A New Hop Duration Blind Estimation Algorithm for Frequency-Hopping Signals

Lei, Yingke; Zi-fa, Zhong; Wu, Yanhua

doi:10.1109/paciia.2008.378

Cited by 8 publications

(2 citation statements)

References 4 publications

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“…For quadratic TFA methods, such as Cohen's class distribution, a large number of time-frequency cross terms will be generated under strong interference and noise, which greatly limits its application under the condition of low SNR. Although many researchers have made many improvements to the quadratic TFA methods in order to obtain better time-frequency distribution, such as smoothing pseudo Wigner Ville distribution (SPWVD) [11], Radially Gaussian Kernel Distribution (RGKD) [12,13] and so on. In the application of TFA method, problems such as time-frequency resolution, analysis accuracy, cross term influence, etc.…”

Section: Introductionmentioning

confidence: 99%

A Novel Parameter Estimation Method of FHSS Signal with Low SNR

Zhu

Dai

et al. 2023

IEEJ Transactions Elec Engng

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A novel parameter estimation method of frequency hopping spread spectrum (FHSS) signal is proposed. The observed signal is divided into multiple segments and forms an observed matrix, performing FFT on the observed matrix with different segment lengths to obtain the corresponding spectrum matrix. By analyzing the convergence characteristics of the spectrum matrix, the estimation of the symbol period is realized, on this basis, the symbol‐frequency distribution is obtained and its projected spectrum in Frequency‐Amplitude plane is further obtained to select the candidate frequencies. The matrix composed of multiple single frequency signals is constructed according to the candidate frequencies and multiplied with the observed matrix under the segment length of symbol period, then the number of symbols per hopping duration is estimated according to the matrix multiplication result, so as to realize the estimation of the hopping duration, and finally the real hopping frequencies and hopping sequence can be found out from the candidate frequencies. Simulation results are presented to indicate that the proposed method has good estimation performance especially under the condition of low SNR. © 2023 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

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Section: Introductionmentioning

confidence: 99%

A Novel Parameter Estimation Method of FHSS Signal with Low SNR

Zhu

Dai

et al. 2023

IEEJ Transactions Elec Engng

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“…. 따라서 주파수 도약 대역확산 신호의 수신을 위해 동기 획득 [2,3] , 신호 검출 및 분리 [4,5] , 도약 시각 및 도 약 주파수와 같은 파라미터 추정 [6][7][8][9][10] , 기저대역 복조 …”

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A Blind Hopping Phase Estimator in Hopped FM/BFSK Systems

Seong¹,

Jeong²,

Lee³

2014

The Journal of Korea Information and Communications Society

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We proposed a hopping phase estimator to demodulate the received signals without any hopping information in frequency hopping spread spectrum systems. The demodulation process in this paper is as follows: hopped frequency tracking is accomplished by choosing a frequency component with maximum amplitude after taking discrete Fourier transform and a hopping frequency estimator which estimates the phase generated by hopped frequency is established through difference product and down-sampling. We obtained the probability density function and variance performance of the proposed estimator and confirmed that the analysis and the simulation results were agreed with each other. . 따라서 주파수 도약 대역확산 신호의 수신을 위해 동기 획득 [2,3] , 신호 검출 및 분리 [4,5] , 도약 시각 및 도 약 주파수와 같은 파라미터 추정 [6][7][8][9][10] , 기저대역 복조

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An Adaptive Window Time-Frequency Analysis Method Based on Short-Time Fourier Transform

Wang

et al. 2019

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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A New Hop Duration Blind Estimation Algorithm for Frequency-Hopping Signals

Cited by 8 publications

References 4 publications

A Novel Parameter Estimation Method of FHSS Signal with Low SNR

A Novel Parameter Estimation Method of FHSS Signal with Low SNR

A Blind Hopping Phase Estimator in Hopped FM/BFSK Systems

An Adaptive Window Time-Frequency Analysis Method Based on Short-Time Fourier Transform

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