Sharif Digital Repository

An algorithm, by cooperation of multiple flying vehicles, is developed to localize a moving target in the presence of measurement noise and mis-modeling. It works based on jointly sharing information and data fusion by using a recursive Bayesian estimator and a searching guidance law to direct each flying vehicle to a position where the probability of target detection is maximum. To evaluate this algorithm, a high fidelity simulation program with six degrees of freedom dynamics is also developed  

We define model-data interaction (MDI) as a two way process between models and data, in which on one hand data can serve the modeling purpose by supporting model discrimination, parameter refinement, uncertainty analysis, etc., and on the other hand models provide a tool for data fusion, interpretation, interpolation, etc. MDI has many applications in the realm of groundwater and has been the topic of extensive research in the groundwater community for the past several decades. This has led to the development of a multitude of increasingly sophisticated methods. The progress of data acquisition technologies and the evolution of models are continuously changing the landscape of groundwater... 

Attitude determination for underwater vehicles in control and navigation applications has been always an important issue. MEMS-based accelerometer and gyroscope data can be usually used to determine the underwater vehicle attitude. However, the gyroscope sensors suffer from bias problem and the accelerometer data is not reliable in the presence of the external acceleration for the attitude determination. Therefore, data fusion for these two sensors is used to determine the attitude. But it should be noted that the common fusion algorithm does not perceive some special maneuvering accelerated motions and the use of accelerometer data causes a mistake in determining the Euler angles in these... 

Underwater navigation is generally accomplished through the data fusion of INS (Inertial Navigation System) and auxiliary sensors such as DVL (Doppler Velocity Logger) sensor. However, because of the possibility of DVL outage, alternative low-cost solutions are attractive. Among these, one is using vehicle kinetic model information extracted by the Newton-Euler equation to improve INS performance, which is called model-aided navigation. In this paper, only the vehicle translational motion dynamics are used to replace DVL in underwater navigation in DVL outage. The vehicle 3D translational dynamics has been obtained by using general Newton-Euler equations. Integrating these dynamics leads to... 

Vacuum arc is one of the most important failure factors of the vacuum tubes. The amount of delivered energy from the high-voltage dc power supply to the vacuum tube is an important issue during the vacuum arc in the tube. Vacuum arc acts as a short-circuit fault (SCF) at the power supply output. The majority of converters use a single current sensor to measure only the converter output current for detecting the SCF. However, the sensor may provide unreliable data because of the noise effect. Application of a low-pass filter reduces the noise effect. Regarding the delay of the low-pass filter, the interval of arc detection increases and more energy is delivered to the tube. In this article, a... 

Haplotype information has become increasingly important in analyzing fine-scale molecular genetics data, Due to the mutated form in human genome; SNPs (Single Nucleotide Polymorphism) are responsible for some genetic diseases. As a consequence, obtaining all SNPs from human populations is one of the primary goals of studies in human genomics. In this paper, a data fusion method based on multiple parallel classifiers for reconstruction of haplotypes from a given sample Single Nucleotide Polymorphism (SNP) is proposed. First, we design a single greedy algorithm for solving haplotype reconstructions. [2] is used as an efficient approach to be combined with first classification method. The... 

The track fusion combines individual tracks formed by different sensors. Tracks are usually obtained by Kalman Filter (KF), since it is suitable for real-time application. The KF is an optimal linear estimator when the measurement noise has a Gaussian distribution with known covariance. However, in practice, some of the sensors do not have these properties, and the traditional KF is not an optimal estimator. In this paper, a novel adaptive Kalman filter (NAKF) is proposed. In this approach, the measurement noise covariance is adjusted by using an introduced simple mathematical function of one variable, called the degree of matching (DoM), where it is defined on the basis of covariance... 

The problem of gyrocompassing using inertial sensors, i.e., gyros and accelerometers, is addressed. North finding, with an order of accuracy of one arc-min, is not only required for the initial alignment of inertial navigation systems, but also has a critical role to play in the guidance and navigation of ships that navigate for long periods of time. In this work, after extracting the error model of an inertial navigation system and augmenting it with the error model of inertial sensors, a processing algorithm based on the Kalman filter is designed and simulated to process the navigation system velocity error, and to estimate and correct tilt and heading errors along with gyro drifts and... 

Facial Action Coding System consists of 44 action units (AUs) and more than 7000 combinations. Hidden Markov models (HMMs) classifier has been used successfully to recognize facial action units (AUs) and expressions due to its ability to deal with AU dynamics. However, a separate HMM is necessary for each single AU and each AU combination. Since combinations of AU numbering in thousands, a more efficient method will be needed. In this paper an accurate real-time sequence-based system for representation and recognition of facial AUs is presented. Our system has the following characteristics: 1) employing a mixture of HMMs and neural network, we develop a novel accurate classifier, which can... 

