2,743 research outputs found
An opportunistic indoors positioning scheme based on estimated positions
The localization requirements for mobile nodes in wireless (sensor) networks are increasing. However, most research works are based on range measurements between nodes which are often oversensitive to the measurement error. In this paper we propose a location estimation scheme based on moving nodes that opportunistically exchange known positions. The user couples a linear matrix inequality (LMI) method with a barycenter computation to estimate its position. Simulations have shown that the accuracy of the estimation increases when the number of known positions increases, the radio range decreases and the node speeds increase. The proposed method only depends on a maximum RSS threshold to take into account a known position, which makes it robust and easy to implement. To obtain an accuracy of 1 meter, a user may have to wait at the same position for 5 minutes, with 8 pedestrians moving within range on average
Group behavior impact on an opportunistic localization scheme
In this paper we tackled the localization problem from an opportunistic perspective, according to which a node can infer its own spatial position by exchanging data with passing by nodes, called peers. We consider an opportunistic localization algorithm based on the linear matrix inequality (LMI) method coupled with a weighted barycenter algorithm. This scheme has been previously analyzed in scenarios with random deployment of peers, proving its effectiveness. In this paper, we extend the
analysis by considering more realistic mobility models for peer nodes. More specifically, we consider two mobility models, namely the Group Random Waypoint Mobility Model and the Group Random Pedestrian Mobility Model, which is an
improvement of the first one. Hence, we analyze by simulation the opportunistic localization algorithm for both the models, in order to gain insights on the impact of nodes mobility pattern onto the localization performance. The simulation results show that the mobility model has non-negligible effect on the final localization error, though the performance of the opportunistic localization scheme remains acceptable in all the considered scenarios
Collision and evaporation avoidance for spacecraft formation
<p>Formation flying is an extremely promising approach to space operations with the potential to enable new types of missions and providing substantial increase in the performance of future space science and Earth observation applications. To successfully validate formation flying however requires the development of specific technologies and methodologies, which are beyond current state-of-the art in a wide range of diverse fields such as metrology and spacecraft guidance, navigation and control. A number of missions are currently under different stages of development to implement some of these stringent requirements.</p>
<p>The paper develops and compares collision avoidance algorithms, demonstrating them within a 6 degrees of freedom, multi-spacecraft environment. At first a number of different collision avoidance scenarios will be identified alongside the triggers that will cause the algorithms to be activated. Once activated the collision avoidance algorithm must ensure corrective action to avoid catastrophic consequences to the mission.</p>
Towards the development of a smart flying sensor: illustration in the field of precision agriculture
Sensing is an important element to quantify productivity, product quality and to make decisions. Applications, such as mapping, surveillance, exploration and precision agriculture, require a reliable platform for remote sensing. This paper presents the first steps towards the development of a smart flying sensor based on an unmanned aerial vehicle (UAV). The concept of smart remote sensing is illustrated and its performance tested for the task of mapping the volume of grain inside a trailer during forage harvesting. Novelty lies in: (1) the development of a position-estimation method with time delay compensation based on inertial measurement unit (IMU) sensors and image processing; (2) a method to build a 3D map using information obtained from a regular camera; and (3) the design and implementation of a path-following control algorithm using model predictive control (MPC). Experimental results on a lab-scale system validate the effectiveness of the proposed methodology
Variational assimilation of Lagrangian data in oceanography
We consider the assimilation of Lagrangian data into a primitive equations
circulation model of the ocean at basin scale. The Lagrangian data are
positions of floats drifting at fixed depth. We aim at reconstructing the
four-dimensional space-time circulation of the ocean. This problem is solved
using the four-dimensional variational technique and the adjoint method. In
this problem the control vector is chosen as being the initial state of the
dynamical system. The observed variables, namely the positions of the floats,
are expressed as a function of the control vector via a nonlinear observation
operator. This method has been implemented and has the ability to reconstruct
the main patterns of the oceanic circulation. Moreover it is very robust with
respect to increase of time-sampling period of observations. We have run many
twin experiments in order to analyze the sensitivity of our method to the
number of floats, the time-sampling period and the vertical drift level. We
compare also the performances of the Lagrangian method to that of the classical
Eulerian one. Finally we study the impact of errors on observations.Comment: 31 page
A review of smartphones based indoor positioning: challenges and applications
The continual proliferation of mobile devices has encouraged much effort in
using the smartphones for indoor positioning. This article is dedicated to
review the most recent and interesting smartphones based indoor navigation
systems, ranging from electromagnetic to inertia to visible light ones, with an
emphasis on their unique challenges and potential real-world applications. A
taxonomy of smartphones sensors will be introduced, which serves as the basis
to categorise different positioning systems for reviewing. A set of criteria to
be used for the evaluation purpose will be devised. For each sensor category,
the most recent, interesting and practical systems will be examined, with
detailed discussion on the open research questions for the academics, and the
practicality for the potential clients
Underwater Positioning System Based on Drifting Buoys and Acoustic Modems
GNSS (Global Navigation Satellite System) positioning is not available underwater due to the very short range of electromagnetic waves in the sea water medium. In this article a LBL (Long Base Line) acoustic repeater system of the GNSS positioning is presented. The system is hyperbolic, i.e., based on time differences and it does not need very accurate atomic clocks to synchronize repeaters. The system architecture and system calculations that demonstrate the feasibility of the solution are presented. The system uses four buoys that sequentially transmit their position and the time of the instant of transmission, for which they are equipped with GNSS receivers and acoustic modems. The buoys can be fixed or even drifting, but they are inexpensive devices, which pose no hazard to navigation and can be easily and quickly deployed for a specific underwater mission. The multilateration algorithm used in the receiver is presented. To simplify the algorithm, the depth of the receiver, measured by a depth sensor, is used. Results are presented for the position error of an underwater vehicle due to its displacement during the transmission frame of the four buoys.Funding for open access charge: Universidad de MĂĄlag
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