Joint Angle-Frequency Determination via SOCP
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Solution Overview
Problem
Current signal processing techniques for electro-magnetic signals, such as those in ELINT and radar systems, face challenges in achieving significant power savings while maintaining performance, especially when detecting and locating signals across wide bandwidths from sparse sources, as they often require complex and power-hungry sparse optimization methods.
Innovation Solution
Implementing sparsity-based signal processing using Second Order Cone Program (SOCP) for joint determination of angle and frequency in a signal environment that is jointly sparse in the angle-frequency domain, leveraging compressive sensing and phase functional mapping to reduce the number of computations and power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If compressive sensing is used to reduce bandwidth, then data acquisition and processing requirements are reduced, but processing complexity and power consumption increase
Solution Approach 1:
The patent changes the optimization parameter from general sparse optimization to convex optimization (Second Order Cone Program), which fundamentally alters the computational complexity characteristics. This parameter change enables efficient solution with reduced power consumption while maintaining the benefits of compressive sensing for reducing data volume.
2Ease of operation
If two-step techniques (angle location followed by wideband processing) are used, then processing can be divided into manageable steps, but computational time and energy consumption increase
Solution Approach 1:
The patent merges angle determination and frequency analysis into a single simultaneous convex optimization problem. This consolidation eliminates the sequential two-step process, reducing total processing time and energy consumption while maintaining operational clarity through the unified mathematical formulation.
3Productivity
If increasing computing power and processor speed are used to handle data intensive processing, then processing capability improves, but power consumption increases
Solution Approach 1:
The patent replaces traditional mechanical/computational approaches (brute force search, iterative optimization) with a mathematical substitution using convex optimization theory. This substitution transforms the processing problem into one that can be solved efficiently with standard convex optimization algorithms, achieving high productivity without requiring proportionally higher processor power.
Data Source
AI summary
A system for data acquisition and processing includes a selector for obtaining samples from one or more sensors, each of which is configured to collect a sample during one or more sampling intervals forming a dwell period. The selector is configured to obtain only a subset of samples of a complete set of samples that can be collected during a dwell period. A solver is configured to solve an underdetermined system based on the collected samples and a mapping relation/phase function, to jointly determine one or more angles and one or more frequencies of transmissions received by the one or more sensors.