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Article

Improved Kalman Filter Variants for UAV Tracking with Radar Motion Models

by 1, 2,3 and 4,*
1
School of Electronic and Information Engineering, Beihang University, Beijing 100191, China
2
Yunnan Innovation Institute·BUAA, Kunming 650233, China
3
Beijing Key Laboratory for Microwave Sensing and Security Applications, Beihang University, Beijing 100191, China
4
Department of Electrical Engineering, ETS, University of Quebec, Montreal, QC H1A 0A1, Canada
*
Author to whom correspondence should be addressed.
Electronics 2020, 9(5), 768; https://doi.org/10.3390/electronics9050768
Received: 8 April 2020 / Revised: 26 April 2020 / Accepted: 30 April 2020 / Published: 7 May 2020
(This article belongs to the Special Issue Recent Advances in Mobile Ad Hoc Networks)
Unmanned aerial vehicles (UAV) have made a huge influence on our everyday life with maturity of technology and more extensive applications. Tracking UAVs has become more and more significant because of not only their beneficial location-based service, but also their potential threats. UAVs are low-altitude, slow-speed, and small targets, which makes it possible to track them with mobile radars, such as vehicle radars and UAVs with radars. Kalman filter and its variant algorithms are widely used to extract useful trajectory information from data mixed with noise. Applying those filter algorithms in east-north-up (ENU) coordinates with mobile radars causes filter performance degradation. To improve this, we made a derivation on the motion-model consistency of mobile radar with constant velocity. Then, extending common filter algorithms into earth-centered earth-fixed (ECEF) coordinates to filter out random errors is proposed. The theory analysis and simulation shows that the improved algorithms provide more efficiency and compatibility in mobile radar scenes. View Full-Text
Keywords: unmanned aerial vehicle (UAV); Kalman filter; east-north-up (ENU) coordinate; earth-centered earth-fixed (ECEF) coordinate; mobile radar unmanned aerial vehicle (UAV); Kalman filter; east-north-up (ENU) coordinate; earth-centered earth-fixed (ECEF) coordinate; mobile radar
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MDPI and ACS Style

Wei, Y.; Hong, T.; Kadoch, M. Improved Kalman Filter Variants for UAV Tracking with Radar Motion Models. Electronics 2020, 9, 768. https://doi.org/10.3390/electronics9050768

AMA Style

Wei Y, Hong T, Kadoch M. Improved Kalman Filter Variants for UAV Tracking with Radar Motion Models. Electronics. 2020; 9(5):768. https://doi.org/10.3390/electronics9050768

Chicago/Turabian Style

Wei, Yuan, Tao Hong, and Michel Kadoch. 2020. "Improved Kalman Filter Variants for UAV Tracking with Radar Motion Models" Electronics 9, no. 5: 768. https://doi.org/10.3390/electronics9050768

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