Search results for "kalman filtering"

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…

ARIANNA: a smartphone-based navigation system with human in the loop

2014

In this paper we present a low cost navigation system, called ARIANNA, primarily designed for visually impaired people. ARIANNA (pAth Recognition for Indoor Assisted NavigatioN with Augmented perception) permits to find some points of interests in an indoor environment by following a path painted or sticked on the floor. The path is detected by the camera of the smartphone which also generates a vibration signal providing a feedback to the user for correcting his/her direction. Some special landmarks can be deployed along the path for coding additional information detectable by the camera. In order to study the practical feasibility of the ARIANNA system for human users that want to follow …

Improved GNSS positioning exploiting a vehicular P2P infrastructure

2010

This paper considers the possibility to exploit external altitude measurements to improve the performance of a Kalman based GNSS receiver. The altitude measurements are provided by means of a peer to peer network, that is supposed to be based on the evolution of the 802.11 standard for the vehicular environment, namely the WAVE (802.11p). The performance of such a system are investigated for different characteristics of the aiding measurement and for a different number and disposals of the aiding peers. 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…

An Indoor and Outdoor Navigation System for Visually Impaired People

2019

In this paper, we present a system that allows visually impaired people to autonomously navigate in an unknown indoor and outdoor environment. The system, explicitly designed for low vision people, can be generalized to other users in an easy way. We assume that special landmarks are posed for helping the users in the localization of pre-defined paths. Our novel approach exploits the use of both the inertial sensors and the camera integrated into the smartphone as sensors. Such a navigation system can also provide direction estimates to the tracking system to the users. The success of out approach is proved both through experimental tests performed in controlled indoor environments and in r…

Extended complex Kalman filter for sensorless control of an induction motor

2014

Abstract This paper deals with the design of an extended complex Kalman filter (ECKF) for estimating the state of an induction motor (IM) model, and for sensorless control of systems employing this type of motor as an actuator. A complex-valued model is adopted that simultaneously allows a simpler observability analysis of the system and a more effective state estimation. The observability analysis of this model is first performed by assuming that a third order ECKF has to be designed, by neglecting the mechanical equation of the IM model, which is a valid hypothesis when the motor is operated at constant rotor speed. It is shown that this analysis is more effective and easier than the one …

Is it possible to define a fully digital state model for Kalman filtering?

2010

Advanced Motion Control in Induction Motor Systems - Modelling, Analysis and Control

Using a unified notation, this thesis collects and discusses the most important steps and issues in the design of estimation and control algorithms for induction motors. It contains many estimation and control algorithms. Their stability is analyzed and their performance is illustrated by simulations and experiments on the same induction motor. An intense and challenging collective research effort is carefully documented and analyzed, with the aim of providing and clarifying the basic intuition and tools required in the analysis and design of nonlinear feedback control algorithms. This material should be of specific interest to engineers who are engaged in the design of control algorithms f…

Optimization of Delayed-State Kalman-Filter-based Algorithm via Differential Evolution for Sensorless Control of Induction Motors

2010

This paper proposes the employment of the differential evolution (DE) to offline optimize the covariance matrices of a new reduced delayed-state Kalman-filter (DSKF)-based algorithm which estimates the stator-flux linkage components, in the stationary reference frame, to realize sensorless control of induction motors (IMs). The DSKF-based algorithm uses the derivatives of the stator-flux components as mathematical model and the stator-voltage equations as observation model so that only a vector of four variables has to be offline optimized. Numerical results, carried out using a low-speed training test, show that the proposed DE-based approach is very promising and clearly outperforms a cla…

Advanced technologies for detecting tremor in Parkinson's disease.

2019

Objective Accurate and reliable detection of tremor onset in Parkinson’s disease (PD) is critical to the success of adaptive deep brain stimulation (aDBS) therapy. Here, we investigated the potential use of feature engineering and machine learning methods for more accurate detection of rest tremor in PD. Methods We analyzed the local field potential (LFP) recordings from the subthalamic nucleus region in 12 patients with PD (16 recordings). To explore the optimal biomarkers and the best performing classifier, the performance of state-of-the-art machine learning (ML) algorithms and various features of the subthalamic LFPs were compared. We further used a Kalman filtering technique in feature…