Weak Signal Detection Method for Millimeter-Wave Sensor Signals Based on Heterodyne Duffing Oscillator

Millimeter-wave technology helps achieve antenna miniaturization and high gain, but it is limited by factors such as short wavelength, high transmission loss, and high signal-to-noise ratio, which put higher requirements on the accuracy and computing speed of signal processing methods. The weak signal detection method based on the Duffing oscillator is suitable for detecting and estimating the parameters of such signals, but its intermittent chaotic state brings difficulties in phase determination and limited frequency detection accuracy. This article proposes a Heterodyne Duffing equation, which analyzes system properties through bifurcation diagrams, timing diagrams, and phase diagrams. Based on this, signal detection and frequency estimation models are designed, and frequency detection accuracy and calculation time are discussed. The analysis and simulation results show that the phase state discrimination speed and accuracy of the Heterodyne Duffing oscillator (HDO) are superior to the traditional Duffing equation-based intermittent chaotic state method. It has adjustable frequency resolution, overcomes the inherent 0.03ω frequency detection error limitation of the traditional Duffing oscillator, and has a significant advantage in phase state discrimination speed. The frequency estimation method based on the proposed HDO can better meet the frequency resolution and real-time requirements of millimeter-wave sensor signals.

Authors

Institutions

Publication Details

Journal
Mathematics
Published
2026-02-03
DOI
https://doi.org/10.3390/math14030545
Primary Topic
Wireless Signal Modulation Classification
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Weak Signal Detection Method for Millimeter-Wave Sensor Signals Based on Heterodyne Duffing Oscillator

Tao An, Ningzhe Zhang, Jinyu Zhang, Xingyu Yan et al.
Mathematics
Wireless Signal Modulation Classification
article

Weak Signal Detection Method for Millimeter-Wave Sensor Signals Based on Heterodyne Duffing Oscillator

Tao An, Ningzhe Zhang, Jinyu Zhang, Xingyu Yan, Xinhong Hao, Jian Dai
article en

Abstract

Millimeter-wave technology helps achieve antenna miniaturization and high gain, but it is limited by factors such as short wavelength, high transmission loss, and high signal-to-noise ratio, which put higher requirements on the accuracy and computing speed of signal processing methods. The weak signal detection method based on the Duffing oscillator is suitable for detecting and estimating the parameters of such signals, but its intermittent chaotic state brings difficulties in phase determination and limited frequency detection accuracy. This article proposes a Heterodyne Duffing equation, which analyzes system properties through bifurcation diagrams, timing diagrams, and phase diagrams. Based on this, signal detection and frequency estimation models are designed, and frequency detection accuracy and calculation time are discussed. The analysis and simulation results show that the phase state discrimination speed and accuracy of the Heterodyne Duffing oscillator (HDO) are superior to the traditional Duffing equation-based intermittent chaotic state method. It has adjustable frequency resolution, overcomes the inherent 0.03ω frequency detection error limitation of the traditional Duffing oscillator, and has a significant advantage in phase state discrimination speed. The frequency estimation method based on the proposed HDO can better meet the frequency resolution and real-time requirements of millimeter-wave sensor signals.

MathematicsVol. 14(3)
Beijing Institute of Technology (CN), Shanghai Power Equipment Research Institute (CN)
Reduced inequalities, Peace, Justice and strong institutions
Openalex Percentile: Top 70%
Wireless Signal Modulation Classification
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.