Adaptive instantaneous frequency estimation based on time-frequency distributions with derivative approximation

Abdoush, Yazan; Garcia-Molina, J.A.; Corazza, G.E.

doi:10.1016/j.sigpro.2019.01.027

Cited by 15 publications

(7 citation statements)

References 24 publications

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“…In (7), the observed signal is divided into r segments with the same length M , this observed matrix is composed of all the segmented signal vectors. If M = N s , each column of D(M ) is a single frequency signal without phase discontinuous point or frequency hopping point, for example, the m-th column can be expressed as:…”

Section: Estimation Of Symbol Period For Observed Signalmentioning

confidence: 99%

“…reflects the maximum value in the frequency domain of n-th column in the observed matrix (7) when the signal segment length is M. Obviously, when the n-th column signal is a single frequency signal without phase discontinuous point or frequency hopping point, it has the best convergence characteristic in the frequency domain, and there will be a large value of S (M ) S −A [n]. If M = N s , there may be several phase discontinuous points or frequency hopping points in some columns of D(M ), the existence of these points makes the spectrum convergence of each column weaker than that of single frequency continuous signal when M = N s .…”

Section: Psmentioning

confidence: 99%

“…While the reception delay is n τ = 0, the matrix constructed by (7) has the structure as shown in Fig. A1 With estimated N s , moving i-1 points out of the observation matrix to get:…”

Section: Initial Timing Acquisitionmentioning

confidence: 99%

“…The frequency of FHSS signal changes randomly with time, which belongs to non-stationary signal, so joint time-frequency analysis (TFA) [4][5][6][7][8] is a common method to analyze FHSS signals, the basic idea of joint time-frequency analysis is to estimate the instantaneous frequency, and then estimate the modulation parameters. Therefore, the estimation accuracy of the instantaneous frequency determines the accuracy of parameters estimation.…”

Section: Introductionmentioning

confidence: 99%

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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: Estimation Of Symbol Period For Observed Signalmentioning

confidence: 99%

Section: Psmentioning

confidence: 99%

“…While the reception delay is n τ = 0, the matrix constructed by (7) has the structure as shown in Fig. A1 With estimated N s , moving i-1 points out of the observation matrix to get:…”

Section: Initial Timing Acquisitionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Novel Parameter Estimation Method of FHSS Signal with Low SNR

Zhu

Dai

et al. 2023

IEEJ Transactions Elec Engng

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“…Generally, the most energetic points of the time-frequency distributions are merged in order to form the IF law of each component and, for this purposes, different time-frequency representations can be used: Wigner distribution [5], multi-window short time Fourier transform [6], pseudo-Wigner-Ville distribution [7], polynomial Wigner-Ville distribution [8]. For instance, different techniques have been proposed for the optimization of IF law estimation from time-frequency distribution based on Viterbi methodology [9,10,11,12].…”

Section: Introductionmentioning

confidence: 99%

Phase Diagram-Based Sensing with Adaptive Waveform Design and Recurrent States Quantification for the Instantaneous Frequency Law Tracking

Digulescu

Ioana

Șerbănescu

2019

Sensors

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Monitoring highly dynamic environments is a difficult task when the changes within the systems require high speed monitoring systems. An active sensing system has to solve the problem of overlapped responses coming from different parts of the surveyed environment. Thus, the need of a new representation space which separates the overlapped responses, is mandatory. This paper describes two new concepts for high speed active sensing systems. On the emitter side, we propose a phase-space-based waveform design that presents a unique shape in the phase space, which can be easily converted into a real signal. We call it phase space lobe. The instantaneous frequency (IF) law of the emitted signal is found inside the time series. The main advantage of this new concept is its capability to generate several distinct signals, non-orthogonal in the time/frequency domain but orthogonal within the representation space, namely the phase diagram. On the receiver side, the IF law information is estimated in the phase diagram representation domain by quantifying the recurrent states of the system. This waveform design technique gives the possibility to develop the high speed sensing methods, adapted for monitoring complex dynamic phenomena In our paper, as an applicative context, we consider the problem of estimating the time of flight in an dynamic acoustic environment. In this context, we show through experimental trials that our approach provides three times more accurate estimation of time of flight than spectrogram based technique. This very good accuracy comes from the capability of our approach to generate separable IF law components as well as from the quantification in phase diagram, both of them being the key element of our approach for high speed sensing.

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Second-Order Multisynchrosqueezing Wavelet Transform for Bearing Fault Detection

Han

Zhou

et al. 2022

J. Vib. Eng. Technol.

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Adaptive instantaneous frequency estimation based on time-frequency distributions with derivative approximation

Cited by 15 publications

References 24 publications

A Novel Parameter Estimation Method of FHSS Signal with Low SNR

A Novel Parameter Estimation Method of FHSS Signal with Low SNR

Phase Diagram-Based Sensing with Adaptive Waveform Design and Recurrent States Quantification for the Instantaneous Frequency Law Tracking

Second-Order Multisynchrosqueezing Wavelet Transform for Bearing Fault Detection

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