Fusion Techniques for Reliable Information: A Survey <s> Joint Directors of Laboratories (JDL) model <s> Abstract This paper uses a modeling and simulation approach in the engineering process of designing a data fusion system for military applications. Fundamental issues in the design of a data fusion system are the selection of appropriate architecture and efficient and dedicated real-time algorithms for the application of interest. Selection of data fusion algorithms is performed using a simulation test bed where realistic modeling of sensor performance is being performed. The test bed also allows the use of multiple algorithms in a dynamic sense based on the particular regime in which the fusion system is operating. This paper first presents the data fusion system engineering guidelines that are being used. Then the paper addresses the complex problem of the tactical picture compilation. Finally the paper shows a case study where the selection of data fusion algorithms is performed for an airborne platform. <s> BIB001 </s> Fusion Techniques for Reliable Information: A Survey <s> Joint Directors of Laboratories (JDL) model <s> Context simplifies and enriches human-human interaction. However, enhancing human-computer interaction through the use of context remains a difficult task. Applications in pervasive and mobile environments need to be context-aware so that they can adapt themselves to rapidly changing situations. One of the problems is that there is no common, reusable model for context used by these environments. In this paper, we propose a model of context that is based on first order predicate calculus. The first order model allows complex rules involving contexts to be written. It also enables automated inductive and deductive reasoning to be done on contextual information. The first order model allows an expressive description of context using Boolean operators and existential and universal quantifiers. Based on this model, an infrastructure to enable context-awareness in ubiquitous computing environments has been developed. The infrastructure allows the easy development and deployment of various sensors and context-aware applications. It also allows distributed reasoning to take place. This context infrastructure is part of our smart spaces framework for ubiquitous computing, Gaia. <s> BIB002 </s> Fusion Techniques for Reliable Information: A Survey <s> Joint Directors of Laboratories (JDL) model <s> Abstract : This paper suggests refinements and extensions of the JDL Data Fusion Model, the standard process model used for a multiplicity of community purposes. However, this Model has not been reviewed in accordance with (a) the dynamics of world events and (b) the changes, discoveries, and new methods in both the data fusion research and development community and related IT technologies. This paper suggests ways to revise and extend this important model. Proposals are made regarding (a) improvements in the understanding of internal processing within a fusion node and (b) extending the model to include (1) remarks on issues related to quality control, reliability, and consistency in DF processing, (2) assertions about the need for co-processing of abductive/ inductive and deductive inferencing processes, (3) remarks about the need for and exploitation of an onto logically-based approach to DF process design, and (4) extensions to account for the case of Distributed Data Fusion (DDF). <s> BIB003 </s> Fusion Techniques for Reliable Information: A Survey <s> Joint Directors of Laboratories (JDL) model <s> Engine diagnostics is a typical multi-sensor fusion problem. It involves the use of multi-sensor information such as vibration, sound, pressure and temperature, to detect and identify engine faults. From the viewpoint of evidence theory, information obtained from each sensor can be considered as a piece of evidence, and as such, multi-sensor based engine diagnosis can be viewed as a problem of evidence fusion. In this paper we investigate the use of Dempster-Shafer evidence theory as a tool for modeling and fusing multi-sensory pieces of evidence pertinent to engine quality. We present a preliminary review of Evidence Theory and explain how the multi-sensor engine diagnosis problem can be framed in the context of this theory, in terms of faults frame of discernment, mass functions and the rule for combining pieces of evidence. We introduce two new methods for enhancing the effectiveness of mass functions in modeling and combining pieces of evidence. Furthermore, we propose a rule for making rational decisions with respect to engine quality, and present a criterion to evaluate the performance of the proposed information fusion system. Finally, we report a case study to demonstrate the efficacy of this system in dealing with imprecise information cues and conflicts that may arise among the sensors. <s> BIB004
JDL model is one of famous models  in fusion system. The purpose of this model is unifying research terminology to promote technology and co-operation among six levels processing: the source processing (0), the object refinement BIB002 , the situation refinement  , the threat refinement (3), the resource management (4), and the cognitive refinement BIB004 . The goal of the model is to serve as a functional model by diverse elements of the data fusion community. Hence, this model should clarify the elements of the problems and the solutions to facilitate the recognition of commonalities BIB001 . The extensions of JDL model refine any generalized data fusion model description by adapting important issues BIB003 . This model is used for target tracking or location tracking. The level 0, 1, and 2 are adapted to process data among objects and users in pervasive computing areas.