Single channel blind estimation algorithm for parameters of multiple frequency-hopping signals

被引：0
作者：
Zhang D. [1 ,2 ]
Liang X. [1 ,2 ]
Wang P. [1 ,2 ]
Yin C. [3 ]
机构：
[1] Air Traffic Control and Navigation School, Air Force Engineering University, Xi'an
[2] Shaanxi Key Laboratory of Meta-Synthesis for Electronic and Information System, Xi'an
[3] Unit 94654, the Chinese People's Liberation Army, Nanjing
来源：
Huazhong Keji Daxue Xuebao (Ziran Kexue Ban)/Journal of Huazhong University of Science and Technology (Natural Science Edition) | 2023年 / 51卷 / 06期
关键词：
blind parameter estimation; frequency-hopping signal; single channel; spectral entropy; start hopping time;
D O I：
10.13245/j.hust.230624
中图分类号：
学科分类号：
摘要：
In order to effectively support the tasks of frequency hopping (FH) network sorting，interference support and information recovery，a blind estimation algorithm for multi-frequency hopping signal parameters based on start hopping time (SHT) sequence detection and sorting was presented under single channel condition，and an asynchronous network frequency automatic sorting was implemented．Firstly，the theoretical distribution of the start hopping time sequences of three types of reconnaissance scenes was summarized，and the theoretical expression of the time domain parameters of frequency hopping signals based on the sorting results of the start hopping time sequences was deduced． Then，an improved spectral entropy algorithm combined with the designed adaptive threshold was used to detect/extract the start hopping time sequence accurately．Based on this，the intercepted samples were divided into several frequency residence times (FRT)，and the accurate estimation of the frequency component in frequency residence times was achieved by combining FFT (fast Fourier transformation) with WVD (Wigner-Ville distribution)．Secondly，making full use of the frequency domain hopping property of frequency hopping signal，the start hopping time sequence was sorted by “frequency hopping”detection of the frequency components in adjacent frequency residence times，which provides data support for blind estimation of time domain parameters of each frequency hopping signal．Finally，the complete flow of the proposed algorithm was summarized．Theoretical analysis and Monte Carlo simulation results show that the proposed algorithm is adaptive to different frequency hopping networking modes，with high estimation accuracy and simple calculation. © 2023 Huazhong University of Science and Technology. All rights reserved.
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页码：152 / 159+165
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