A method is described to improve the performance of sensor fusion algorithms. Data sets available for training fusion algorithms are often smaller than desired, since the sensor suite used for data acquisition is always limited by the slowest, least reliable sensor. In addition, the fusion process expands the dimension of the data, which increases the requirement for training data. By using str...

This paper presents a sensor fusion strategy applied for Simultaneous Localization and Mapping (SLAM) in dynamic environments. The designed approach consists of two features: (i) the first one is a fusion module which synthesizes line segments obtained from laser rangefinder and line features extracted from monocular camera. This policy eliminates any pseudo segments that appear from any moment...

This paper focuses on the research on the state of the art for sensor fusion techniques, applied to the sensors embedded in mobile devices, as a means to help identify the mobile device user's daily activities. Sensor data fusion techniques are used to consolidate the data collected from several sensors, increasing the reliability of the algorithms for the identification of the different activi...

In this paper, proactive data filtering (PDF) algorithm is proposed for data aggregation (or data fusion) in wireless sensor networks. The objective of the algorithm is to further reduce the energy consumption when sensor nodes perform data aggregation. In many applications, the sensor field will be overwhelmed by unnecessary and redundant sensory information when the sink node disseminates a q...

Fraunhofer IITB has realized a testbed for sensors and services in order to trial the architecture and specifications developed in the EU Project SANY (Sensors Anywhere) based on going work of OGC (in particular the Sensor Web Enablement suite of standards). At the sensor network level, an ad hoc wireless network (ZigBee) is complemented by simulated sensor nodes. The nodes measure properties s...

One of the most important problems studied in any sensor network is data fusion. Client/server paradigm has been a commonly used computing model in traditional distributed sensor networks (DSNs). However, the deployment of wireless sensor networks (WSNs) and its ad hoc nature have brought new challenges to the fusion task. For example, the advances in sensor technology allow better, cheaper, an...

Intelligent Sensor-Actuator-Systems Laboratory (ISAS), Institute for Anthropomatics, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany †Dept. Sensor Data and Information Fusion, Fraunhofer FKIE, Wachtberg, Germany ‡Data Fusion Algorithms & Software, EADS Deutschland GmbH, Ulm, Germany [email protected], {michael.feldmann |wolfgang.koch}@fkie.fraunhofer.de [email protected],...

In this paper we study the problem of Bayesian sensor fusion for dynamic object tracking. The prospects of utilizing measurements from several sensors to infer about a system state are manyfold and they range from increased estimate accuracy to more reliable and robust estimates. Sensor measurements may be combined, or fused, at a variety of levels; from the raw data level to a state vector lev...

One of the main future tasks in the field of reconnaissance and surveillance is the data fusion of heterogeneous systems. For this purpose, sensor data of airborne and spaceborne systems, which acquire the data from the same scene with different spatial and spectral coverage, are used. The employment of different sensors offers the opportunity to take benefit of the specific sensor characterist...

Distributed multisensor detection problems with quantized observation data are investigated for cases of nonbinary hypotheses. The observations available at each sensor are quantized to produce a multiple-bit sensor decision which is sent to a fusion center. At the fusion center, the quantized data are combined to form a nal decision using a predetermined fusion rule. Firstly, the necessary con...