A real-time target tracking system for wireless embedded nodes using ranging measurements
A real-time target tracking system for wireless embedded nodes using ranging measurements
The area of wireless embedded nodes has attracted significant research interest, primarily with respect to the utilisation of this technology in a number of applications domains. Under this context, the main topic of this thesis pertains to the design of a framework for real-time, range-only target tracking utilizing low power wireless embedded nodes. The proposed tracking system is designed to operate solely on range measurements which are obtained without the need for additional hardware incorporated on the embedded nodes. The core objective of this research was to present a target tracking system that can be applied to real-world applications, incorporating support for effectively tracking manoeuvring targets facilitated by the ability to obtain accurate range readings from low-power embedded nodes and finally the ability to achieve real-time system operation.
The contribution of the work presented in this thesis is threefold. The tracking problem is theoretically formulated as a dynamical system with the objective being, the real-time estimation of the target’s kinematic variables based on range observations. To address the need for effective tracking of manoeuvring targets an adaptive multiple-model approach was developed. The resulting system is non-linear, due to the non-linearity between the range observations and the kinematic variables. To solve this system, a novel adaptive multiple-model Particle Filter tracking algorithm is proposed. Secondly, to achieve accurate enough ranging between embedded nodes a Time-of-Flight ranging scheme is adopted as part of the proposed tracking system. The final contribution of this work pertains to the real-time operation of the tracking system.
The tracking algorithms were evaluated on a simulation environment under realistic experimental conditions. The ranging method was implemented on embedded nodes and tested in terms of accuracy in various environments. Ultimately, the entire system was implemented on hardware and tested in outdoor experiments. In the experiments carried out one mobile wireless node was used as the target and a set of anchor nodes attempted to infer the target’s kinematic variables. A total of 25 experiments are presented in this thesis. An average accuracy of approximately 2.6m for position and 1.9m/s for velocity was attained in a 15m x 15m square area. Such performance, which is confirmed from the simulation results reveal the potential of the proposed range-only system in application domains where real-time tracking of mobile targets is a demand.
Mazomenos, Evangelos
23983827-c7e7-4ee1-bfc8-986aa3594279
February 2012
Mazomenos, Evangelos
23983827-c7e7-4ee1-bfc8-986aa3594279
Reeve, J.S.
dd909010-7d44-44ea-83fe-a09e4d492618
White, N.M.
c7be4c26-e419-4e5c-9420-09fc02e2ac9c
Mazomenos, Evangelos
(2012)
A real-time target tracking system for wireless embedded nodes using ranging measurements.
University of Southampton, Faculty of Physical and Applied Sciences, Doctoral Thesis, 169pp.
Record type:
Thesis
(Doctoral)
Abstract
The area of wireless embedded nodes has attracted significant research interest, primarily with respect to the utilisation of this technology in a number of applications domains. Under this context, the main topic of this thesis pertains to the design of a framework for real-time, range-only target tracking utilizing low power wireless embedded nodes. The proposed tracking system is designed to operate solely on range measurements which are obtained without the need for additional hardware incorporated on the embedded nodes. The core objective of this research was to present a target tracking system that can be applied to real-world applications, incorporating support for effectively tracking manoeuvring targets facilitated by the ability to obtain accurate range readings from low-power embedded nodes and finally the ability to achieve real-time system operation.
The contribution of the work presented in this thesis is threefold. The tracking problem is theoretically formulated as a dynamical system with the objective being, the real-time estimation of the target’s kinematic variables based on range observations. To address the need for effective tracking of manoeuvring targets an adaptive multiple-model approach was developed. The resulting system is non-linear, due to the non-linearity between the range observations and the kinematic variables. To solve this system, a novel adaptive multiple-model Particle Filter tracking algorithm is proposed. Secondly, to achieve accurate enough ranging between embedded nodes a Time-of-Flight ranging scheme is adopted as part of the proposed tracking system. The final contribution of this work pertains to the real-time operation of the tracking system.
The tracking algorithms were evaluated on a simulation environment under realistic experimental conditions. The ranging method was implemented on embedded nodes and tested in terms of accuracy in various environments. Ultimately, the entire system was implemented on hardware and tested in outdoor experiments. In the experiments carried out one mobile wireless node was used as the target and a set of anchor nodes attempted to infer the target’s kinematic variables. A total of 25 experiments are presented in this thesis. An average accuracy of approximately 2.6m for position and 1.9m/s for velocity was attained in a 15m x 15m square area. Such performance, which is confirmed from the simulation results reveal the potential of the proposed range-only system in application domains where real-time tracking of mobile targets is a demand.
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mazomenos_thesis_final.pdf
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Published date: February 2012
Organisations:
University of Southampton, EEE
Identifiers
Local EPrints ID: 336229
URI: http://eprints.soton.ac.uk/id/eprint/336229
PURE UUID: e48b495b-5f11-4e46-8956-11eec8cbe0e5
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Date deposited: 29 Jun 2012 10:56
Last modified: 15 Mar 2024 02:41
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Contributors
Author:
Evangelos Mazomenos
Thesis advisor:
J.S. Reeve
Thesis advisor:
N.M. White
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