Turn Rate Estimation Techniques in IMM Estimators for ESA Radar Tracking

Veeraraghavan, S.; Rathi, Aparna; Sagayaraj, M.J.; Nagar, C.V.R.

doi:10.1109/aero.2008.4526441

Cited by 5 publications

(2 citation statements)

References 11 publications

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“…The range profiles of a target are aspect dependent in the sense they vary with look angle. Classification of radar targets based on their HRRP has been studied [12][13][14][15][16][17][18][19][20] . A recent study using long short-term memory -recurrent neural network (LSTM-RNN) may be found in Sagayaraj 19 , et al Application of convolutional neural network (CNN) in radar target classification problems based on SAR images and micro doppler signatures have also been studied [23][24][25] .…”

Section: Case Studies 61 Radar Target Classification Based On High-rmentioning

confidence: 99%

A Hybrid Approach to Cognition in Radars

et al. 2018

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In many engineering domains, cognition is emerging to play vital role. Cognition will play crucial role in radar engineering as well for the development of next generation radars. In this paper, a cognitive architecture for radars is introduced, based on hybrid cognitive architectures. The paper proposes deep learning applications for integrated target classification based on high-resolution radar range profile measurements and target revisit time calculation as case studies. The proposed architecture is based on the artificial cognitive systems concepts and provides a basis for addressing cognition in radars, which is inadequately explored for radar systems. Initial experimental studies on the applicability of deep learning techniques under this approach provided promising results.

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Section: Case Studies 61 Radar Target Classification Based On High-rmentioning

confidence: 99%

A Hybrid Approach to Cognition in Radars

et al. 2018

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“…Since the success of using CT model relies on the correct estimation of turn rate, various schemes have been proposed in the literature for estimation of turn rate. Veeraraghavan et al [18] compared different turn rate estimation techniques for electronically scanned array radar tracking and employed an adaptive scheme for tracking targets using IMM estimator. Wang and Han [19] calculated the turn rate with the estimator of velocity and radius of curvature of target's trajectory by least squares and curve fitting to improve the CT tracking.…”

Section: Introductionmentioning

confidence: 99%