KEYWORDS: Sensors, Detection and tracking algorithms, Weapons, Data fusion, Algorithm development, Telecommunications, Sensor networks, Information theory, Monte Carlo methods, Environmental sensing
In a dynamic battlespace the utility of decisions is a sensitive function of their timeliness. The allocation of weapons, and assignment of sensing and communications resources are examples where timely decisions are crucial to long-term survival. In this paper, we investigate the application of information-based decision-making theory to a data fusion network in such an environment. Specifically, we examine the advantages of decentralised information-based control for sensor-to-target assignment for identification as well as weapon allocation, and compare different utilities for optimising the combat strategy and therefore the life of the network.
In our application a positive identification is required before a weapon can be allocated to the target. The quality of sensor-to-target assignment is a key factor in determining whether incoming threats can be identified and destroyed before they can act. The two aspects of information-based control in our scenario are sensor-to-target assignment and weapon allocation. These can be treated as sequential decision-making processes, or more optimally as an integrated process. In the sequential approach, the decisions from the sensor-to-target assignment are simply propagated. The integrated approach assigns sensors to targets on the basis of the utility of the information that can be gained in the context of the weapon allocation decisions that must be made. This concept is also known as information value. Both approaches are considered here.
KEYWORDS: Telecommunications, Data fusion, Data communications, Sensors, Filtering (signal processing), Detection and tracking algorithms, Computer simulations, Algorithms, Linear filtering, Active sensors
Networked data fusion applications require adaptive strategies to
maximise their performance subject to fluctuating resource constraints. If the application is simply picture compilation (i.e., target tracking and identification) then Fisher/Shannon metrics provide a normative basis for approaching this problem. In this paper we demonstrate how information gain can be used to manage a constrained communication bandwidth in a decentralised tracking system that has to adapt to asymmetric communication bandwidth and data delays. When the sensor nodes are active participators in the information acquisition process, the relevance of information must also be considered. Specifically, what is the balance between the cost of information and the expected pay-off resulting from its application in a decision-making process? It is described how issues such as this fit into the formal framework of decentralised partially observed Markov decision process (DEC-POMDP) theory.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.