In order to fuse data from a distributed sensor system, different fusion architectures can be chosen. In this work, distributed data fusion has been applied to data from a ground sensor network. Measurements have been made using five seismic and five acoustic sensor nodes, each consisting of three sensors, on vehicles of five different types. The data were analyzed off-line to achieve tracking ...

Sensor fusion is being increasingly viewed as an important perceptual activity in mobile robotics. While the potential beneets of sensor fusion have motivated much research , no general purpose method for accomplishing sensor fusion has emerged. This article reviews the literature from the biological and cognitive sciences in sensory integration and derives principles for use in constructing in...

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, it is demonstrate...

An existing facility for data acquisition in aerial surveys is presented. It contains a laser radar, an infrared camera and a video camera. The system supports synchronisation of sensor data, even when the sensor does not inherently offer that feature. This allows data from different sensors to be merged and processed together. The necessary temporal referencing is achieved by specialised hardw...

Embedded sensor networks (ESNs) are one of the prime candidates for widely used ubiquitous computing systems that will bridge the gap between computing and physical worlds. One of the most important generic ESN tasks is multi-modal sensor fusion, where data from sensors of different modalities are combined in order to obtain better information mapping of the physical world. One of the key prere...

Owing to continuous developments in technology and new requirements single sensor measurements are faced with constraints in their accuracy and thus in the applicability of their results. An innovative method of improving the geometric and radiometric data quality is the fusion of data obtained from different digital sensors. Sensor fusion means merging data obtained from different individual p...

In this paper we present a method for evaluating sensor fusion algorithms based on a quantitative comparison, which is independent of the data acquired and the sensors used. The sensor fusion performance measures and performance analysis procedure provide a basis for modeling, analyzing, experimenting, and comparing different sensor fusion algorithms. The capability to compare different algorit...

Fusion of information from multiple sources to achieve performances exceeding those of individual sources has been recognized in diverse areas [17] such as reliability, forecasting, pattern recognition, neural networks, decision fusion, and statistical estimation. In engineering systems, the fusion methods have proven to be particularly important since they can provide system capabilities with ...

In this paper, a multisensor data fusion system for object tracking is presented. It is able to track in real-time multiple targets in outdoor environments. The system can take advantage of the redundant information coming from different sensors monitoring the same scene. The measurements (positions of the targets) obtained from the available sources are fused together to obtain a more accurate...

Target classification fusion problem in a distributed, wireless sensor network is investigated. We propose a distance-based decision fusion scheme exploiting the relationship between sensor to target distance, signal to noise ratio and classification rate, which requires less communication while achieving higher region classification rate when compared to conventional majority-vote based fusion...