Jpn Pt 1, 84(1): 1–11, 2001

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Section: Introductionmentioning

confidence: 99%

A Kalman tracker with a turning acceleration estimator

Kawase

Tsurunosono

Ehara

et al. 2000

Electron. Comm. Jpn. Pt. I

Self Cite

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“…[ r;+111; = F i q i ; (4) where Z k l k is the smoothed value of xi; at sample k and k1 kS11i; is the linear prediction of z k at sample k + l . K The principle of the circular prediction filter is shown in Fig.?.…”

Section: A N Adaptivie-gain Alpha-beta Tracker Combined With Circularmentioning

confidence: 99%

“…To track snch a target. t l i c (1-3 tracking filter combined with maneuver-driven circ.iilar prediction which takes the linear prediction together with circular prcdiction can be used [4]. Both prediction filt c r s i i~ t h e same smoothed position and velocity.…”

Section: Introductionmentioning

confidence: 99%

An adaptive-gain alpha-beta tracker combined with circular prediction for maneuvering target tracking

Kawase

Tsurunosono

Ehara

et al.

TENCON '97 Brisbane - Australia. Proceedings of IEEE TENCON '97. IEEE Region 10 Annual Conference. Speech and Image Technologie

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iln atlaptive-gain 0-9 tracker cornbined with circular prediction for maneuvering target tracking is proposed as a nonlinear prediction filer. For track-while-scan systems using phased array antenna, the reduction of prediction error is ill1 very important issutr. The purpose of this scheme ir t o achieve good noise reduction and get better maneu-\ c:r-following capability. Simulation results for several targci profilcs arc. incliided for a comparison of the perfortniiiices of our proposed scheme with that of conventional I r i d i t i g filters.

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A New Prediction Algorithm for Embedded Real-Time Applications

Gracia

Pérez-Vidal

2010

IEICE Trans. Fundamentals

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An alpha‐beta tracking filter combined with maneuver‐driven circular prediction

Cited by 3 publications

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A Kalman tracker with a turning acceleration estimator

A Kalman tracker with a turning acceleration estimator

An adaptive-gain alpha-beta tracker combined with circular prediction for maneuvering target tracking

A New Prediction Algorithm for Embedded Real-Time Applications

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