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This paper describes a methodology for incorporating human observations into a hard+soft information fusion process for counterinsurgency intelligence analysis. The goal of incorporating human observations into the information fusion process is important as it extends the ability of the fusion algorithms to associate and merge disparate pieces of information by allowing for information collected from...
This paper addresses the problem of automated multiagent search in an unknown environment. Autonomous agents equipped with sensors carry out a search operation in a search space, where the uncertainty, or lack of information about the environment, is known a priori as an uncertainty density distribution function. The agents are deployed in the search space to maximize single step search effectiveness...
Cooperative spectrum sensing for cognitive radio is recently being studied to minimize uncertainty in primary user detection. In order to improve the detection probability under a sustainable false alarm probability, a reliable scheme for cooperative spectrum sensing based on double threshold energy detection and Dempster-Shafer (D-S) theory is proposed in this paper. In the algorithm, the double...
Autonomous navigation in cross-country environments presents many new challenges including obstacle perception for Unmanned Ground Vehicle. This paper proposes new method that is suitable for distributing Basic Probability Assignment (BPA), based on which D-S theory of evidence is employed to integrate sensors information and recognize the obstacle. Firstly, select the experiment formula, then by...
To deal with sensor reliability in evidence modeling, the sensor credibility is evaluated by means of the statistical characters. Then an evidence model based on sensor credibility is established. When modeling, plausibility discount strategy is used to integrate the credibility into the evidence model. The total uncertainty of the evidence model decreases. The simulation example shows that the method...
Existing research on context and context awareness has broadly focused on the technical aspects of context acquisition and interpretation of users' surroundings, also called physical or sensor-based context. Such an approach is lack of reconciling the user's perception of real-world context and a context-aware system's interpretation of that context. Using Analytic Hierarchy Process (AHP), we propose...
A system structure for water jet cutting machine fault diagnosis based on multi-information fusion is presented, which takes the time-varying, redundancy and uncertainty of the multi-fault characteristic information into consideration. We make use of the neural network's ability of better fault tolerance, strong generalization capability, characteristics of self-organization, self-learning, and self-adaptation,...
The present work includes the development of a multi-agent game-theoretic model and closed-form risk-averse strategies of sense and avoid for responsive sensor resources management. The model is intended to provide appropriate scenarios for teaming and cooperation of multiple sensor agents, targeting applications in surveillance, exploration and cooperative manipulation. The essential contribution...
Due to providing ideal detection performance, cooperative spectrum sensing has been widely employed in cognitive radio networks. However, sensing results of the distributed second users have great uncertainty arising from channel conditions. In order to settle the problem, this paper proposes a selective cooperative spectrum sensing scheme based on improved Dempster-Shafer evidence theory. The scheme...
In many applications data values are inherently uncertain. This includes moving-objects, sensors and biological databases here has been recent interest in the development of database management systems that can handle uncertain data. Some proposals for such systems include attribute values that are uncertain. In particular, an attribute value can be modeled as a range of possible values, associated...
During the process of fusing multi-source information, a challenging problem is how to deal effectively with the available data and information that are vague, imprecise and uncertain. Vague sets are suitable for accurately describing the uncertain information. Dempster-Shafer (D-S) theory is a promising method for the combination of evidence obtained from different source. A new approach is proposed...
The goal of state estimation method is to compute an accurate estimation of the state of the system based on the measurement given by different sensors and a mathematical representation of the system. In this paper a new state estimation method based on Dampster-Shafer theory and interval analysis is presented. This method uses belief structures composed of a finite number of axis-aligned boxes with...
In this paper we discuss types of imprecision that are important for a tactical driver assistance system during its reasoning process. Methods for handling imprecision are presented using a previously developed overtake assistant as a showcase. The ideas for handling imprecision are demonstrated using several examples, together with the application of different approaches for different types of uncertainty...
In cognitive radio systems, unlicensed users can use the frequency bands when the licensed users are not present. Hence reliable detection of available spectrum is the foundation of cognitive radio technology. In order to efficiently detect the licensed users under prior knowledge constraints in the fusion center, a novel cooperative spectrum sensing algorithm based on Dempster-Shafer theory is proposed...
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