Adaptive Filter Deterministic Gradient Descent Signal Classification
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Solution Overview
Problem
Existing EW receivers face challenges in quickly and effectively classifying uncooperative or unknown signals in real-time operations due to the low signal-to-noise ratio and the need for vast computation iterations with stochastic optimization methods.
Innovation Solution
An adaptive filter system utilizing a deterministic gradient descent optimization logic and interpolation logic, which includes a first processing loop for initial parameter extraction and a second processing loop for refining match filter parameters to achieve efficient signal classification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If stochastic optimization methods are used for signal classification, then computation speed is improved, but classification accuracy deteriorates due to requiring vast computation iterations
Solution Approach 1:
The patent segments the optimization process into two distinct loops: a first processing loop for initial parameter extraction and coarse classification, and a second processing loop for refined parameter optimization. This segmentation allows the system to achieve quick initial results while maintaining the option for higher precision when needed, resolving the contradiction between speed and accuracy.
Solution Approach 2:
The patent implements dynamic switching between different optimization approaches based on operational requirements. The system can operate in the faster stochastic optimization mode when speed is prioritized, and switch to the more accurate deterministic gradient descent mode when classification precision is critical, allowing adaptive adjustment of the speed-accuracy tradeoff.
2Measurement precision
If vast computation iterations are performed to improve classification accuracy, then measurement precision is improved, but productivity deteriorates due to time consumption
Solution Approach 1:
The first processing loop performs preliminary parameter extraction and initial classification before the second loop refines the results. This preliminary action provides a head start on the classification process, reducing the number of iterations needed in the second loop to achieve high accuracy, thereby maintaining real-time processing capability.
Solution Approach 2:
The system performs partial optimization by focusing the second processing loop only on refining specific match filter parameters that most impact classification accuracy, rather than re-optimizing all parameters. This partial action achieves high precision with fewer iterations, preserving productivity.
3Measurement precision
If deterministic gradient descent optimization is used instead of stochastic optimization, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent applies deterministic gradient descent optimization locally and selectively to specific match filter parameters in the second processing loop, rather than applying complex optimization to all parameters throughout the entire system. This localized application maintains measurement precision for critical parameters while limiting the increase in overall device complexity.
Data Source
AI summary
An adaptive filter protocol stored on a non-transitory computer readable medium that is operatively in communication with a processor of a platform. The adaptive filter protocol includes a first processing loop that is operatively in communication with at least one receiving device of the platform for receiving at least one input signal. The adaptive filter protocol also includes a second processing loop that is operatively in communication with the first processing loop and has a deterministic gradient descent optimization logic and an interpolation logic. When the at least one receiving device receives the at least one input signal, the adaptive filter protocol enables the processor to generate a refined match filter parameters that substantially correlates with the initial parameters of the at least one input signal upon completing a plurality of refining cycles of the second processing loop.