Search for: unscented-kalman-filtering
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    Extended and Unscented Kalman filters for parameter estimation of an autonomous underwater vehicle

    , Article Ocean Engineering ; Vol. 91, issue , 2014 , p. 329-339 Sabet, M. T ; Sarhadi, P ; Zarini, M ; Sharif University of Technology
    In this paper, a high performance procedure for estimating of hydrodynamic coefficients in Autonomous Underwater Vehicles (AUV's) is proposed. In modeling of an AUV, experimental data should be verified and validated using appropriate techniques. Due to implementation complexity in calculating methods, computation of hydrodynamic parameters is challenging. This paper presents analytical approaches for estimating an AUV's hydrodynamic coefficients. Nonlinear Kalman Filter (KF) algorithms are implemented to estimate unknown augmented states (coefficients). A comparative study is conducted which shows the superior performance of Unscented Kalman Filter (UKF) in comparison with Extended Kalman... 

    Fin failure diagnosis for non-linear supersonic air vehicle based on inertial sensors

    , Article Advances in Aircraft and Spacecraft Science ; Volume 7, Issue 1 , 2020 , Pages 1-17 Ashrafifar, A ; Fathi Jegarkandi, M ; Sharif University of Technology
    Techno Press  2020
    In this paper, a new model-based Fault Detection and Diagnosis (FDD) method for an agile supersonic flight vehicle is presented. A nonlinear model, controlled by a classical closed loop controller and proportional navigation guidance in interception scenario, describes the behavior of the vehicle. The proposed FDD method employs the Inertial Navigation System (INS) data and nonlinear dynamic model of the vehicle to inform fins damage to the controller before leading to an undesired performance or mission failure. Broken, burnt, unactuated or not opened control surfaces cause a drastic change in aerodynamic coefficients and consequently in the dynamic model. Therefore, in addition to the... 

    An adaptive unscented Kalman filter for quaternion-based orientation estimation in low-cost AHRS

    , Article Aircraft Engineering and Aerospace Technology ; 2007 , Pages 485-493 ; 00022667 (ISSN) ; Volume 79, Issue 5 Pourtakdoust, S. H ; Ghanbarpour Asl, H ; Sharif University of Technology
    Purpose - This paper aims to develop an adaptive unscented Kalman filter (AUKF) formulation for orientation estimation of aircraft and UAV utilizing low-cost attitude and heading reference systems (AHRS). Design/methodology/approach - A recursive least-square algorithm with exponential age weighting in time is utilized for estimation of the unknown inputs. The proposed AUKF tunes its measurement covariance to yield optimal performance. Owing to nonlinear nature of the dynamic model as well as the measurement equations, an unscented Kalman filter (UKF) is chosen against the extended Kalman filter, due to its better performance characteristics. The unscented transformation of the UKF is shown... 

    Power System State Estimation Including PMUs and Traditional Measurement Instruments

    , M.Sc. Thesis Sharif University of Technology Abootorabi Zarchi, Dawood (Author) ; Hosseini, Hamid (Supervisor)
    State estimation is a process in which values of unknown system state variables is obtained by considering measurements in such a system. State estimators’ output data are applied in control centers of power systems. Nowadays, using of phasor measurement unit (PMU) in WAMS (Wide Area Measurement Systems) and SCADA have significantly extended. PMUs increase the accuracy proportion compared with traditional measurement units, improve the power networks observability as well as detect and correct bad data. Since the possibility of removing the traditional measurement devices and replacing them with full PMU ones does not exist in the near future it is mandatory to find out an efficient and... 

    Satellite Attitude Estimation Using MEMS

    , M.Sc. Thesis Sharif University of Technology Mirzaei Teshnizi, Masoud (Author) ; Pourtakdoost, Hossein (Supervisor)
    This thesis deals with the attitude estimation based on low cost sensor for a micro satellite in a circular, low earth orbit (LEO) and sensor calibration. With two body problem theory and Quaternion formulation, rotational motion is modeled. In addition gravity gradient effect is considered on satellite orbital elements. Using a 3-axis MEMS-based magnetometer and a sun sensor as two measurement systems, low cost attitude estimation is proposed. Bias and Scale factor are presented to model deterministic sensor error and white Gaussian noise to model stochastic sensor error. It is shown that by sensor calibration the estimation accuracy will improve. Non-linear estimation methods EKF, SRUKF... 

    IMU and Kinect Data Fusion for Human Arm Motion Tracking Using Unscented Kalman Filter

    , M.Sc. Thesis Sharif University of Technology Atrsaei, Arash (Author) ; Salarieh, Hassan (Supervisor) ; Alasti, Aria (Co-Advisor)
    Due to various applications of human motion capture techniques, developing low-cost methods that would be applicable in non-laboratory environments is under consideration. MEMS inertial sensors and Kinect are two low-cost devices that can be utilized in home-based motion capture systems, e.g. home-based rehabilitation. In this work, an unscented Kalman filter approach was developed based on the complementary properties of Kinect and the inertial sensors to fuse the orientation data of these two devices for human arm motion tracking during both stationary shoulder joint position and human body movement. A new measurement model of the fusion algorithm was obtained that can compensate for the... 

