788 resultados para statistical modelling, wind effects, signal propagation, wireless sensor networks
Resumo:
Spacecraft formation flying navigation continues to receive a great deal of interest. The research presented in this dissertation focuses on developing methods for estimating spacecraft absolute and relative positions, assuming measurements of only relative positions using wireless sensors. The implementation of the extended Kalman filter to the spacecraft formation navigation problem results in high estimation errors and instabilities in state estimation at times. This is due tp the high nonlinearities in the system dynamic model. Several approaches are attempted in this dissertation aiming at increasing the estimation stability and improving the estimation accuracy. A differential geometric filter is implemented for spacecraft positions estimation. The differential geometric filter avoids the linearization step (which is always carried out in the extended Kalman filter) through a mathematical transformation that converts the nonlinear system into a linear system. A linear estimator is designed in the linear domain, and then transformed back to the physical domain. This approach demonstrated better estimation stability for spacecraft formation positions estimation, as detailed in this dissertation. The constrained Kalman filter is also implemented for spacecraft formation flying absolute positions estimation. The orbital motion of a spacecraft is characterized by two range extrema (perigee and apogee). At the extremum, the rate of change of a spacecraft’s range vanishes. This motion constraint can be used to improve the position estimation accuracy. The application of the constrained Kalman filter at only two points in the orbit causes filter instability. Two variables are introduced into the constrained Kalman filter to maintain the stability and improve the estimation accuracy. An extended Kalman filter is implemented as a benchmark for comparison with the constrained Kalman filter. Simulation results show that the constrained Kalman filter provides better estimation accuracy as compared with the extended Kalman filter. A Weighted Measurement Fusion Kalman Filter (WMFKF) is proposed in this dissertation. In wireless localizing sensors, a measurement error is proportional to the distance of the signal travels and sensor noise. In this proposed Weighted Measurement Fusion Kalman Filter, the signal traveling time delay is not modeled; however, each measurement is weighted based on the measured signal travel distance. The obtained estimation performance is compared to the standard Kalman filter in two scenarios. The first scenario assumes using a wireless local positioning system in a GPS denied environment. The second scenario assumes the availability of both the wireless local positioning system and GPS measurements. The simulation results show that the WMFKF has similar accuracy performance as the standard Kalman Filter (KF) in the GPS denied environment. However, the WMFKF maintains the position estimation error within its expected error boundary when the WLPS detection range limit is above 30km. In addition, the WMFKF has a better accuracy and stability performance when GPS is available. Also, the computational cost analysis shows that the WMFKF has less computational cost than the standard KF, and the WMFKF has higher ellipsoid error probable percentage than the standard Measurement Fusion method. A method to determine the relative attitudes between three spacecraft is developed. The method requires four direction measurements between the three spacecraft. The simulation results and covariance analysis show that the method’s error falls within a three sigma boundary without exhibiting any singularity issues. A study of the accuracy of the proposed method with respect to the shape of the spacecraft formation is also presented.
Resumo:
Range estimation is the core of many positioning systems such as radar, and Wireless Local Positioning Systems (WLPS). The estimation of range is achieved by estimating Time-of-Arrival (TOA). TOA represents the signal propagation delay between a transmitter and a receiver. Thus, error in TOA estimation causes degradation in range estimation performance. In wireless environments, noise, multipath, and limited bandwidth reduce TOA estimation performance. TOA estimation algorithms that are designed for wireless environments aim to improve the TOA estimation performance by mitigating the effect of closely spaced paths in practical (positive) signal-to-noise ratio (SNR) regions. Limited bandwidth avoids the discrimination of closely spaced paths. This reduces TOA estimation performance. TOA estimation methods are evaluated as a function of SNR, bandwidth, and the number of reflections in multipath wireless environments, as well as their complexity. In this research, a TOA estimation technique based on Blind signal Separation (BSS) is proposed. This frequency domain method estimates TOA in wireless multipath environments for a given signal bandwidth. The structure of the proposed technique is presented and its complexity and performance are theoretically evaluated. It is depicted that the proposed method is not sensitive to SNR, number of reflections, and bandwidth. In general, as bandwidth increases, TOA estimation performance improves. However, spectrum is the most valuable resource in wireless systems and usually a large portion of spectrum to support high performance TOA estimation is not available. In addition, the radio frequency (RF) components of wideband systems suffer from high cost and complexity. Thus, a novel, multiband positioning structure is proposed. The proposed technique uses the available (non-contiguous) bands to support high performance TOA estimation. This system incorporates the capabilities of cognitive radio (CR) systems to sense the available spectrum (also called white spaces) and to incorporate white spaces for high-performance localization. First, contiguous bands that are divided into several non-equal, narrow sub-bands that possess the same SNR are concatenated to attain an accuracy corresponding to the equivalent full band. Two radio architectures are proposed and investigated: the signal is transmitted over available spectrum either simultaneously (parallel concatenation) or sequentially (serial concatenation). Low complexity radio designs that handle the concatenation process sequentially and in parallel are introduced. Different TOA estimation algorithms that are applicable to multiband scenarios are studied and their performance is theoretically evaluated and compared to simulations. Next, the results are extended to non-contiguous, non-equal sub-bands with the same SNR. These are more realistic assumptions in practical systems. The performance and complexity of the proposed technique is investigated as well. This study’s results show that selecting bandwidth, center frequency, and SNR levels for each sub-band can adapt positioning accuracy.
