Stochastic Mission Planning System for Combat Survivability
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Solution Overview
Problem
Current systems lack an effective method to optimize mission survivability and attack effectiveness for vehicles engaging targets in dynamic combat scenarios, as they rely heavily on human intervention or simplistic sensor data, failing to provide a statistical advantage in complex situational conditions.
Innovation Solution
A system utilizing stochastic simulation to determine optimal courses of action by identifying condition data, selecting relevant parameters, and implementing behavioral logic to suggest statistically best paths for engagement or avoidance, incorporating lethality ranges and standoff ratios to enhance mission objectives.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If human intervention or simplistic sensor data is used for decision-making, then the system is easier to operate and understand, but mission survivability and attack effectiveness are not optimized
Solution Approach 1:
The system performs stochastic simulations offline before the actual mission to pre-calculate optimal courses of action for various situational conditions. These pre-computed results are stored and retrieved during the mission, eliminating the need for complex real-time calculations while maintaining high reliability in decision-making.
Solution Approach 2:
The patent introduces an intermediary layer between simple sensor data and complex decision-making. The stochastic simulation results serve as a mediator that translates raw sensor data into optimized course of action recommendations, bridging the gap between simple input data and complex optimal decisions without requiring the vehicle to directly process complex algorithms in real-time.
2Reliability
If complex stochastic simulation is used to determine optimal courses of action, then attack effectiveness and survivability are maximized, but the computational complexity and processing requirements increase
Solution Approach 1:
The stochastic simulations are performed offline in advance to generate lookup tables of optimal courses of action for various situational parameters. During the actual mission, the system only needs to query these pre-computed tables based on current sensor data, reducing real-time computational power requirements while maintaining the benefits of complex simulation-based optimization.
3Reliability
If real-time stochastic simulation is performed for each decision, then the most optimal course of action is determined, but the response time and decision-making speed are reduced
Solution Approach 1:
The system pre-computes optimal courses of action through stochastic simulations for a comprehensive set of possible situational conditions before the mission. These results are stored in lookup tables that can be quickly queried during the mission. This approach eliminates the need for time-consuming real-time simulations while maintaining high decision quality by selecting from pre-optimized options that match current situational conditions.
4Measurement precision
If more sensor data and parameters are collected and analyzed, then the accuracy of course of action determination is improved, but the data processing load and system complexity increase
Solution Approach 1:
The system performs comprehensive data analysis and stochastic simulations offline before the mission, processing all sensor data and parameters in advance to build lookup tables. During the mission, the vehicle only needs to collect current sensor data and query the pre-processed lookup tables, significantly reducing real-time data processing complexity while maintaining high situational awareness accuracy.
Data Source
AI summary
A system for suggesting a course of action for a vehicle engaged in a situation includes a portion for identifying condition data that corresponds to conditions sensed from the situation. The system also includes a portion for selecting parameters associated with the condition data. The system further includes a portion for determining a suggested course of action based on the selected parameters.