Reference : Integrated Trajectory Optimization and Cubature Kalman Filter for UAV-Based Target Tr...
Scientific congresses, symposiums and conference proceedings : Paper published in a book
Engineering, computing & technology : Electrical & electronics engineering
http://hdl.handle.net/10993/53615
Integrated Trajectory Optimization and Cubature Kalman Filter for UAV-Based Target Tracking with Unknown Initial Position
English
Xu, Sheng [> >]
Wu, Linlong mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SPARC]
MR, Bhavani Shankar [> >]
Babu, Prabhu [> >]
2022
2022 IEEE 12th Sensor Array and Multichannel Signal Processing Workshop (SAM)
331--335
Yes
2022 IEEE 12th Sensor Array and Multichannel Signal Processing Workshop (SAM)
from 20-06-2022 to 23-06-2022
IEEE
[en] This paper investigates the target localization/tracking by angle-of-arrival (AOA) sensors carried on an unmanned aerial vehicle (UAV). In many practical applications, the UAV's own position is not available, since the global position system (GPS) can hardly work in the indoor environment or interference region. Therefore, considering the unknown initial position of the UAV, a modified cubature Kalman filter (CKF) is developed to estimate both the target states and UAV's initial position jointly by leveraging a benchmark anchor. To further improve the estimation efficiency, we propose an algorithm to optimize the UAV flying trajectory by minimizing the the trace of the estimation covariance matrix in the CKF. According to the simulation results, an observation is found that the UAV will keeping flying alternatively between the anchor and target to guarantee the estimation performance.
http://hdl.handle.net/10993/53615
H2020 ; 742648 - AGNOSTIC - Actively Enhanced Cognition based Framework for Design of Complex Systems
FnR ; FNR12734677 > Bjorn Ottersten > SPRINGER > Signal Processing For Next Generation Radar > 01/09/2019 > 31/08/2022 > 2018

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