TY - GEN
T1 - Modeling of three-dimensional radar tracking system and its estimation using Extended Kalman Filter
AU - Arif, Didik Khusnul
AU - Adzkiya, Dieky
AU - Aditya, Prima
AU - Winata, Feri
AU - Agustin, Diah
AU - Habibi, M. Reza
AU - Ririsati, Alfiana
AU - Prasyanto, Ramadhani
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/10/13
Y1 - 2017/10/13
N2 - Nowadays, the three-dunensional radar tracking has a rapid deveiopment lï'acldiig filter designs commonly rely on a linear system, while the nonlinear systems mostly occur in everyday life. The development of this fUter algorithm can solve the three-dimensional radar tracking problem by using some measurement data. In the case discussed in this paper, the target is measured by radar with distance r, azimuth angle Θ, and the elevation angle φ. Notice that the data is not a linear measurement data. Thus, to address the nonlinearities inherent in the system model and the measurement model, we use the Extended Kalman FUter approach. Variables and parameters are adjusted directly on the three-dimensional radar system. The simulation results show that the proposed formulation is very effective in the calculation of nonlinear measurement with the error belongs to interval from 0.69% to 1.21%.
AB - Nowadays, the three-dunensional radar tracking has a rapid deveiopment lï'acldiig filter designs commonly rely on a linear system, while the nonlinear systems mostly occur in everyday life. The development of this fUter algorithm can solve the three-dimensional radar tracking problem by using some measurement data. In the case discussed in this paper, the target is measured by radar with distance r, azimuth angle Θ, and the elevation angle φ. Notice that the data is not a linear measurement data. Thus, to address the nonlinearities inherent in the system model and the measurement model, we use the Extended Kalman FUter approach. Variables and parameters are adjusted directly on the three-dimensional radar system. The simulation results show that the proposed formulation is very effective in the calculation of nonlinear measurement with the error belongs to interval from 0.69% to 1.21%.
UR - http://www.scopus.com/inward/record.url?scp=85037155567&partnerID=8YFLogxK
U2 - 10.1109/ICA.2017.8068412
DO - 10.1109/ICA.2017.8068412
M3 - Conference contribution
AN - SCOPUS:85037155567
T3 - Proceedings of the 2017 5th International Conference on Instrumentation, Control, and Automation, ICA 2017
SP - 51
EP - 55
BT - Proceedings of the 2017 5th International Conference on Instrumentation, Control, and Automation, ICA 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 5th International Conference on Instrumentation, Control, and Automation, ICA 2017
Y2 - 9 August 2017 through 11 August 2017
ER -