Resumo:
Energy consumption modelling by state based approaches often assume constant energy consumption values in each state. However, it happens in certain situations that during state transitions or even during a state the energy consumption is not constant and does fluctuate. This paper discusses those issues by presenting some examples from wireless sensor and wireless local area networks for such cases and possible solutions.
Resumo:
The advantages of wireless sensing implemented on the cold chain of fresh products are well known. These sensor systems consist of a combination of delicate internal electronic circuitry enclosed in a special housing unit. Manufacturers however are presented with the challenge that the housing required to withstand the harsh environment in which the sensors are being used all too often take from the functionality of the sensor. Therefore the target of this study is to determine the dynamic behavior and the counteractive effects of the sensor housing on temperature recording accuracy in the wireless nodes of Wireless Sensor Network (WSN) and Radio Frequency Identification (RFID) semi-passive tags. Two kind of semi-passive Turbo Tags were used (T700 and T702-B), which consisted of sensors with and without a cover, and two kind of WSN nodes, IRIS (sensors Intersema and Sensirion soldered in the motherboard) and NLAZA (Sensirion in a cable and soldered to the motherboard). To recreate the temperature profiles the devices were rotated between a cold room(5 ºC) through a ambient room(23 ºC) to a heated environment (35ºC) and vice versa. Analysis revealed the differences between housing and no housing are 308.22s to 21.99s respectively in the step from 5 to 35 ºC. As is demonstrated in these experiments the influence of the housing significantly hinders sensor accuracy.
Resumo:
Wireless teleoperation of field robots for maintenance, inspection and rescue missions is often performed in environments with low wireless connectivity, caused by signal losses from the environment and distance from the wireless transmitters. Various studies from the literature have addressed these problems with time-delay robust control systems and multi-hop wireless relay networks. However, such approaches do not solve the issue of how to present wireless data to the operator to avoid losing control of the robot. Despite the fact that teleoperation for maintenance often already involves haptic devices, no studies look at the possibility of using this existing feedback to aid operators in navigating within areas of variable wireless connectivity. We propose a method to incorporate haptic information into the velocity control of an omnidirectional robot to augment the operators perception of wireless signal strength in the remote environment. In this paper we introduce a mapping between wireless signal strength from multiple receivers to the force feedback of a 6 Degree of Freedom haptic master and evaluate the proposed approach using experimental data and randomly generated wireless maps
Resumo:
Multiple input multiple output (MIMO) wireless systems use multiple element antennas (MEAs) tit the transmitter (TX) and the receiver (RX) in order to offer improved information rates (capacity) over conventional single antenna systems in rich scattering environments. In this paper, an example of a simple MIMO system is considered in which both antennas and scattering objects is are formed by wire dipoles. Such it system can be analyzed in the strict electromagnetic (EM) sense and its capacity can be determined for varying array size, interelement spacing, and distributions of scatterers. The EM model of this MIMO system can be used to assess the validity of single- or double-bounce scattering models for mixed line of sight (LOS) and non-line of sight (NLOS) signal-propagation conditions. (c) 2006 Wiley Periodicals, Inc.
Resumo:
In indoor environments the properties of communication channel are affected by the presence of various objects which block the Line Of Sight signal propagation. For example, this occurs because of presence of movement of humans and furniture. In this paper, the effect of reflection and scattering due to the presence of such objects is studied with respect to the capacity of a multiple input multiple output (MIMO) wireless system. The carried out investigations are performed by applying a simple electromagnetic model, in which transmitting and receiving antennas of MIMO system, as well as signal blocking objects, are represented by wire dipoles. In order to provide a fair assessment, calculations of MIMO capacity are performed under both fixed transmitted power and fixed received power conditions.
