Journal Article10.1177/027836498800700608
Sensor models and multisensor integration
335
TL;DR: The importance of having a model of sensor performance is that capabilities can be estimated a priori and, thus, sensor strategies developed in line with information requirements can be developed as mentioned in this paper.
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Abstract: We maintain that the key to intelligent fusion of disparate sensory information is to provide an effective model of sensor capabilities. A sensor model is an abstraction of the actual sensing process. It describes the information a sensor is able to provide, how this information is limited by the environment, how it can be enhanced by information obtained from other sensors, and how it may be improved by active use of the physical sensing device. The importance of having a model of sensor performance is that capabilities can be estimated a priori and, thus, sensor strategies developed in line with information requirements.
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Citations
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References
The Bargaining Problem
TL;DR: In this paper, a new treatment is presented of a classical economic problem, one which occurs in many forms, as bargaining, bilateral monopoly, etc It may also be regarded as a nonzero-sum two-person game in which a few general assumptions are made concerning the behavior of a single individual and of a group of two individuals in certain economic environments.
•Book
Applied Optimal Estimation
Arthur Gelb
- 01 Jan 1974
TL;DR: This is the first book on the optimal estimation that places its major emphasis on practical applications, treating the subject more from an engineering than a mathematical orientation, and the theory and practice of optimal estimation is presented.
6.9K
Team decision theory and information structures in optimal control problems--Part II
Yu-Chi Ho,K'ai-ching Chu +1 more
TL;DR: Equivalence relations in information and in control functions among different systems are developed and aid in the solving of many general problems by relating their solutions to those of the systems with "perfect memory".
718
Team decision theory and information structures
Yu-Chi Ho
- 01 Jun 1980
TL;DR: This tutorial-survey paper introduces the problems of decentralized statistical decision making (team theory) where the decision makers have access to different information concerning the underlying uncertainties.
451