Air Defense Engagement Plan Allocation via Auction Algorithm
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Solution Overview
Problem
Existing air defense systems face challenges in determining an optimal commitment plan for allocating missiles to air threats during saturating attacks, due to constraints such as limited ammunition and specific shooting windows, while also managing conflicts between missile allocations.
Innovation Solution
A process and system that utilize an auction algorithm to determine a commitment plan by calculating classic and adapted benefits for each missile-target couple, taking into account primary and secondary constraints, and resolving conflicts through the auction process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional allocation methods are used to assign missiles to targets, then the system can handle simple scenarios, but it cannot effectively manage saturating attacks with multiple constraints and conflicts
Solution Approach 1:
The patent segments the missile allocation problem into distinct components: missiles, targets, launchers, and availability windows. Each component is independently modeled with specific attributes and constraints, allowing the complex allocation problem to be broken down into manageable sub-problems that can be processed systematically by the auction algorithm.
Solution Approach 2:
The patent transforms the allocation problem by introducing numerical parameters including classic benefits, adapted benefits, and conflict coefficients. These parameter changes convert qualitative allocation decisions into quantitative optimization problems, enabling rapid computational processing while handling multiple constraints simultaneously.
2Ease of operation
If the system allocates missiles without considering launcher constraints, then allocation is simpler, but the engagement plan becomes infeasible
Solution Approach 1:
The patent applies preliminary action by pre-defining launcher constraints including missile availability, firing preparation times, and availability windows before the allocation process begins. These constraints are encoded into the system model in advance, allowing the auction algorithm to automatically respect them during allocation without requiring complex real-time checks.
Solution Approach 2:
The patent implements feedback mechanisms through the auction algorithm where missiles provide bids to targets based on adapted benefits, and conflicts between allocations generate feedback signals that adjust the allocation decisions. This iterative feedback process ensures feasibility constraints are satisfied while maintaining allocation effectiveness.
3Device complexity
If the system uses classic benefit only for allocation, then calculation is simpler, but conflicts between missile allocations are not resolved
Solution Approach 1:
The patent adds another dimension to the allocation problem by introducing the time dimension through availability windows and firing dates. This transforms a static allocation problem into a dynamic one where missiles are allocated not only to targets but also to specific time slots, enabling the system to resolve conflicts by scheduling allocations across different time dimensions.
Solution Approach 2:
The patent creates a composite evaluation metric called adapted benefit that combines classic benefit with conflict coefficients. This composite parameter integrates multiple factors including target value, missile effectiveness, launcher constraints, and allocation conflicts into a single optimization criterion, allowing comprehensive allocation decisions without separate conflict resolution steps.
4Loss of time
If the system processes allocation in real-time during saturating attacks, then response time is reduced, but computational accuracy may decrease
Solution Approach 1:
The patent implements dynamics by making the allocation system adaptive and iterative. The auction algorithm allows missiles to dynamically bid on targets and conflicts to be dynamically resolved through repeated adjustments. This dynamic process continues until convergence, ensuring optimal allocation even under time-critical saturating attack conditions.
Solution Approach 2:
The patent uses parameter changes to balance speed and accuracy by adjusting the precision of benefit calculations and conflict coefficient computations during the auction process. The algorithm can terminate when sufficient accuracy is achieved, allowing flexible control over the trade-off between computational time and allocation optimality based on the severity of the threat situation.
Data Source
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AI summary
- Method and device for determining an engagement plan for an air defense system. - The device determines, using a processing unit, an engagement plan for an air defense system (2) comprising munitions (Mj) fired from launchers (4), the processing unit determining the engagement plan by implementing an auction algorithm taking into account, on the one hand, the number of munitions (Mj) from the launcher (4) representing a first constraint concerning the munitions (Mj) from the launcher (4), and on the other hand, a number of firing dates in availability windows representing a second constraint concerning the firing dates, the engagement plan comprising, for each target (Ci), the allocation of, on the one hand, a particular munition (Mj) from a particular launcher (4) and, on the other hand, a firing date for this munition (Mj), this allocation satisfying the said first and second constraints.