Distributed Phased-Array Signal Processing for Adaptive Jamming Response
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Solution Overview
Problem
Current adaptive signal processing techniques for phased array systems are limited by hardware architectures, data throughput, and processing timelines, making them ineffective against rapidly deployable and reconfigurable jamming threats.
Innovation Solution
Implementing distributed adaptive signal processing with unsupervised machine learning algorithms and distributed processing boards to parallelize operations, reducing data throughput and processing complexity while maintaining performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If centralized processing is used to maintain signal processing performance, then processing capability is improved, but data throughput requirements and processing complexity increase
Solution Approach 1:
The patent divides the phased array system into multiple sub-arrays, each processed by separate processing electronics. This segmentation allows distributed signal processing where each sub-array processes signals independently and combines results, reducing the data throughput burden on any single processing unit while maintaining overall processing capability.
Solution Approach 2:
The patent transitions from a single centralized processing dimension to a distributed multi-dimensional processing architecture. By distributing processing across multiple spatially separated processing units, the system reduces the data throughput requirements at any single point while maintaining aggregate processing performance through parallel operations.
2Ease of operation
If a single central processing system is used, then processing coordination is simplified, but size, weight, and power requirements increase
Solution Approach 1:
The central processing system is segmented into multiple distributed processing units located at different sub-arrays. Each unit handles a portion of the signal processing tasks, distributing the computational burden and reducing the size, weight, and power requirements of any single processing unit while maintaining coordinated operation through standardized interfaces.
Solution Approach 2:
The patent introduces standardized data interfaces and communication protocols as intermediaries between distributed processing units. These intermediaries enable coordinated operation without requiring a single large centralized system, allowing multiple smaller processing units to work together efficiently while reducing overall system SWaP.
3Device complexity
If traditional adaptive signal processing is used, then hardware architecture is simplified, but adaptability to rapidly changing threats is reduced
Solution Approach 1:
The patent implements dynamic adaptive signal processing where processing parameters and algorithms can be rapidly reconfigured in response to changing threat environments. The distributed architecture allows each processing unit to independently adapt to local conditions while coordinating with other units, providing both hardware simplicity and high adaptability through software-defined processing.
Solution Approach 2:
The system enables rapid parameter changes in signal processing algorithms and filtering characteristics without hardware modifications. The distributed processing architecture allows independent parameter adjustment at each processing unit based on real-time threat assessment, maintaining simple hardware while achieving high adaptability through dynamic parameter reconfiguration.
4Productivity
If distributed processing is implemented to reduce data throughput, then processing efficiency is improved, but system complexity increases
Solution Approach 1:
The patent segments the array into sub-arrays with dedicated processing electronics, creating a modular distributed architecture. This segmentation reduces data throughput requirements at each processing node by handling only local sub-array data, while the standardized modular interfaces keep the overall system complexity manageable through repetition of identical processing units.
Solution Approach 2:
The distributed processing units are designed to be homogeneous and interchangeable, each performing the same signal processing functions on their respective sub-arrays. This homogeneity simplifies the distributed architecture by allowing identical processing modules to be replicated and combined, reducing the complexity of coordination and integration compared to heterogeneous distributed systems.
Data Source
AI summary
A system may include a first sub-array of transceivers comprising a plurality of transmitters and receivers. A system may include a second sub-array of transceivers comprising a plurality of transmitters and receivers. A system may include a first processing electronics circuit configured to process one or more signals received by the first sub-array of transceivers. A system may include a second processing electronics circuit configured to process the signals received by the second sub-array of transceivers. A system may include a central processing system in communication with the first and second processing electronics modules.