TY - GEN
T1 - Noisy network localization via optimal measurement refinement part 1
T2 - Bearing-only orientation registration and localization
AU - Bishop, Adrian N.
AU - Shames, Iman
PY - 2011
Y1 - 2011
N2 - The problem of localizing or tracking a number of targets using a network of bearing-only sensors is considered. To solve such a high-level problem, each sensor report must be successfully recorded in a common spatial reference frame and the position of the sensors must be determined. In practice, however, the reports from individual sensors are characterized by both random (called noise) and systematic errors (called biases). Typical bias errors are axis misalignments (due to azimuth and elevation biases) and range offset errors. Conditions under which the systematic errors can be removed given noisy measurements are examined in this work. In addition, certain conditions are identified which lend themselves naturally to the design of algorithms for network registration, localization and subsequently target localization. These conditions are feasible from a computational complexity point of view. This work provides a comprehensive solution to the problem of sensor network-based target localization with bearing measurements as very little a prior information is assumed known and, if certain sensing conditions are met, efficient algorithms are provided.
AB - The problem of localizing or tracking a number of targets using a network of bearing-only sensors is considered. To solve such a high-level problem, each sensor report must be successfully recorded in a common spatial reference frame and the position of the sensors must be determined. In practice, however, the reports from individual sensors are characterized by both random (called noise) and systematic errors (called biases). Typical bias errors are axis misalignments (due to azimuth and elevation biases) and range offset errors. Conditions under which the systematic errors can be removed given noisy measurements are examined in this work. In addition, certain conditions are identified which lend themselves naturally to the design of algorithms for network registration, localization and subsequently target localization. These conditions are feasible from a computational complexity point of view. This work provides a comprehensive solution to the problem of sensor network-based target localization with bearing measurements as very little a prior information is assumed known and, if certain sensing conditions are met, efficient algorithms are provided.
UR - http://www.scopus.com/inward/record.url?scp=84866753802&partnerID=8YFLogxK
U2 - 10.3182/20110828-6-IT-1002.01286
DO - 10.3182/20110828-6-IT-1002.01286
M3 - Conference contribution
SN - 9783902661937
T3 - IFAC Proceedings Volumes (IFAC-PapersOnline)
SP - 8842
EP - 8847
BT - Proceedings of the 18th IFAC World Congress
PB - IFAC Secretariat
ER -