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data-fusion
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Secure consensus averaging in sensor networks using random offsets
, Article 2007 IEEE International Conference on Telecommunications and Malaysia International Conference on Communications, ICT-MICC 2007, Penang, 14 May 2007 through 17 May 2007 ; 2007 , Pages 556-560 ; 1424410940 (ISBN); 9781424410941 (ISBN) ; Talebi, M. S ; Hossein Khalaj, B ; Rabiee, H. R ; Sharif University of Technology
2007
Abstract
In this work, we have examined the distributed consensus averaging problem from a novel point of view considering the need for privacy and anonymity. We have proposed a method for incorporating security into the scalable average consensus mechanisms proposed in the literature. Random Offsets Method (ROM) is lightweight, transparent and flexible since it is not based on cryptography, does not require any change in the fusion system and can be used optionally by some nodes who care about their privacy. In this method, which is based on noisiflcation of nodes' information, we achieve robustness against n - 1 colluding adversaries in a network of n nodes, which is maximum level of robustness...
Transmit power reduction by adapting rate or power for single carrier wireless systems
, Article 25th IEEE International Performance, Computing, and Communications Conference, 2006, IPCCC 2006, Phoenix, AZ, 10 April 2006 through 12 April 2006 ; Volume 2006 , 2006 , Pages 103-109 ; 1424401976 (ISBN); 9781424401970 (ISBN) ; Pakravan, M. R ; Khalaj, B. H ; Sharif University of Technology
2006
Abstract
Adaptive modulation with the goal of minimizing the average transmit power is investigated. This is the dual problem of the well-known problem of maximizing the average spectral efficiency. This is desirable in power limited systems such as mobile and sensor networks. Two main cases are considered: adapting only transmit power and adapting only rate. Appropriate expressions for rate or power control policies are derived for different cases. For rate adaptation, we consider both continuous and discrete rate policies. Then, we will apply these methods to a special case of M-QAM modulation over Rayleigh fading channel. We will show that by using rate or power adaptation schemes, between 7dB and...
Estimation error minimization in sensor networks with mobile agents
, Article 2006 3rd IEEE Consumer Communications and Networking Conference, CCNC 2006, Las Vegas, NV, 8 January 2006 through 10 January 2006 ; Volume 2 , 2006 , Pages 964-968 ; 1424400856 (ISBN); 9781424400850 (ISBN) ; Arbab, V. R ; Pakravan, M. R ; Sharif University of Technology
2006
Abstract
In a SEnsor Network with Mobile Agents (SENMA) is an architecture proposed for large scale sensor networks. In sensor networks, a fraction of the packets generated by only part of the sensors is sufficient to provide a good estimation of all network information. SENMA uses this inherent redundancy. However, the performance of such system is limited by estimation errors and packet errors due to collision. Estimation error is a major problem in applications such as habitat monitoring in which information is a function of node position. In this paper, we first derive the equations of distortion in a general scenario and use this model to compare the estimation error for regular networks. Then...
Energy conserving movement-assisted deployment of Ad hoc sensor networks
, Article IEEE Communications Letters ; Volume 10, Issue 4 , 2006 , Pages 269-271 ; 10897798 (ISSN) ; Nayyeri, A ; Yazdani, N ; Lucas, C ; Sharif University of Technology
2006
Abstract
Sensor network deployment is very challenging due to hostile and unpredictable nature of usage environments. In this letter, we propose two methods for the self-deployment of mobile sensors. The first one is a randomized solution that provides both simplicity and applicability to different environments. Inspired by simulated annealing, it improves both speed and energy conservation of the deployment process. The other method is suggested for environments where sensors form a connected graph, initially. At the cost of this extra limitation, we gain considerable improvements. © 2006 IEEE
Real-Time Fusion of Asynchronous Data in Distributed Sensor Networks
,
Ph.D. Dissertation
Sharif University of Technology
;
Hemmatyar, A. M. Afshin
(Supervisor)
Abstract
Real-time asynchronous data fusion for high-speed phenomena is an important and challenging task in the sensor networks. Examples of data fusion applications in sensor networks are: managing the traffic of maneuvering airplanes and ground vehicles in airside areas of an airport, traffic management in streets and roads, Driver Assistance Systems, guidance of antiaircraft and antimissile missiles. In all the data fusion applications the estimation of the required variables is necessary.
