Correlative Receiver Wireless Emitter Mapping
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Solution Overview
Problem
Existing methods struggle to accurately and efficiently map and classify wireless emitters in a geographic area without decrypting or decoding the information in their emissions.
Innovation Solution
The use of a correlative receiver system that processes signal inputs from multiple antennas to determine geolocations and characteristics of wireless emitters by analyzing spectral correlation and cyclic-autocorrelation functions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If spectral correlation and cyclic-autocorrelation functions are used to map wireless emitters, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system segments the complex spectral analysis into modular components: multiple antennas receive signals independently, correlation processing is separated into distinct computational stages, and geolocation is derived from processed correlation outputs. This modular segmentation enables high-precision mapping while managing system complexity through organized functional blocks.
2Measurement precision
If multiple antennas are used to receive wireless emissions, then measurement precision is improved, but device complexity increases
Solution Approach 1:
Multiple antennas are merged into a coordinated array system where signals from all antennas are processed together through correlation functions. This merging enables precise emitter geolocation by combining spatial information from multiple reception points, achieving high measurement precision while managing complexity through unified signal processing.
3Productivity
If real-time processing of wireless emissions is performed, then productivity is improved, but use of energy increases
Solution Approach 1:
The system performs preliminary correlation processing on received signals before final geolocation calculation. By pre-computing spectral and cyclic-autocorrelation functions from the raw emissions, the system prepares processed data that can be quickly converted into geolocation information, enabling real-time productivity while distributing energy consumption across staged processing operations.
Data Source
AI summary
Systems and methods for mapping location and characteristics about wireless emitters are described. The systems and methods advantageously use correlative receivers for observing the emissions from the wireless emitters without decrypting or decoding information included in the emissions from the wireless emitters to allow for tracking location and emitter class and type in real-time. The real-time geolocation and emitter class information for many receivers in a geographic area can be determined and overlaid on a map, for example.