Multi-station time-frequency map fusion unmanned aerial vehicle signal signal-to-noise ratio cooperative enhancement method and system

By using a multi-station time-frequency map fusion method, and by employing global optimization to solve the problem of low signal-to-noise ratio in complex urban environments, the problem of low signal-to-noise ratio in complex urban environments is solved, and highly reliable, long-range drone detection and monitoring is achieved.

CN122339596APending Publication Date: 2026-07-03JILIN PROVINCIAL INFORMATION CONSTRUCTION PROMOTION CENTER (JILIN PROVINCIAL MACHINERY & EQUIPMENT COMPLETE SETS BUREAU)
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
JILIN PROVINCIAL INFORMATION CONSTRUCTION PROMOTION CENTER (JILIN PROVINCIAL MACHINERY & EQUIPMENT COMPLETE SETS BUREAU)
Filing Date
2026-06-04
Publication Date
2026-07-03

AI Technical Summary

Technical Problem

Existing drone detection technologies are limited by drone transmission power, signal attenuation, and electromagnetic interference in complex urban environments, resulting in low signal-to-noise ratios and making it difficult to achieve highly reliable, long-range drone detection and monitoring.

Method used

By using a multi-station time-frequency map fusion method, UAV time-domain signals collected by multiple time-synchronized radio monitoring stations are acquired, and a two-dimensional time-frequency map is generated by performing short-time Fourier transform. Using a preset reference station as a benchmark, the optimal time delay vector is solved through global optimization to align and fuse the time dimensions, thereby improving the signal-to-noise ratio.

Benefits of technology

It effectively improves the signal-to-noise ratio of UAV signals, enhances detection performance, reduces the difficulty of system hardware implementation, and improves detection reliability and positioning accuracy in complex electromagnetic environments.

✦ Generated by Eureka AI based on patent content.

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Abstract

This application discloses a method and system for collaboratively enhancing the signal-to-noise ratio (SNR) of UAV signals through multi-station time-frequency map fusion, relating to the field of UAV radio detection and signal processing technology. The method includes: acquiring UAV time-domain signals collected by several time-synchronized radio monitoring stations, where ≥2; performing a short-time Fourier transform on the UAV time-domain signals collected by each radio monitoring station to obtain the corresponding two-dimensional time-frequency map; using a preset reference radio monitoring station as a benchmark and aiming for optimal time-frequency map fusion quality, obtaining the optimal time delay vectors of the remaining stations relative to the reference station through global optimization; aligning and fusing the two-dimensional time-frequency maps according to the optimal time delay vectors, and outputting a fused time-frequency map. This invention can effectively improve the SNR of UAV signals in low SNR environments, enhance the reliability of UAV detection in complex electromagnetic environments, and provide reliable data support for subsequent UAV identification and positioning.
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