In this research two methods are introduced for real-time asynchronous data fusion, especially for track-to-track fusion of high-speed phenomena in sensor networks. The effectiveness and usability of these...
In this research two methods are introduced for real-time asynchronous data fusion, especially for track-to-track fusion of high-speed phenomena in sensor networks. The effectiveness and usability of these...
Concurrent orbit and attitude estimation using minimum sigma point unscented Kalman filter
, Article Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering ; Vol. 228, issue. 6 , 2014 , p. 801-819 ; Pourtakdoust, S. H ; Sharif University of Technology
Abstract
Concurrent orbit and attitude determination (COAD) plays a key role in reducing the cost of navigation and control subsystem for small satellites. This article is devoted to the problem of the COAD of satellites. A measurement package consisting of three axis magnetometer (TAM) and a sun sensor is shown to be sufficient to estimate the attitude and orbit information. To this end, an autonomous gyro-less COAD algorithm is proposed and implemented through the centralized data fusion of the TAM and the sun sensor. The set of nonlinear-coupled roto-translation dynamics of the satellite is used with a modified unscented Kalman filter (MUKF) to estimate the full satellite states. The MUKF is...
Sharif-Human movement instrumentation system (SHARIF-HMIS): Development and validation
, Article Medical Engineering and Physics ; Volume 61 , 2018 , Pages 87-94 ; 13504533 (ISSN) ; Akbari, A ; Zobeiri, O ; Rashedi, E ; Parnianpour, M ; Sharif University of Technology
Elsevier Ltd
2018
Abstract
The interest in wearable systems among the biomedical engineering and clinical community continues to escalate as technical refinements enhance their potential use for both indoor and outdoor applications. For example, an important wearable technology known as a microelectromechanical system (MEMS) is demonstrating promising applications in the area of biomedical engineering. Accordingly, this study was designed to investigate the Sharif-Human Movement Instrumentation System (SHARIF-HMIS), consisting of inertial measurement units (IMUs), stretchable clothing, and a data logger—all of which can be used outside the controlled environment of a laboratory, thus enhancing its overall utility....
Accuracy improvement of GPS/INS navigation system using extended kalman filter
, Article 6th International Conference on Control, Instrumentation and Automation, ICCIA 2019, 30 October 2019 through 31 October 2019 ; 2019 ; 9781728158150 (ISBN) ; Haeri, M ; Iranian Society of Instrumentation and Control Engineers; Smart/Micro Grids Research Center; University of Kurdistan ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2019
Abstract
Inertial navigation is a method for determining position and orientation of a vehicle, which operates according to Newton's laws of motion. Due to continual increase of output error because of measurement noise, bias, misalignment and so on, one may need one or more additional navigation systems to improve accuracy in long-Term navigation. In this paper, the error compensation based on GPS/INS data fusion algorithm is studied. Then, by designing a DSP processor-based hardware, GPS and INS data are recorded and GPS/INS data fusion algorithm is implemented. Results indicate that the accuracy of the positioning is improved and position, velocity, and orientation errors are confined to a limited...
A robust short-circuit fault diagnosis for high voltage DC power supply based on multisensor data fusion
, Article 10th International Power Electronics, Drive Systems and Technologies Conference, PEDSTC 2019, 12 February 2019 through 14 February 2019 ; 2019 , Pages 659-664 ; 9781538692547 (ISBN) ; Kaboli, S ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2019
Abstract
Short-circuit fault (SCF) detection is mandatory in a high voltage DC power supply (HVPS) to prevent fatal damage. The majority of converters employ a single sensor to detect the SCF. This attribute increases the interference vulnerability of the fault detection (FD) system in the presence of noise. Therefore, miss detections and false alarms are possible to occur. Miss detections and false alarms are harmful catastrophes in most applications. A commonly used method to suppress the noise impacts is using a low-bandwidth low-pass filter. However, the use of the low-bandwidth low-pass filter reduces the speed of FD due to the filter delay. This paper proposes a fast FD algorithm based on...