Resumo:
A wide range of non-destructive testing (NDT) methods for the monitoring the health of concrete structure has been studied for several years. The recent rapid evolution of wireless sensor network (WSN) technologies has resulted in the development of sensing elements that can be embedded in concrete, to monitor the health of infrastructure, collect and report valuable related data. The monitoring system can potentially decrease the high installation time and reduce maintenance cost associated with wired monitoring systems. The monitoring sensors need to operate for a long period of time, but sensors batteries have a finite life span. Hence, novel wireless powering methods must be devised. The optimization of wireless power transfer via Strongly Coupled Magnetic Resonance (SCMR) to sensors embedded in concrete is studied here. First, we analytically derive the optimal geometric parameters for transmission of power in the air. This specifically leads to the identification of the local and global optimization parameters and conditions, it was validated through electromagnetic simulations. Second, the optimum conditions were employed in the model for propagation of energy through plain and reinforced concrete at different humidity conditions, and frequencies with extended Debye's model. This analysis leads to the conclusion that SCMR can be used to efficiently power sensors in plain and reinforced concrete at different humidity levels and depth, also validated through electromagnetic simulations. The optimization of wireless power transmission via SMCR to Wearable and Implantable Medical Device (WIMD) are also explored. The optimum conditions from the analytics were used in the model for propagation of energy through different human tissues. This analysis shows that SCMR can be used to efficiently transfer power to sensors in human tissue without overheating through electromagnetic simulations, as excessive power might result in overheating of the tissue. Standard SCMR is sensitive to misalignment; both 2-loops and 3-loops SCMR with misalignment-insensitive performances are presented. The power transfer efficiencies above 50% was achieved over the complete misalignment range of 0°-90° and dramatically better than typical SCMR with efficiencies less than 10% in extreme misalignment topologies.
Resumo:
A wide range of non-destructive testing (NDT) methods for the monitoring the health of concrete structure has been studied for several years. The recent rapid evolution of wireless sensor network (WSN) technologies has resulted in the development of sensing elements that can be embedded in concrete, to monitor the health of infrastructure, collect and report valuable related data. The monitoring system can potentially decrease the high installation time and reduce maintenance cost associated with wired monitoring systems. The monitoring sensors need to operate for a long period of time, but sensors batteries have a finite life span. Hence, novel wireless powering methods must be devised. The optimization of wireless power transfer via Strongly Coupled Magnetic Resonance (SCMR) to sensors embedded in concrete is studied here. First, we analytically derive the optimal geometric parameters for transmission of power in the air. This specifically leads to the identification of the local and global optimization parameters and conditions, it was validated through electromagnetic simulations. Second, the optimum conditions were employed in the model for propagation of energy through plain and reinforced concrete at different humidity conditions, and frequencies with extended Debye's model. This analysis leads to the conclusion that SCMR can be used to efficiently power sensors in plain and reinforced concrete at different humidity levels and depth, also validated through electromagnetic simulations. The optimization of wireless power transmission via SMCR to Wearable and Implantable Medical Device (WIMD) are also explored. The optimum conditions from the analytics were used in the model for propagation of energy through different human tissues. This analysis shows that SCMR can be used to efficiently transfer power to sensors in human tissue without overheating through electromagnetic simulations, as excessive power might result in overheating of the tissue. Standard SCMR is sensitive to misalignment; both 2-loops and 3-loops SCMR with misalignment-insensitive performances are presented. The power transfer efficiencies above 50% was achieved over the complete misalignment range of 0°-90° and dramatically better than typical SCMR with efficiencies less than 10% in extreme misalignment topologies.
Resumo:
A number of theoretical and experimental investigations have been made into the nature of purlin-sheeting systems over the past 30 years. These systems commonly consist of cold-formed zed or channel section purlins, connected to corrugated sheeting. They have proven difficult to model due to the complexity of both the purlin deformation and the restraint provided to the purlin by the sheeting. Part 1 of this paper presented a non-linear elasto plastic finite element model which, by incorporating both the purlin and the sheeting in the analysis, allowed the interaction between the two components of the system to be modelled. This paper presents a simplified version of the first model which has considerably decreased requirements in terms of computer memory, running time and data preparation. The Simplified Model includes only the purlin but allows for the sheeting's shear and rotational restraints by modelling these effects as springs located at the purlin-sheeting connections. Two accompanying programs determine the stiffness of these springs numerically. As in the Full Model, the Simplified Model is able to account for the cross-sectional distortion of the purlin, the shear and rotational restraining effects of the sheeting, and failure of the purlin by local buckling or yielding. The model requires no experimental or empirical input and its validity is shown by its goon con elation with experimental results. (C) 1997 Elsevier Science Ltd.
