TDOA-/FDOA-Based Adaptive Active Target Localization Using Iterated Dual-EKF Algorithm

TDOA-/FDOA-Based Adaptive Active Target Localization Using Iterated Dual-EKF Algorithm

Most geolocation methods use only the time difference of arrival for estimating the emitter's location. In this letter, to obtain the velocity estimate values of an active target, we use the frequency difference of arrival. The iterated dual-extended Kalman filter (EKF) algorithm is used as a g...

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Veröffentlicht in:IEEE communications letters 2019-04, Vol.23 (4), p.752-755
Hauptverfasser: Lee, Kyunghyun, Oh, Jinhwan, You, Kwanho
Format: Artikel
Sprache:eng
Schlagworte:
Algorithms
Computer simulation
Convergence
Emitters
Extended Kalman filter
frequency difference of arrival
Geology
iterated dual-EKF
localization
Mathematical model
Noise measurement
Parameter estimation
Receivers
Simulation
Temperature measurement
Time difference of arrival
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Beschreibung
Zusammenfassung:Most geolocation methods use only the time difference of arrival for estimating the emitter's location. In this letter, to obtain the velocity estimate values of an active target, we use the frequency difference of arrival. The iterated dual-extended Kalman filter (EKF) algorithm is used as a geolocation process for a moving emitter. In comparison with the dual-EKF algorithm, the parameter estimation filter's update speed of the iterated dual-EKF algorithm shows a high convergence rate through the iteration process. To verify the performance of the proposed algorithm, simulation results by using the iterated dual-EKF algorithm are presented.
ISSN:1089-7798
1558-2558
DOI:10.1109/LCOMM.2019.2899615