Search results for "Kalman Filter"
showing 10 items of 108 documents
Real-time people counting system using a single video camera
2008
This is the copy of journal's version originally published in Proc. SPIE 6811. Reprinted with permission of SPIE: http://spie.org/x10.xml?WT.svl=tn7 There is growing interest in video-based solutions for people monitoring and counting in business and security applications. Compared to classic sensor-based solutions the video-based ones allow for more versatile functionalities, improved performance with lower costs. In this paper, we propose a real-time system for people counting based on single low-end non-calibrated video camera. The two main challenges addressed in this paper are: robust estimation of the scene background and the number of real persons in merge-split scenarios. The latter…
A statistical monitoring approach for automotive on-board diagnostic systems
2007
The current generation of vehicle models are increasingly being equipped with on-board diagnostic (OBD) systems aimed at assessing the ‘state of health’ of important anti-pollution subsystems and components. In order to promptly diagnose and fix quality and reliability problems that may potentially affect such complex diagnostic systems, even during advanced development prior to mass production, some vehicle prototypes undergo a testing phase under realistic conditions of use (a mileage accumulation campaign). The aim of this work is to set up a statistical tool for improving the reliability of the OBD system by monitoring its operation during the mileage accumulation campaign of a new vehi…
Peer to Peer Equation Augmentation for an Altitude Aided GNSS Receiver
2010
This paper considers the possibility to integrate external altitude measurements with a Kalman based Global Navigation Satellite System (GNSS) receiver in a peer to peer scenario. The performance of such a system is investigated for different characteristics of the aiding measurement and for different degree of trust of the receiver upon the aiding measurement. The aiding measurement is obtained starting from the altitude measurements that the other peers in the network send to the aided user. The experiments highlight the need for a parameter that points out the effectiveness and the consistency of the computed aiding measurement. To this purpose, a reliability index is proposed, on the ba…
Decentralized unscented Kalman filter based on a consensus algorithm for multi-area dynamic state estimation in power systems
2015
Abstract A decentralized unscented Kalman filter (UKF) method based on a consensus algorithm for multi-area power system dynamic state estimation is presented in this paper. The overall system is split into a certain number of non-overlapping areas. Firstly, each area executes its own dynamic state estimation based on local measurements by using the UKF. Next, the consensus algorithm is required to perform only local communications between neighboring areas to diffuse local state information. Finally, according to the global state information obtained by the consensus algorithm, the UKF is run again for each area. Its performance is compared with the distributed UKF without consensus algori…
State and parameter update in a coupled energy/hydrologic balance model using ensemble Kalman filtering
2012
Summary The capability to accurately monitor and describe daily evapotranspiration (ET) in a cost effective manner is generally attributed to hydrological models. However, continuous solution of energy and water balance provides precise estimations only when a detailed knowledge of sub-surface characteristics is available. On the other hand, residual surface energy balance models, based on remote observation of land surface temperature, are characterised by sufficient accuracy, but their applicability is limited by the lack of high frequency and high resolution thermal data. A compromise between these two methodologies is represented by the use of data assimilation scheme to include sparse …
Adaptive high-gain extended kalman filter and applications
2010
The work concerns the ``observability problem” --- the reconstruction of a dynamic process's full state from a partially measured state--- for nonlinear dynamic systems. The Extended Kalman Filter (EKF) is a widely-used observer for such nonlinear systems. However it suffers from a lack of theoretical justifications and displays poor performance when the estimated state is far from the real state, e.g. due to large perturbations, a poor initial state estimate, etc… We propose a solution to these problems, the Adaptive High-Gain (EKF). Observability theory reveals the existence of special representations characterizing nonlinear systems having the observability property. Such representations…
An Online Time Warping based Map Matching for Vulnerable Road Users’ Safety
2018
International audience; High penetration rate of Smartphones and their increased capabilities to sense, compute, store and communicate have made the devices vital components of intelligent transportation systems. However, their GPS positions accuracy remains insufficient for a lot of location-based applications especially traffic safety ones. In this paper, we developed a new algorithm which is able to improve smartphones GPS accuracy for vulnerable road users' traffic safety. It is a two-stage algorithm: in the first stage GPS readings obtained from smartphones are passed through Kalman filter to smooth deviated reading. Then an adaptive online time warping based map matching is applied to…
EKF-based estimation and control of electric drivetrain in offshore pipe racking machine
2016
A typical challenge for electric drivetrains is to reduce the number of sensors required for control action or system monitoring. This is particularly important for electric motors operating in offshore conditions, since they work in hostile environment which often damages data acquisition systems. Therefore, this paper deals with verification and validation of the extended Kalman filter (EKF) for sensorless indirect field-oriented control (IFOC) of an induction motor operating in offshore conditions. The EKF is employed to identify the speed of the induction motor based on the measured stator currents and voltages. The estimated speed is used in the motor speed control mode instead of a ph…
A multi-sensor multi-rate algorithm for motor rehabilitation with Augmented Reality devices
2016
Using Augmented Reality (AR) could offer stimuli to rehabilitation from neuro-motor disorders, since the patient can be aided in a better known reality than Virtual Reality (VR). The main goal for an AR system is to achieve a good quality of tracking the real object to align with virtual contents. Often a single sensor could not provide enough information to that end due to a low updating rate; therefore joining an other high updating rate sensor could be indispensable, but how to combine data from different sensors especially when they work all at different rates? In this paper an approach based on recursive parameter estimation, focusing on multi-rate tracking in AR devices is suggested. …
Speed and rotor flux estimation of induction motors via on-line adjusted extended kalman filter
2006
This paper deals with the estimation of speed and rotor flux of induction motors via Extended Kalman Filter (EKF) with on-line adjusting of the system noise covariance matrix. The predictor of EKF consists of a discrete time model obtained by means of a second order discretization of the original nonlinear model of the induction motor. In order to obtain accurate estimation of the above mentioned variables, the load torque is included in the state variables and then estimated. Three different system noise models are also illustrated and compared each other by simulations carried out in Matlab/Simulink environment. For one of these models, EKF is adjusted on-line by means of an additional PI…