Resumo:
Orebody modelling, support effects and the estimation of recoverable reserves are key parts of open pit optimization studies. A case study is presented on the estimation of recoverable reserves using an implementation of indicator kriging where metal quantity is used to select cutoffs, and support corrections founded on a conditional simulation approach. Mining selectivity is explored in the subsequent optimization study to compare results from indicator kriging of grade estimates on a regular size blocks and indicator kriging estimates on small size blocks. The use of indicator kriging models adjusted for a given selectivity and the use of grade proportions in each block for the optimization study, provide a presentation of the expected ore recovery for a predefined level of selectivity. The case study shows that indicator kriging estimation with full accounting of block grade distributions generates substantially better results in the pit optimization study. In addition, the adverse effects of small blocks and over-smoothing on optimization results are illustrated.
Resumo:
This paper describes a process-based metapopulation dynamics and phenology model of prickly acacia, Acacia nilotica, an invasive alien species in Australia. The model, SPAnDX, describes the interactions between riparian and upland sub-populations of A. nilotica within livestock paddocks, including the effects of extrinsic factors such as temperature, soil moisture availability and atmospheric concentrations of carbon dioxide. The model includes the effects of management events such as changing the livestock species or stocking rate, applying fire, and herbicide application. The predicted population behaviour of A. nilotica was sensitive to climate. Using 35 years daily weather datasets for five representative sites spanning the range of conditions that A. nilotica is found in Australia, the model predicted biomass levels that closely accord with expected values at each site. SPAnDX can be used as a decision-support tool in integrated weed management, and to explore the sensitivity of cultural management practices to climate change throughout the range of A. nilotica. The cohort-based DYMEX modelling package used to build and run SPAnDX provided several advantages over more traditional population modelling approaches (e.g. an appropriate specific formalism (discrete time, cohort-based, process-oriented), user-friendly graphical environment, extensible library of reusable components, and useful and flexible input/output support framework). (C) 2003 Published by Elsevier Science B.V.
Resumo:
Knowing exactly where a mobile entity is and monitoring its trajectory in real-time has recently attracted a lot of interests from both academia and industrial communities, due to the large number of applications it enables, nevertheless, it is nowadays one of the most challenging problems from scientific and technological standpoints. In this work we propose a tracking system based on the fusion of position estimations provided by different sources, that are combined together to get a final estimation that aims at providing improved accuracy with respect to those generated by each system individually. In particular, exploiting the availability of a Wireless Sensor Network as an infrastructure, a mobile entity equipped with an inertial system first gets the position estimation using both a Kalman Filter and a fully distributed positioning algorithm (the Enhanced Steepest Descent, we recently proposed), then combines the results using the Simple Convex Combination algorithm. Simulation results clearly show good performance in terms of the final accuracy achieved. Finally, the proposed technique is validated against real data taken from an inertial sensor provided by THALES ITALIA.
Resumo:
Consider a wireless sensor network (WSN) where a broadcast from a sensor node does not reach all sensor nodes in the network; such networks are often called multihop networks. Sensor nodes take individual sensor readings, however, in many cases, it is relevant to compute aggregated quantities of these readings. In fact, the minimum and maximum of all sensor readings at an instant are often interesting because they indicate abnormal behavior, for example if the maximum temperature is very high then it may be that a fire has broken out. In this context, we propose an algorithm for computing the min or max of sensor readings in a multihop network. This algorithm has the particularly interesting property of having a time complexity that does not depend on the number of sensor nodes; only the network diameter and the range of the value domain of sensor readings matter.
Resumo:
This paper presents the design of low-cost, conformal UHF antennas and RFID tags on two types of cork substrates: 1) natural cork and 2) agglomerate cork. Such RFID tags find an application in wine bottle and barrel identification, and in addition, they are suitable for numerous antenna-based sensing applications. This paper includes the high-frequency characterization of the selected cork substrates considering the anisotropic behavior of such materials. In addition, the variation of their permittivity values as a function of the humidity is also verified. As a proof-of-concept demonstration, three conformal RFID tags have been implemented on cork, and their performance has been evaluated using both a commercial Alien ALR8800 reader and an in-house measurement setup. The reading of all tags has been checked, and a satisfactory performance has been verified, with reading ranges spanning from 0.3 to 6 m. In addition, this paper discusses how inkjet printing can be applied to cork surfaces, and an RFID tag printed on cork is used as a humidity sensor. Its performance is tested under different humidity conditions, and a good range in excess of 3 m has been achieved, allied to a good sensitivity obtained with a shift of >5 dB in threshold power of the tag for different humid conditions.