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| Fundamental Frequency Estimation Method for Low-Altitude Helicopter Acoustic-to-Seismic Wave Signals Based on Harmonic Structure Correlation |
| NIE Yixuan1， JIANG Libing1， LIU Xiaojun1， WANG Zhuang1，
DAI Shaohuai2 |
| 1. College of Electronic Science and Technology， National University of Defense Technology， Changsha 410073， Hunan， China； 2. Shanghai Electro-Mechanical Engineering Institute， Shanghai 201109， China |
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Abstract During low-altitude helicopter flight, air vibrations excited by rotor blade rotation propagate to the ground through the acoustic-to-seismic coupling effect, forming acoustic-to-seismic waves. In the frequency domain, these waves exhibit harmonic characteristics with the blade passage frequency (BPF) as the fundamental frequency, which serves as an important feature for low-altitude helicopter detection. To address the problem of fundamental frequency estimation bias or even failure caused by differential spectral attenuation and complete absorption of certain frequencies during seismic wave propagation along the ground surface under varying geological conditions, this paper proposes a target fundamental frequency estimation method based on harmonic structure correlation in the cyclic frequency domain. By considering the frequency selectivity and amplitude modulation effects of surface media during the propagation of acoustic-to-seismic waves from low-altitude helicopters, and combining the intrinsic harmonic characteristics of target signals, a signal constraint model under harmonic structure correlation is constructed. Furthermore, an optimal discrimination is built based on the clustering concept to achieve effective identification of the target fundamental frequency. Simulation and measured data demonstrate that the proposed method can effectively identify the target fundamental frequency and exhibits favorable robustness against missing signal harmonics and random frequency interference, providing a reliable fundamental frequency estimation approach for target detection of low-altitude helicopters via acoustic-to-seismic waves under complex geological conditions.
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Received: 17 March 2026
Published: 10 July 2026
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| [1] |
DU Jiangpeng, WANG Chaofeng, ZHANG Xiaowei, TIAN Yi, SHE Shaobo, ZHANG Qunyan. Research on Intelligent Target Spectral Detection Technology Based on Field-of-View Gating[J]. Air & Space Defense, 2026, 9(4): 119-127. |
| [2] |
ZHANG Kunfeng, XU Xiao, SUN Zhuoran, XU Zhizhao, NIU Yalei. Design of Real-Time Simulation System for Target Detection and Tracking Devices Based on Digital-Physical Integration[J]. Air & Space Defense, 2026, 9(2): 60-67. |
| [3] |
WANG Jianyuan, CHEN Xiaotong, ZHANG Yue, SUN Junge, SHI Donghao, CHEN Jinbao. Urban Target Detection Algorithm Based on Multi-Modal Fusion of UAV[J]. Air & Space Defense, 2024, 7(1): 32-39. |
| [4] |
CAI Yunze, ZHANG Yanjun. Infrared Dim and Small Target Detection Based on Dual-Channel Feature-Enhancement Integrated Attention Network[J]. Air & Space Defense, 2021, 4(4): 14-22. |
| [5] |
WANG Yuexing, WU Yongguo, XU Chuangang. Infrared Ship Target Detection Algorithm Based on Deep Transfer Learning[J]. Air & Space Defense, 2021, 4(4): 61-66. |
| [6] |
ZHAO Huipan, LIU Huanyu. Low Signature Target Group Detection Based on Multimodal Data Learning Fusion Network[J]. Air & Space Defense, 2021, 4(3): 41-47. |
| [7] |
TONG Pengfei, CHEN Hao, XU Xinpeng, ZHOU Ge. Study on Information Fusion Technology of Multi-missile Multi-target Collaborative Detection[J]. Air & Space Defense, 2020, 3(3): 54-62. |
| [8] |
ZHANG Yan, JIA Zhenyu, ZHOU Guren, HUANG Zhengrong, LIU Jingqiu. Infrared Dim Target Detection Based on Multi-directional Mixed Template[J]. Air & Space Defense, 2019, 2(1): 64-69. |
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2026, Vol. 9 