A novel adaptive tracking algorithm for maneuvering targets based on information fusion by neural network
, Article EUROCON 2007 - The International Conference on Computer as a Tool, Warsaw, 9 September 2007 through 12 September 2007 ; December , 2007 , Pages 818-822 ; 142440813X (ISBN); 9781424408139 (ISBN) ; Sadati, N ; Sharif University of Technology
2007
Abstract
The current statistical model and adaptive filtering (CSMAF) algorithm is one of the most effective methods for tracking the maneuvering targets. However, it is still worthy to investigate the characteristics of the CSMAF algorithm, which has a higher precision in tracking the maneuvering targets with larger accelerations while it has a lower precision in tracking the maneuvering targets with smaller acceleration. In this paper a novel adaptive tracking algorithm for maneuvering targets is proposed. To overcome the disadvantage of the CSMAF algorithm, a simple multi-layer feedforward neural network (NN) is used By introducing NN, two sources of information of the filter are fused while its...
A New Algorithm for Multiple RF Sources Localization by Means of a Group of Robots
, M.Sc. Thesis Sharif University of Technology ; Bagheri Shouraki, Saeed (Supervisor)
Abstract
The main subject of this project is to present a new algorithm for multiple RF sources localization by means of a group of robots. This problem (locating multiple radio sources) could be utilized in many domains, either military (passive radars) or civil (search and rescue) uses. Confronting detrimental effects of real environment on wave’s propagation pattern is the main challenge in this problem. Optimized movement of robots has been chosen as basic strategy to overcome this challenge. Presenting a general solution for this problem requires researches in four topics. The first one is simulation of environment and sensor with main objective of evaluating obtained algorithms’ performance....
A Novel Model for Three-Dimensional Imaging Using Interferometric ISAR in Curved Target Flight Paths
, Ph.D. Dissertation Sharif University of Technology ; Bastani, Mohammad Hasan (Supervisor)
Abstract
A Synthetic Aperture Radar (SAR) is a system which collects the received signal from a ground target area along linear motion of a flying vehicle carrying it, in order to provide a very high resolution 2D image of it. In Inverse SAR (ISAR), the radar is fixed on the ground and the data collection is performed along the linear motion of the aerial target. Using a second receiver antenna close to the main transceiver antenna of ISAR, it is possible to make a three-dimensional (3D) image of the target, or equivalently find the 3D coordinates of the target scattering points. Such system is called bistatic, monopulse or interferometric ISAR (InISAR). In the conventional model of ISAR, the flying...
Applying of Data Fusion Method for Improving the Protection System of the High Voltage DC Power Supply
, M.Sc. Thesis Sharif University of Technology ; Kaboli, Shahriyar (Supervisor)
Abstract
Short-circuit fault detection is mandatory in a high voltage DC power supply to prevent fatal damage. The majority of converters employ a single sensor to detect the short-circuit fault. This attribute increases the interference vulnerability of the fault detection system in the presence of noise. Therefore, miss detections and false alarms are possible to occur. Miss detections and false alarms are harmful catastrophes in most applications. A commonly used method to suppress the noise impacts is using a low-bandwidth low-pass filter. However, the use of the low-bandwidth low-pass filter reduces the speed of fault detection due to the filter delay. This paper proposes a fast fault detection...
Sensory Circuit For Security Robot
, M.Sc. Thesis Sharif University of Technology ; Vosoughi Vahdat, Bijan (Supervisor)
Abstract
The fire event may cause danger to life and property. In general, most fire-detection devices are set on the wall or ceiling. . However, this method is not flexible enough to detect a fire occurrence, and this needs the use of many fire-detection devices in a building. Since it is not suitable, we use an active fire-detection device to detect a fire incident. In the past, smoke sensors were used for fire detection, but often the smoke sensors triggered a false alarm when someone smoked in the room. Therefore, multisensor fire-detection methods are one of the current important developments for fire- detection technology. We design a fire-detection module using an ionization smoke sensor...
Image Flow and INS Sensor Fusion for the Accurate Localization of Planner Micro Robots
, M.Sc. Thesis Sharif University of Technology ; Vossoughi, Gholamreza (Supervisor)
Abstract
This research focuses on the robust mobile robot localization exploiting motion information acquired from an optical mouse operating based on optical flow technology. Most techniques of visual motion measurement are based on the well research discipline called “optical flow”. Theoretically, optical flow as a method of localization can be highly accurate, but it is sensitive to the noise and surface texture/optical characteristics and distance variations between the CCD detector and surface. As one could not achieve acceptable results in practical situations, to handle these problems, we propose to attach an acceleration – gyro (INS) sensor on the CCD detector (optical mouse) to improve the...
