A neural approach to a sensor fusion problem
نویسندگان
چکیده
Our problem concerns the joint interpretation of UltraSonic and InfraRed measurements provided by a composite proximity sensor, in order to extract geometrical and morphological features of a at target. Neural networks are applied here both for modeling and for classi cation purposes. Physical knowledge of the sensing modalities helps in simplifying the network structure, in order to minimize its complexity, save computing time and make the system suitable for real{time applications.
منابع مشابه
Detecting Surface Waters Using Data Fusion of Optical and Radar Remote Sensing Sensor
Identification and monitoring of surface water using remote sensing have become very important in recent decades due to its importance in human needs and political decisions. Therefore, surface water has been studied using remote sensing systems and Sentinel-1 and Sentinel-2 sensors in this study. In this paper, two data fusion approaches and decision fusion improve the accuracy of surface wate...
متن کاملA New Approach to Self-Localization for Mobile Robots Using Sensor Data Fusion
This paper proposes a new approach for calibration of dead reckoning process. Using the well-known UMBmark (University of Michigan Benchmark) is not sufficient for a desirable calibration of dead reckoning. Besides, existing calibration methods usually require explicit measurement of actual motion of the robot. Some recent methods use the smart encoder trailer or long range finder sensors such ...
متن کاملUncertainty Measurement for Ultrasonic Sensor Fusion Using Generalized Aggregated Uncertainty Measure 1
In this paper, target differentiation based on pattern of data which are obtained by a set of two ultrasonic sensors is considered. A neural network based target classifier is applied to these data to categorize the data of each sensor. Then the results are fused together by Dempster–Shafer theory (DST) and Dezert–Smarandache theory (DSmT) to make final decision. The Generalized Aggregated Unce...
متن کاملDesigning a Home Security System using Sensor Data Fusion with DST and DSMT Methods
Today due to the importance and necessity of implementing security systems in homes and other buildings, systems with higher certainty, lower cost and with sensor fusion methods are more attractive, as an applicable and high performance methods for the researchers. In this paper, the application of Dempster-Shafer evidential theory and also the newer, more general one Dezert-Smarandache theory ...
متن کاملFlood Forecasting Using Artificial Neural Networks: an Application of Multi-Model Data Fusion technique
Floods are among the natural disasters that cause human hardship and economic loss. Establishing a viable flood forecasting and warning system for communities at risk can mitigate these adverse effects. However, establishing an accurate flood forecasting system is still challenging due to the lack of knowledge about the effective variables in forecasting. The present study has indicated that th...
متن کاملModel-based Approach for Multi-sensor Fault Identification in Power Plant Gas Turbines
In this paper, the multi-sensor fault diagnosis in the exhaust temperature sensors of a V94.2 heavy duty gas turbine is presented. A Laguerre network-based fuzzy modeling approach is presented to predict the output temperature of the gas turbine for sensor fault diagnosis. Due to the nonlinear dynamics of the gas turbine, in these models the Laguerre filter parts are related to the linear d...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 1998