Multiple emitter localization using range only measurements considering geometrical constraints

This paper proposes a constrained optimization approach to improve the accuracy of a Time-of-Arrival (ToA) based multiple target localization system. Instead of using an overdetermined measurement system, this paper uses local distance measurements between the targets/emitters as the geometric constraint.Computer simulations are used to evaluate the performance of the geometrically constrained optimization method.

Optimal sensor placement in range based localization for linear arrays

This paper investigates the linear separation requirements for range sensors in order to achieve the optimal performance in estimating the position of a target from multiple and typically noisy sensor measurements. We analyze the sensor-target geometry in terms of the Cramer-Rao inequality and the corresponding Fisher information matrix, in order to characterize localization performance with respect to the linear special distribution.

Localization with ghost elimination of emitters via time-of-arrival measurements

This paper looks at the theoretical conditions underpinning unique localization of synchronized multiple emitters using Time-of-Arrival measurements subjected to the data-association problem. The necessary fundamental requirements to solve the so-called ghost node problem associated with sensor arrays are examined. We derive a measurement bound for ideal situations and the underlying concepts are illustrated via simulations.

Localization of copper and copper transporters in the human brain

Disturbances in brain copper result in rare and severe neurological disorders and may play a role in the pathogenesis and progression of multiple neurodegenerative diseases. Our current understanding of mammalian brain copper transport is based on model systems outside the central nervous system and no data are available regarding copper transport systems in the human brain. To address this deficit, we quantified regional copper concentrations and examined the distribution and cellular localization of the copper transport proteins Copper transporter 1, Atox1, ATP7A, and ATP7B in multiple regions of the human brain using inductively coupled plasma-mass spectrometry, Western blot and immunohistochemistry. We identified significant relationships between copper transporter levels and brain copper concentrations, supporting a role for these proteins in copper transport in the human brain. Interestingly, the substantia nigra contained twice as much copper than that in other brain regions, suggesting an important role for copper in this brain region. Furthermore, ATP7A levels were significantly greater in the cerebellum, compared with other brain regions, supporting an important role for ATP7A in cerebellar neuronal health. This study provides novel data regarding copper regulation in the human brain, critical to understand the mechanisms by which brain copper levels can be altered, leading to neurological disease.

Localization and tracking of agents for close range applications

This research investigates the state estimation problem in close-range involving multiple targets using Doppler Radar. As the main theme is based on measurements with linear sensor arrays, optimal sensor arrangements are studied for two most popular measurement technologies: Angle-of-Arrival and range based localization systems.

Underwater swarm robotics consensus control

The control of a swarm of underwater robots requires more than just a control algorithm, it requires a communications system. Underwater communications is difficult at the best of times and so large time delays and minimal information is a concern. The control system must be able to work on minimal and out of date information. The control system must also be able to control a large number of robots without a master control, a decentralized control approach. This paper describes one such control method.

Quantification of spatial and thematic uncertainty in the application of underwater video for benthic habitat mapping

This study presents an analysis of the application of underwater video data collected for training and validating benthic habitat distribution models. Specifically, we quantify the two major sources of error pertaining to collection of this type of reference data. A theoretical spatial error budget is developed for a positioning system used to co-register video frames to their corresponding locations at the seafloor. Second, we compare interpretation variability among trained operators assessing the same video frames between times over three hierarchical levels of a benthic classification scheme. Propagated error in the positioning system described was found to be highly correlated with depth of operation and varies from 1.5m near the surface to 5.7m in 100m of water. In order of decreasing classification hierarchy, mean overall observer agreement was found to be 98% (range 6%), 82% (range 12%) and 75% (range 17%) for the 2, 4, and 6 class levels of the scheme, respectively. Patterns in between-observer variation are related to the level of detail imposed by each hierarchical level of the classification scheme, the feature of interest, and to the amount of observer experience. © 2014 Copyright © Taylor & Francis Group, LLC.