Human Leg Motion Tracking by IMU and single Camera Data Fusion using Extended Kalman Filter
, M.Sc. Thesis Sharif University of Technology ; Alasty, Aria (Supervisor) ; Salarieh, Hassan (Co-Advisor)
Abstract
Human motion capture is frequently used to study rehabilitation and clinical problems, as well as to provide realistic animation for the entertainment industry. IMU based systems as well as Marker based motion tracking systems are of most popular methods to track movement due to their low cost of implementation and lightweight. Results of IMU leads to unacceptable drift errors while marker based systems are Drift-free. Also, unlike cameras, IMUs are suitable for long-distance motion capturing. Based on the complementary properties of marker based systems and the inertial sensors, in this work, an Extended Kalman Filter approach was developed to fuse the data of two IMUs and a single camera...
Crop Classification using Sentinel-Image Timeseries and Deep Learning
, M.Sc. Thesis Sharif University of Technology ; Manzuri, Mohammad Taghi (Supervisor)
Abstract
Crop classification is one of the most important applications of remote sensing in agriculture. Knowing what crops are on the farm is invaluable both on a micro and macro scale. For example, this information can be used to design and imple- ment agricultural policies, product management and ensure food security. Also, this information can be used as a prerequisite for implementing other programs at the farm scale, such as monitoring and detecting anomalies during the crop growth cycle. Most of the studies in this field are focused on the optical data of the Sentinel-2 satel- lite, but the optical data are vulnerable to atmospheric conditions, and on the other hand, there is valuable...
Multi-Sensor Data Fusion with Deep Learning in Semantic Segmentation
, M.Sc. Thesis Sharif University of Technology ; Kasaei, Shohreh (Supervisor)
Abstract
In image processing applications, sensors (Camera, LiDAR and Stereo) are essential for scene perception and Deep learning methods outperform most of the image processing tasks like 3D and 2D object detection and semantic segmentation. Different sensors are used in image processing tasks. Sensor fusion is using multiple sensors data to get better performance. Each sensor captures different data (e.g, color, texture, and depth). Some of them are distorted in inclement weather, intense illuminance changes, and dark environments which multi-sensor data fusion is used to overcome sensor weaknesses. One of the most important fields that sensor fusion used is Auto Driving cars (AD). Different...
Multiple human tracking using PHD filter in distributed camera network
, Article Proceedings of the 4th International Conference on Computer and Knowledge Engineering, ICCKE 2014 ; 2014 , pp. 569-574 ; ISBN: 9781479954865 ; Jamzad, M ; Sharif University of Technology
Abstract
The Gaussian mixture probability hypothesis density (GM-PHD) filter is a closed form approximation of the multi-target Bayes filter which can overcome most multitarget tracking problems. Limited field of view, decreasing cost of cameras, and advances of using multi-camera induce us to use large-scale camera networks. In this paper, a multihuman tracking framework using the PHD filter in a distributed camera network is proposed. Each camera tracks objects locally with PHD filter and a track-after-detect scheme and its estimates of targets are sent to neighboring nodes. Then each camera fuses its local estimates with it's neighbors. The proposed method is evaluated on the public PETS2009...
How to synchronize and register an optical-inertial tracking system
, Article Applied Mechanics and Materials ; Volume 332 , 2013 , Pages 130-136 ; 16609336 (ISSN) ; 9783037857335 (ISBN) ; Akbar, M ; Farahmand, F ; Sharif University of Technology
2013
Abstract
Multi-sensor tracking is widely used for augmentation of tracking accuracy using data fusion. A basic requirement for such applications is the real time temporal synchronization and spatial registration of two sensory data. In this study a new method for time and space coordination of two tracking sensor measurements has been presented. For spatial registration we used a body coordinate system and then applied the effect of the level arm. The time synchronization was done based on least mean square (LMS) error method. This method was implemented to synchronize the position and orientation of an object using Inertial (1IMU) and Optical (Optotrak) tracking systems. The results of synchronized...