This work describes an efficient technique to sequentially combine estimates resulting from individual sets of measurements provided by a network of satellites. The prescribed method is especially effective to estimate motion states of an uncooperative space object using range image data. The technique, which is fast and suitable for on-line applications, could also be effective to capture stray objects or those satellites that require periodic servicing. Such missions call for high degree of precision and reliable estimation methods. In fact, the proposed estimation architecture consists of a network of synchronized platforms, i.e., Observer Satellites (OS), each with processing power and... 

This paper presents a system based on pedestrian dead reckoning (PDR) for localization of networked mobile users, which relies only on sensors embedded in the devices and device- to-device connectivity. The user trajectory is reconstructed by measuring step by step the user displacements. Though step length can be estimated rather accurately, heading evaluation is extremely problematic in indoor environments. Magnetometer is typically used, however measurements are strongly perturbed. To improve the location accuracy, this paper proposes a novel cooperative system to estimate the direction of motion based on a machine learning approach for perturbation detection and filtering, combined with... 

Vacuum arc is one of the most important failure factors of the vacuum tubes. The amount of delivered energy from the high-voltage dc power supply to the vacuum tube is an important issue during the vacuum arc in the tube. Vacuum arc acts as a short-circuit fault (SCF) at the power supply output. The majority of converters use a single current sensor to measure only the converter output current for detecting the SCF. However, the sensor may provide unreliable data because of the noise effect. Application of a low-pass filter reduces the noise effect. Regarding the delay of the low-pass filter, the interval of arc detection increases and more energy is delivered to the tube. In this article, a... 

INS-DVL integration is a common method for underwater navigation. However, inherent errors of sensors, especially in MEMS IMUs, lead to inaccuracies in estimating the position and attitude. In this paper, dynamic motion model of AUV is used to improve MEMS INS-DVL navigation. In this method, which is called model-aided or model-based navigation, the information of the kinetic model of the vehicle (obtained from Newton-Euler equations) is used to improve the navigation performance. Previous model-aided navigation studies about AUVs have been focused on the translational dynamic model of vehicles. As the best of our knowledge, this paper is the first one which suggests using a rotational... 

Underwater navigation is generally accomplished through the data fusion of INS (Inertial Navigation System) and auxiliary sensors such as DVL (Doppler Velocity Logger) sensor. However, because of the possibility of DVL outage, alternative low-cost solutions are attractive. Among these, one is using vehicle kinetic model information extracted by the Newton-Euler equation to improve INS performance, which is called model-aided navigation. In this paper, only the vehicle translational motion dynamics are used to replace DVL in underwater navigation in DVL outage. The vehicle 3D translational dynamics has been obtained by using general Newton-Euler equations. Integrating these dynamics leads to... 

In this article, time-varying formation tracking problem for multi-agent systems is investigated. It is assumed the number of agents is changing and obstacles should be avoided along the trajectory. In addition, the tracking formation should be reached while the leader trajectory is unknown and communication data are noisy. To reach the desired formation tracking, first, a virtual leader is constructed using the local neighbouring data. Second, the reference signal is created based on the virtual leader and the leader data (which is available for some agents). The data fusion at this stage is done based on Kalman filtering to reduce the effect of communication noise. Third, an integral state... 

By development of ocean exploration, autonomous vehicles are employed to perform on-water and underwater tasks. Using an extended Kalman filter, Inertial Navigation System/Doppler Velocity Log (INS/DVL) integrated systems are trying to navigate in oceans and underwater environments when Global Positioning System (GPS) signals are not accessible. The dependency of DVL signals on acoustic environments may cause any DVL malfunction due to sea creatures or strong wave-absorbing material. In this paper, an improved version of evolutionary TS-fuzzy (eTS) is proposed in order to predict DVL sensor outputs at DVL malfunction moment, by utilizing an artificial intelligent (AI) aided integrated... 

Fusion of high spectral but low spatial resolution multispectral and low spectral but high spatial resolution panchromatic satellite images is a very useful technique in various remote sensing applications, such as change detection. Recently, some studies showed that wavelet-based image fusion methods provide high quality spectral content of the fused image. However, most of wavelet-based methods have a spatial resolution of the fused result less than the Brovey, IHS, and PCA fusion methods. This is mainly because real wavelet transform cannot efficiently represent the singularity of linear/curved contents. In this paper, we introduce a new method based on the contourlet transform which...