    Calibration of Rigid Connected Vision and Inertial Sensors

    , M.Sc. Thesis Sharif University of Technology Ebrahimi, Mohsen (Author) ; Manzuri, Mohammad Taghi (Supervisor)
    One of the major problems encountered in artificial intelligence is environment interaction. A sensible way for around-interaction is to collect information from sensors and make proper reactions. Generally, in the real world, an intelligent agent needs to know its pose. There are several ways to know the pose of an agent. One of them is based on the fusion of the output of an inertial sensor with the information retrieved from a camera. This leads to enhance the estimation of the pose of an agent. In this research different solutions for this problem are compared. Studies are done with the goal of attitude detection for vehicles and mini-robots, moving on planar surface. For this end, we... 

    Integrated Magnetometer-Horizon Sensor Low-Earth-Orbit Determination

    , M.Sc. Thesis Sharif University of Technology Farahani far, Mohammad (Author) ; Asadian, Nima (Supervisor)
    In this thesis, the orbit determination of Low Earth Orbits (LEO) using the integrated magnetometer and horizon sensor data has been investigated. Orbit determination is an essential part of a space mission. Not only the modeling, guidance, navigation and control errors may results in error in injecting the satellite into its nominal orbit, the environmental disturbances deviate the satellite from its predicted orbit and from an operational perspective most satellites need continuous orbit determination. Traditionally, ground based orbit determination is used which are non-autonomous and expensive and just can be used for specific times which the satellite can be observed from the ground... 

    Integrated magnetometer-horizon sensor low-earth orbit determination using UKF

    , Article Acta Astronautica ; Volume 106 , January–February , 2015 , Pages 13-23 ; 00945765 (ISSN) Farahanifar, M ; Assadian, N ; Sharif University of Technology
    Elsevier Ltd  2015
    The estimation of the satellite orbital elements using the integrated magnetometer and horizon sensors data has been investigated in this study. These sensors are generally employed for attitude estimation. The magnetometer and the horizon sensor measure the Earths magnetic field as well as the Earths center direction in the body frame, respectively. The magnitude of the magnetic field and the angle between two vectors have been used for orbit estimation purpose. This excludes the knowledge of the attitude in the orbit determination. The Gaussian variation of parameters equations is used for the orbital motion dynamical model to have the orbital elements as the states of the system. Since... 

    Modification of unscented kalman filter using a set of scaling parameters

    , Article IET Signal Processing ; Volume 12, Issue 4 , 2018 , Pages 471-480 ; 17519675 (ISSN) Zarei Jalalabadi, M ; Malaek, M. B ; Sharif University of Technology
    Institution of Engineering and Technology  2018
    This work, based on the standard unscented Kalman filter (UKF), proposes a modified UKF for highly non-linear stochastic systems, assuming that the associated probability distributions are normal. In the standard UKF with 2n + 1 sample points, the estimated mean and covariance match the true mean and covariance up to the third order, besides, there exists a scaling parameter that plays a crucial role in minimising the fourth-order errors. The proposed method consists of a computationally efficient formulation of the unscented transform that incorporates N - 1, N ≥ 2, constant parameters to scale 2n(N - 1) + 1 sample points such that the 2Nth order errors are minimised. The scaling parameters... 

    Data-driven buiding climate control using model prediction and online weather forecast data

    , Article ; July , 2020 , Pages 1801-1806 Mohammadzadeh Mazar, M ; Rezaei Zadeh, A ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2020
    This paper proposes a multi-unit building model, in which the parameters are obtained via an online identification process. The identification process is carried out on-the-fly so it can update the best model of the building units. A model predictive controller (MPC) is also employed that uses the prediction of the building model, as well as the weather forecast data and acts on the heating boiler in an optimal fashion. In addition, since the controller is designed for a multi-unit building, it is crucial to estimate the amount of the delay that takes the hot flow to reach the units. This paper presents a very simple method for the delay identification based on unscented kalman filter. For... 

    A Wearable pedestrian localization and gait identification system using kalman filtered inertial data

    , Article IEEE Transactions on Instrumentation and Measurement ; Volume 70 , 2021 ; 00189456 (ISSN) Hajati, N ; Rezaeizadeh, A ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2021
    In this article, we introduce a pedestrian dead reckoning (PDR)-based navigation device that does not require global navigation satellite system (GNSS) signals or beacons and works with an inertial measurement unit (IMU) mounted on its waist belt. The system identifies the individual by their walking pattern to use the proper gains in the computations, estimates the attitude by applying an unscented Kalman filter, and finally derives the position in three dimensions with the help of a step detection algorithm. The experimental results show an outdoor 4.7-km walk resulting in an error of 0.96%. © 1963-2012 IEEE  

    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 Kiani, M ; Pourtakdoust, S. H ; Sharif University of Technology
    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... 

