Cognitive EW Scheduling for Real-Time Agile Emitter Detection
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Solution Overview
Problem
Current electronic warfare (EW) systems rely on pre-mission data and predetermined scan schedules, which are inefficient in detecting agile and dynamic emitters, leading to missed detections and delayed response times in contested electromagnetic environments.
Innovation Solution
A cognitive scheduler and asset allocation system that dynamically allocates receiver assets in real-time based on detected electromagnetic signals without prior data, assigning priority levels to frequency bands and reallocating resources as threat levels change, enabling near-real-time reaction to agile threats.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If pre-mission data and predetermined scan schedules are used, then system complexity is reduced and ease of operation is improved, but detection reliability deteriorates and response time increases due to inability to detect agile emitters
Solution Approach 1:
The patent implements dynamic scan schedule generation that adapts to detected emitter behavior in real-time. The system transitions from static predetermined schedules to dynamic schedules that modify search parameters based on observed emitter patterns, frequency hopping, and dwell times, thereby maintaining detection reliability against agile threats while preserving operational simplicity through automated adaptation.
Solution Approach 2:
The system incorporates feedback loops where detection results from wideband receivers inform subsequent scan schedule adjustments. The cognitive processing unit analyzes detected signals and feeds this information back to modify search parameters, frequency bands, and receiver allocation dynamically, improving detection reliability without requiring complex manual intervention.
2Loss of time
If pre-mission data collection and predetermined scan schedules are employed, then operational preparation time is reduced, but response time to agile threats increases and detection precision deteriorates
Solution Approach 1:
The system performs preliminary actions by pre-configuring wideband receiver capabilities and cognitive processing algorithms that enable rapid adaptation. While the scan schedule itself is generated dynamically, the receivers are prepared in advance with broad frequency coverage and the cognitive unit is pre-programmed with emitter detection algorithms, allowing immediate responsive action without sacrificing precision.
Solution Approach 2:
The patent implements dynamic adjustment of scan parameters including frequency bands, dwell times, and receiver allocation based on real-time detection of emitter behavior. This dynamic approach enables the system to respond quickly to agile threats by adapting search patterns to match observed emitter characteristics, thereby reducing response time while maintaining or improving detection precision through targeted resource allocation.
3Productivity
If receiver assets are allocated according to predetermined schedules, then resource allocation simplicity is improved, but resource utilization efficiency deteriorates due to mismatch with actual threat locations
Solution Approach 1:
The patent implements dynamic receiver asset allocation where the cognitive processing unit continuously monitors detected emitters and reallocates receiver resources based on current threat locations and characteristics. This dynamic allocation optimizes resource utilization efficiency by directing receivers to areas of highest interest while adapting to changing threat patterns, without requiring complex manual resource management.
Solution Approach 2:
The system performs self-service through automated cognitive processing that independently analyzes detected signals and makes real-time decisions about receiver allocation. The cognitive unit autonomously determines which frequency bands and geographic areas require monitoring and automatically reconfigures receiver assignments, improving resource utilization efficiency while keeping device complexity manageable through rule-based automated decision-making.
Data Source
AI summary
A cognitive scheduler and asset allocation system to optimize electronic warfare (EW) resource allocation in reaction to RF signals observed in real-time without the need for prior collected data and without a predetermined scan schedule. The EW system of the present disclosure may further provide optimum resource allocation to minimize response time and to more effectively react to agile threat systems in an area of operations.