In this paper, online multisensor data fusion algorithm using CORBA event channel is proposed, in order to deal with simplifying problem in sensor registration and fusion for vehicle’s state estimation. The networked based navigation concept for Autonomous Ground Vehicle (AGV) using several sensors is presented. A simulation of various application scenarios are considered by choosing several pa...

Abstruct-A knowledge-based approach and a reasoning system for multisensor data fusion (MSF) is presented. The scenario taken for the example is an air-land battlefield situation. A data fusion system obtains data from a variety of sensors. This is an essential step in a Command, Control, Communication and Intelligence (C31) system. Automatic processing of sensor data has become essential due t...

In this work the recently developed fuzzy logic-based adaptive Kalman filter (FL-AKF) is used to build adaptive centralized, decentralized, and federated Kalman filters for Adaptive MultiSensor Data Fusion (AMSDF). The adaptation carried out is in the sense of adaptively adjusting the measurement noise covariance matrix of each local FL-AKF to fit the actual statistics of the noise profiles pre...

Dealing with conflicting and target-specific requirements is an important issue in multi-sensor and multi-target tracking. This paper aims to allocate sensing resources among various targets in reaction to individual information requests. The approach proposed is to introduce agents for every relevant target responsible for its tracking. Such agents are expected to bargain with each other for a...

This paper proposes a new approach to multisensor data fusion, suggesting by considering information about the sensors’ different characteristics, aggregation of data acquired by individual sensors can be done more efficient. Same as the most effective sensors’ characteristics, especially in control systems, our focus is on sensors’ accuracy and frequency response. A rulebased fuzzy system is p...

Within the environmental sciences, the ability to accurately collate, combine and present data from various sensors is important to validate research. Whilst measuring data from a single sensor is a standard practice, fusing the output of more than one sensor can be a complicated and computationally intensive process. Outlined is a brief introduction to the art of multisensor fusion and a sugge...

This paper explains how multisensor data fusion and target identification can be performed within the transferable belief model, a model for the representation of quantified uncertainty based on belief functions. The paper is presented in two parts: methodology and application. In this part, we present the underlying theory, in particular the General Bayesian Theorem needed to transform likelih...

From the intelligent fault diagnosis system requirements, this article analyzes the relationship between the fault diagnosis and the multi-information fusion basing on the summing up the multi-sensor information fusion technology, and studies the hierarchical structure of multisensor information fusion system and the content of integration, and establishes an intelligent fault diagnosis model w...

In this paper we introduce a novel sensor fusion algorithm based on the cooperative coevolutionary paradigm. We develop a multisensor robust moving object detection system that can operate under a variety of illumination and environmental conditions. Our experiments indicate that this evolutionary paradigm is well suited as a sensor fusion model and can be extended to different sensing modalities.