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Linear and nonlinear filtering for state estimation (e.g. position estimation or sensor fusion) for indoor positioning and navigation applications is a challenging task. Sensor fusion becomes more important with cost-effective sensors being readily available. However, state estimation with recursive Bayesian filters for sensor fusion and filtering are difficult to apply. We present an overview for...
This study focuses on a novel touchless interface for mobile devices by using infrared LED sensors. The reflected light from a set of proximity sensors are used to determine the position of the hand through the trilateration method. The position accuracy is easily affected by undesired object. In this paper, the problem can be overcome by using the Kalman filter; the Kalman filter to improve the infrared-based...
Estimating the location of sensor nodes in wireless sensor networks is a fundamental requirement in a variety of sensing applications. In large scale dense deployments where the area covered by sensor nodes is very large, it is impossible to localize all sensor nodes using single-hop localization techniques. A solution to this problem is to use a multi-hop localization technique to estimate sensor...
In this study, IMU (inertial measurement unit) using the principle of dead reckoning and instead of GPS (global positioning system), a digital compass and encoder signals were blended by using a Kalman filter. Firstly, a mathematical model was established. After that, the mathematical model was turned into software via MATLAB-Simulink. In order to mount the sensors, an unmanned land vehicle prototype...
Knowing the position of sensor nodes in an environmental monitoring is useful to identify the location of events. However deploying GPS receivers or other anchor sensors is expensive, since the role of anchor nodes ends after localizing sensor nodes' positions and they are transferred into ordinary sensor nodes. In this paper, we introduce a new localization scheme for a wireless sensor network that...
The localization of mobile robot is an important part of control problem. Pseudolite Ultrasonic System (PUS) is the method to find an absolute position by using ultrasonic sensor. PUS can be able to estimate the position of mobile robot precisely, in which errors are not accumulated. PUS insure a high accuracy on static state. But mobile robot moves as fast as an estimated position errors are increased...
For a microwave locating system virtual synchronisation of low-cost free-running transmitter clocks is proposed. The synchronisation strategy is based on modelling the transmitter clocks. A stable stochastic model was designed by analysing the correlation function of the observables in the locating system i.e. time of arrival and carrier phase. Exploiting this model in a Kalman filter, a reference...
In this article, we propose a method for improving the estimates of the absolute positions of cars. In the proposed method, each car measures its velocity, the absolute position, and the relative distance to a car in front, and uploads these measurements to a server. Using these measurements, the server computes the estimates of the cars' positions by means of the Kalman filter. This method can estimate...
Car navigation systems have three main tasks, namely 1) positioning; 2) routing; and 3) navigation (guidance). Positioning of the car is carried out by appropriately combining information from several sensors and information sources, including odometers, gyroscopes, Global Positioning System (GPS) information, and digital maps. This paper describes two sensor-fusion steps implemented in commercial...
A positioning algorithm for navigation signals based on improved Kalman Filter is proposed in this paper. The receiver estimates the position and velocity via measuring the pseudo ranges and their speeds. By using Kalman filter to estimate the errors of parameters in stead of the parameters themselves, the operation errors are reduced and the positioning accuracy is improved efficiently. During the...
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