A Distributed Network Enabled Weapon-Target Assignment for Combat Formations

Léchevin, N.; Rabbath, C.A.; Lauzon, M.

doi:10.1007/978-3-540-88063-9_3

Cited by 4 publications

(9 citation statements)

References 17 publications

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“…To limit the processing time in solving the optimization problem, constraints on energy expenditure are taken into account. A detailed presentation of the high-level DM is available in reference [1], where it is shown that a parallel version of the cross-entropy method can solve moderately complex multirouting-type, multiformation-target assignment problems with relatively short processing times. To compute new lists of targets whenever the evolution of the operation theatre is deemed significant enough, the algorithm is distributed among the formations, which share information through a communication network [2].…”

Section: Hierarchical Decision Makingmentioning

confidence: 99%

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A hierarchical decision and information system for multi-aircraft combat missions

Léchevin

Rabbath

2010

Proceedings of the Institution of Mechanical Engineers, Part G:

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Designing decision, control and information systems is motivated, in part, by the need to support the deployment of multiple aircraft, such as combat vehicles, unmanned combat air vehicles, unmanned aerial vehicles, and weapons, in missions taking place in a dynamic, although uncertain, environment. Such systems aim at ensuring mission success without overloading the operating crew, the pilots, and the commanders. One of the main design challenges lies in obtaining some sort of coherent behaviour of the fleet, by means of solutions to potentially NPhard problems, given incomplete and imperfect information, and despite limited computational and communication capabilities. In this context, this article proposes a hierarchical decision and information system aiming at providing, in real-time, coordinated aircraft path planning and deceptive engagement assignments. The blue-red engagement policy is obtained by minimizing, and balancing, the energy expenditure among the vehicles while constraining information exchanges to a minimum defined by a risk of inconsistency. The proposed system relies on dynamic programming, online heuristic techniques and stochastic, consistency-checking methods. Numerical simulations show that the proposed approach compares advantageously to a random process and to a law that seeks to minimize the cost of the confrontation at a given time regardless of past moves. However, there is a trade-off between increasing the level of deception and the level of energy consumption.Results from stochastic approximation algorithms are used in the sequel [16]. As previously discussed, J o depends onÛ j,o , which is a known matrix, whereas recursions J 1,o andJ 1,o depend on the nominal matrix U * f ,o , where f ∈ {i, j, k} indicates the vehicle that will become the leader for the next 3 × 3 engagement, i.e.

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Section: Hierarchical Decision Makingmentioning

confidence: 99%

“…Notation d 1 and d 1/2 2 , for a quantization level n q and for units that are located in such a way that utility matrices U r are uniformly distributed in L u is given by…”

Section: Two-vehicle Group Versus N Armed Ground Unitsmentioning

confidence: 99%

A hierarchical decision and information system for multi-aircraft combat missions

Léchevin

Rabbath

2010

Proceedings of the Institution of Mechanical Engineers, Part G:

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“…Decision making is the solution to a combinatorial optimization problem. We proposed in [1] a parallelized Cross-Entropy-Based Algorithm (CEMBA) to provide the UCVs with fast, near-optimal decision making. It consists of the parallelization of the cross-entropy method applied to a vehicle multirouting problem.…”

Section: Application To Newtasmentioning

confidence: 99%

“…Motivated by the desire to implement distributed cooperative optimization schemes in realistic operating conditions, an agreement-reaching algorithm is proposed to ensure consistency of the state variables exchanged among agents despite limited communications bandwidth. Distributed cooperative optimization may be needed for weapon-target assignment strategies and multiagent path planning [1]. Typically, such strategies require that each agent solves a local optimization problem using information obtained from neighboring agents.…”

Section: Introductionmentioning

confidence: 99%

Information broadcasting algorithm for Finite-Time Reaching-at-Risk Consensus with application to weapon-target assignment

Léchevin

Rabbath

Zhang

2009

2009 American Control Conference

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We propose a randomized algorithm aimed at reaching, in finite time, exact consensus among a set of agents that are linked though a connected, possibly time-varying, graph. The information exchanged among neighboring agents is limited in size, by randomly selecting the content from an agent internal state. The time needed to reach the agreement is a random variable, whose empirical cumulative distribution function is utilized to determine a stopping rule that ensures consensus is achieved with a prescribed confidence level. Simulation results show that the consensus-reaching time obtained with a prescribed confidence level compares relatively well to local-averaging-based algorithms. The algorithm is shown to be robust, to some extent, to lossy communications and is demonstrated on a weapon-target assignment problem.

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“…In [16], WA in the context of network-centric warfare was regarded as a dynamic human decision-making resource (e.g., sensors and weapons) during the conduct of command and control activities. In [25], the weapon-target assignment problem was formulated in such a way that a group of weapons, or unmanned combat vehicles, were able to form groups of varying dimensions with the objective of maximizing a global utility function. In [17], a game-theoretic combat model was proposed, in which networked elements perform autonomous operations while cooperating to counter the enemy's attack.…”

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confidence: 99%

An Approach for Weapon System-of-Systems Scheme Generation Based on a Supernetwork Granular Analysis

Zhao

Dou

et al. 2017

IEEE Systems Journal

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A weapon system of systems (WSoS) is a collection of interdependent systems providing multiple interdependent capabilities to support multiple tasks. In this paper, we propose a WSoS scheme generation method based on a granular analysis of a WSoS supernetwork. More precisely, we establish a WSoS supernetwork model based on a "network-centered" combat mode. Next, based on the theory of quotient space, a granular analysis is presented to reduce the complexity of the WSoS scheme generation. Then, the WSoS supernetwork is converted into a directed weighted network with multiple granularities, and an algorithm for the WSoS scheme generation based on the directed weighted network is presented. Consequently, each WSoS scheme corresponds to a path in the directed weighted network, and the capability of supporting the realization of a task by a WSoS can be analyzed based on the schemes. Finally, the feasibility of the proposed approach is demonstrated using an illustrative example.

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A Distributed Network Enabled Weapon-Target Assignment for Combat Formations

Cited by 4 publications

References 17 publications

A hierarchical decision and information system for multi-aircraft combat missions

A hierarchical decision and information system for multi-aircraft combat missions

Information broadcasting algorithm for Finite-Time Reaching-at-Risk Consensus with application to weapon-target assignment

An Approach for Weapon System-of-Systems Scheme Generation Based on a Supernetwork Granular Analysis

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