    Human arm motion tracking by inertial/magnetic sensors using unscented kalman filter and relative motion constraint

    , Article Journal of Intelligent and Robotic Systems: Theory and Applications ; 2017 , Pages 1-10 ; 09210296 (ISSN) Atrsaei, A ; Salarieh, H ; Alasty, A ; Abediny, M ; Sharif University of Technology
    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... 

    Motion estimation of uncooperative space objects: A case of multi-platform fusion

    , Article Advances in Space Research ; Volume 62, Issue 9 , 2018 , Pages 2665-2678 ; 02731177 (ISSN) Zarei Jalalabadi, M ; Malaek, S. M. B ; Sharif University of Technology
    Elsevier Ltd  2018
    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... 

    Model identification of a Marine robot in presence of IMU-DVL misalignment using TUKF

    , Article Ocean Engineering ; Volume 206 , 2020 Ghanipoor, F ; Alasty, A ; Salarieh, H ; Hashemi, M ; Shahbazi, M ; Sharif University of Technology
    Elsevier Ltd  2020
    In today's world, control and navigation of autonomous underwater vehicles (AUVs) are quite challenging issues. In these fields, obtaining an identified dynamic model of AUV is a vital part. In this paper, a method for parameter estimation of an AUV planar model is proposed, which uses augmented state space technique and Square Root Transformed Unscented Kalman Filter (SR-TUKF) as an estimator. Furthermore, by modeling, misalignment between Inertial Measurement Unit (IMU) and Doppler Velocity Log (DVL) is estimated, simultaneously. Parameter identification is conducted using data of an AUV, equipped with Gyroscope, DVL and Encoder for measuring control inputs, in a planar maneuver. According... 

    Autonomous Orbit and Attitude Estimation of Satellite Using Star Sensor and Earth Sensor

    , M.Sc. Thesis Sharif University of Technology Hosseini Moghaddam, Mohammad Hossein (Author) ; Ghanbarpour Asl, Habib (Supervisor)
    In this Thesis, attitude and orbit of a satellite is estimated using a star sensor and an earth sensor. An algorithm has been developed to estimate satellite attitude and orbit that can be implement on a satellite as strap-down hardware. This system has an uncomplicated implementation compared with platform based systems. That mentioned algorithm estimates satellite orbit by using identified star vectors via star sensor and identified earth vector via earth sensor simultaneously. It also knows the stars vectors according to Star Catalog. Attitude estimation is also executed using both star and earth sensor. It has to be said that an Unscented Kalman Filter synthesize both sensors output data... 

    Inertial Navigation System Error Correction by Combining IMU Unit Information and Consecutive Images in an Unknown Environment

    , M.Sc. Thesis Sharif University of Technology Dehghani Firouzabadi, Abbas (Author) ; Nobahari, Hadi (Supervisor) ; Ghanbarpour Asl, Habib (Supervisor)
    In this research, INS error will be corrected with the help of the unscented kalman filter, by combining the IMU sensors and flight consecutive images information. Measurement equation of the Kalman filter is the epipolar Constraint of geometry of two consecutive images of the camera. In epipolar Constraint, the common points of two consecutive images of the camera field of view have an important role. This points will be extracted by SIFT and SURF algorithms. These algorithms have many mistakes in the process of images matching, but in this research, a solution based on the error covariance of the position of the ground point corresponding to the two common points of two images is presented... 

    Attitude and Deformation Estimation of Flexible Satellite Using Magnetometer and Sun Sensor

    , M.Sc. Thesis Sharif University of Technology Ghani, Marzieh (Author) ; Asadian, Nima (Supervisor)
    The estimation of attitude and deformation of a flexible satellite using magnetometer and sun sensor data are studied in this thesis. To this end, the dynamical differential equations of the flexible satellite have been derived using Lagrange’s equation. These equations of motion are then utilized for the purpose of simulation and verification. After introducing the measurements equations, the observability of the satellite with flexible panels has been evaluated. Afterward, the attitude of the satellite body and deformation of the flexible panels have been estimated by EKF (Extended Kalman Filter) as well as UKF (Unscented Kalman Filter). The results show that the estimations using UKF are... 

    Autonomous Orbit Estimation for Regional Navigation Satellites

    , M.Sc. Thesis Sharif University of Technology Memaran, Mohsen (Author) ; Asadian, Nima (Supervisor)
    In this thesis, autonomous orbit estimation of regional navigation satellites has been investigated. Estimation of satellite orbit is an integral part of satellite navigation, which may be executed via assistance of ground station. As the satellite is exposed to the ground station view, range, direction and rate of range is measured by mean of ranging instrumentation relative to ground reference, hence the precise position is calculated. In this thesis a set of satellites are investigated in a unique structure called constellation with the purpose of navigation. The occurrence which is likely to happen in this condition, is the failure of ground station under certain circumstances or losing...