TY - GEN
T1 - A moving horizon convex relaxation for mobile sensor network localization
AU - Simonetto, Andrea
AU - Leus, Geert
PY - 2014/1/1
Y1 - 2014/1/1
N2 - In mobile sensor network localization problems we seek to estimate the position of the mobile sensor nodes by using a subset of pair-wise range measurements (among the nodes and with mobile anchors). When the sensor nodes are static, convex relaxations have been shown to provide a remarkably accurate approximate solution to this NP-hard estimation problem. In this paper, we propose a novel convex relaxation to tackle the more challenging dynamic case and we develop a moving horizon convex estimator based on a maximum a posteriori (MAP) formulation. The resulting estimator is then compared to standard extended and unscented Kalman filters both with respect to computational complexity and performance with simulated data. The results are promising, yet a more detailed analysis is needed.
AB - In mobile sensor network localization problems we seek to estimate the position of the mobile sensor nodes by using a subset of pair-wise range measurements (among the nodes and with mobile anchors). When the sensor nodes are static, convex relaxations have been shown to provide a remarkably accurate approximate solution to this NP-hard estimation problem. In this paper, we propose a novel convex relaxation to tackle the more challenging dynamic case and we develop a moving horizon convex estimator based on a maximum a posteriori (MAP) formulation. The resulting estimator is then compared to standard extended and unscented Kalman filters both with respect to computational complexity and performance with simulated data. The results are promising, yet a more detailed analysis is needed.
U2 - 10.1109/SAM.2014.6882329
DO - 10.1109/SAM.2014.6882329
M3 - Conference contribution
AN - SCOPUS:84907401348
SN - 9781479914814
T3 - Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop
SP - 25
EP - 28
BT - 2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop, SAM 2014
PB - IEEE Computer Society
T2 - 2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop, SAM 2014
Y2 - 22 June 2014 through 25 June 2014
ER -