Phased-Array Radar Self-Healing for Online Failure Reconfiguration
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Solution Overview
Problem
Current self-healing array systems require downtime for diagnosis and reconfiguration, leading to subpar performance and the need for expensive hardware, while lacking the ability to self-heal online.
Innovation Solution
A system and method for in-flight self-diagnosis and self-healing of phased-array radars that integrates diagnostics, failure classification, auto-correction, and multiple stages of reconfiguration to compensate for T/R module degradation and failures, allowing the array to operate in a degraded mode with minimal downtime and hardware additions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the array is taken offline for diagnosis and reconfiguration, then the array can be properly diagnosed and reconfigured to compensate for failures, but the array experiences downtime and reduced productivity
Solution Approach 1:
The system performs preliminary diagnostics and identifies failing elements before they completely fail. By detecting degradation trends and predicting failures in advance, the system can proactively reconfigure the array to compensate for upcoming failures, maintaining performance without requiring emergency downtime for repairs
Solution Approach 2:
The array system performs self-diagnosis and self-reconfiguration automatically without requiring external intervention or taking the system offline. The control system continuously monitors element health, detects failures, and autonomously adjusts weighting and beamforming parameters to compensate for degraded or failed elements, maintaining continuous operation
2Reliability
If expensive hardware is added to enable self-healing, then the array can compensate for failures, but the system complexity and cost increase
Solution Approach 1:
Instead of adding redundant physical hardware elements, the system creates virtual copies of failed elements through signal processing. By using weighting adjustments and beamforming techniques on remaining functional elements, the system synthesizes the missing element's function, achieving self-healing without physical hardware additions
Solution Approach 2:
The system compensates for element failures by dynamically changing operational parameters such as weighting factors, phase shifts, and amplitude adjustments. These parameter modifications allow the array to adapt to failures using existing hardware, avoiding the need for complex hardware modifications while maintaining self-healing capability
Data Source
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AI summary
Failure in a self-healing array may be handled by: detecting a failing element of the self-healing array by monitoring characteristics of the failing element (52); auto-correcting a failing element of the self-healing array by adjusting characteristics of the failing element to compensate for a portion of the failing element which is failing (62); or correcting performance of the self-healing array when one or more elements of the self-healing array fail by detecting and modeling an impact of the one or more elements of the self-healing array which failed on the performance of the self-healing array (72).