This paper presents a new multi-sensor data fusion method based on the combination of wavelet transform (WT) and extended Kalman filter (EKF). Input data are first filtered by a wavelet transform via Daubechies wavelet “db4” functions and the filtered data are then fused based on variance weights in terms of minimum mean square error. The fused data are finally treated by extended Kalman filter...

Distributed multi-sensor fusion has been widely used in military and civilian applications. In the statistical sensor fusion domain, the design of an optimal fusion processor usually requires the joint statistics of the local sensor outputs. When accurate joint statistical knowledge is not readily available, popular solutions are either to estimate the joint statistics from training data or to ...

Information from complementary and redundant sensors are often combined within sensor fusion algorithms to obtain a single accurate observation of the system at hand. However, measurements from each sensor are characterized by uncertainties. When multiple data are fused, it is often unclear how all these uncertainties interact and influence the overall performance of the sensor fusion algorithm...

This project work presents the sensor fusion of Global Positioning System (GPS), Inertial Measurement Unit (IMU) and Odometry data from wheel encoders which is used to estimate localization of mobile robot. GPS, IMU, Wheel encoders are interfaced with MBED. Filters are used to remove erroneous noise from the data obtained from sensors. Low pass IIR filter is used for Differential Global Positio...

Sensor technology has been used in water environment, which comes into being a water environment wireless sensor monitoring network. Monitoring data in the network slowly change, so we propose a geographical energy-efficient multi-hop clustering fusion routing algorithm based on multilayer perceptron (MLP-GEEMHCFR) in this paper to reduce transmittingdata and save the network energy.The algorit...

Basic probability assignment (BPA) has the key role in multi-sensor data fusion. This paper proposed a way to determine BPA using the various signals acquired from the sensors. It described the analysis of signals detected by the sensors. The determined BPA were used for multi-sensor data fusion to infer and recognize the context targeted by a wireless sensor networks. To determine BPA, the cha...

Magnetic and inertial measurement units are an emerging technology to obtain 3D orientation of body segments in human movement analysis. In this respect, sensor fusion is used to limit the drift errors resulting from the gyroscope data integration by exploiting accelerometer and magnetic aiding sensors. The present study aims at investigating the effectiveness of sensor fusion methods under dif...

Distributed multi-sensor fusion has been widely used in military and civilian applications. In the statistical sensor fusion domain, the design of an optimal fusion processor usually requires the joint statistics of the local sensor outputs. When accurate joint statistical knowledge is not readily available, popular solutions are either to estimate the joint statistics from training data or to ...

We review techniques for sensor fusion in robot navigation, emphasizing algorithms for self-location. These find use when the sensor suite of a mobile robot comprises several different sensors, some complementary and some redundant. Integrating the sensor readings, the robot seeks to accomplish tasks such as constructing a map of its environment, locating itself in that map, and recognizing obj...