Sharif Digital Repository

Sound source localization has always been one of the most challenging subjects in different fields of engineering, one of the most important of which being tracking of flying objects. This article focuses on sound source localization using fuzzy fusion and a beamforming method. It proposes a new fuzzy-based algorithm for localizing a sound source using distributed sensor nodes. Eight low-cost sensor nodes have been constructed in this study each of which consists of a microphone array to capture sound waves. Each node is able to record audio signals synchronously on an SD card to evaluate different algorithms offline. However, the sensor nodes are designed to be able to estimate the location... 

With the advent of new positioning services, one can reach more satellites these days to find his position. Using a combination of satellites which belong to different constellations needs some considerations like addressing biases between their time references. Each constellation has progressed to the point that they have enough satellites to provide accurate position separately. According to this fact, we propose to find the position in each constellation and fusion their results in a way that final position has the minimum possible variance instead of combining the constellations in a satellite level and dealing with inter system biases. Experimental studies are conducted based on IGS... 

Distributed spectrum sensing (DSS) is of great importance in Cognitive Radio, especially under fading or shadowing effects. In order to evaluate the performance of a distributed system, it is commonly compared with the centralized system as an upper performance bound. Now the question is whether or not one can obtain a distributed strategy serving as an upper bound to benchmark any distributed strategy, tighter than that of the centralized scheme. Here, we suggest employing the Neyman-Pearson (NP) fusion rule to achieve an upper bound. Furthermore, the analysis of a randomized fusion rule has been provided, which is a long-existing problem in this field. For this purpose, theoretical... 

In this study, we consider the role of multisensor data fusion in neuromuscular control using an actor-critic reinforcement learning method. The model we use is a single link system actuated by a pair of muscles that are excited with alpha and gamma signals. Various physiological sensor information such as proprioception, spindle sensors, and Golgi tendon organs have been integrated to achieve an oscillatory movement with variable amplitude and frequency, while achieving a stable movement with minimum metabolic cost and coactivation. The system is highly nonlinear in all its physical and physiological attributes. Transmission delays are included in the afferent and efferent neural paths to... 

Asynchronous data fusion is inevitable in track-to-track fusion for tracking high-speed targets. For low-speed targets, e.g., the movement of clouds, synchronization is insignificant and, depending on the application, may be disregarded. Real-time asynchronous fusion is a demanding task in sensor networks when the sensors are not synchronous in sampling-rate or in sampling-phase. In the method proposed in this paper, an estimator in the fusion center estimates the actual time of the sample with respect to the time-reference of the fusion center upon receiving the data from a sensor. Then, the computer of the fusion center uses predictions to transfer all the received data to the data... 

Human tracking is an essential step in many computer vision-based applications. As single view tracking may not be sufficiently robust and accurate, tracking based on multiple cameras has been widely considered in recent years. This paper presents a distributed human tracking method in a smart camera network and introduces a particle filter design based on Histogram of Oriented Gradients (HOG) and color histogram. The proposed adaptive motion model also estimates the target speed from the history of its latest displacement and improves the robustness of the tracker by decreasing the probability of missing targets. In addition, a distributed data fusion method is proposed which fuses the... 

Human movement analysis is an important part of biomechanics and rehabilitation, for which many measurement systems are introduced. Among these, wearable devices have substantial biomedical applications, primarily since they can be implemented both in indoor and outdoor applications. In this study, a Trunk Motion System (TMS) using printed Body‐Worn Sensors (BWS) is designed and developed. TMS can measure three‐dimensional (3D) trunk motions, is lightweight, and is a portable and non‐invasive system. After the recognition of sensor locations, twelve BWSs were printed on stretchable clothing with the purpose of measuring the 3D trunk movements. To integrate BWSs data, a neural network data... 

Human motion tracking has many applications in biomedical and industrial services. Low-cost inertial/magnetic sensors are widely used in human motion capture systems to obtain the orientation of the human body segments. In this paper, we have presented a quaternion-based unscented Kalman filter algorithm to fuse inertial/magnetic sensors measurements for tracking human arm movements. In order to have a better estimation of the orientation of the forearm and the upper arm, a constraint equation was developed based on the relative velocity of the elbow joint with respect to the inertial sensors attached to the forearm and the upper arm. Also to compensate for fast body motions, we adapted the... 

Powerful universal steganalyzers were proposed in the literature during the past few years. In addition some studies have been conducted on improvements of current steganalysis results using information fusion techniques, merging available feature vectors, etc. This paper presents two independent ideas, which can be used together, to obtain higher accuracy in detecting stego images. First, we propose the use of boosted fusion methods to aggregate outputs of multiple steganalyzers. Second, we investigate how passing high frequencies through filtering can enhance the results of steganalysis techniques. In this work, it is shown that, through different tests over the state-of-the-art... 

In this work, we have examined the problem of distributed consensus averaging over senor networks from a novel point of view considering the need for security. We have proposed a method for incorporating privacy into the scalable average consensus mechanisms. Our proposed method, Random Projections Method (RPM), is lightweight and transparent since it is not based on cryptography and does not require any change in the fusion system. RPM is based on introducing a simple, yet effective pre-fusion algorithm. We mathematically derived the correctness of RPM and analyzed its effect on convergence of the system through simulation. Robustness of RPM against honest-but-curious adversaries is... 

Human motion tracking has many applications in biomedical and industrial services. Low-cost inertial/magnetic sensors are widely used in human motion capture systems to obtain the orientation of the human body segments. In this paper, we have presented a quaternion-based unscented Kalman filter algorithm to fuse inertial/magnetic sensors measurements for tracking human arm movements. In order to have a better estimation of the orientation of the forearm and the upper arm, a constraint equation was developed based on the relative velocity of the elbow joint with respect to the inertial sensors attached to the forearm and the upper arm. Also to compensate for fast body motions, we adapted the... 

In this paper, we investigate the problem of detecting and monitoring changes (abnormality) in molecular communication (MC), using the quickest change detection (QCD) schemes. The objective is to watch an environment using a sensor network and make decisions on the time and location of changes based on the received signals from sensors in the fusion center (FC). Such assumptions call for considering spatial and temporal correlations among sensors' transmitting signals. We use the framework of Partially Observable Markov Decision Processes (POMDPs) based on non-homogeneous Markov models. The metric in detection (stopping-time) scenario is to minimize the delay of announcing an abnormality... 

Efficient combination of MIMO (multiple-input multiple-output) and PCL (passive coherent location) ideas is expected to improve performance of localization schemes. While, in general, adding the number of transmit and receive antennas provides spatial diversity, it is possible to obtain similar effects by using multiple transmitters that are already transmitting standard signals (such as digital TV (DTV) transmission) in the environment (also known as illuminators of opportunity). However, in the case of passive schemes, it is not always possible to ensure that signals of different transmitters are orthogonal to each other. In such cases in which nonorthogonal transmitter signals are to be...