scholarly journals Rotor UAV’s Micro-Doppler Signal Detection and Parameter Estimation Based on FRFT-FSST

Sensors ◽  
2021 ◽  
Vol 21 (21) ◽  
pp. 7314
Author(s):  
Huiling Hou ◽  
Zhiliang Yang ◽  
Cunsuo Pang
Keyword(s):  
Parameter Estimation ◽  
Signal Detection ◽  
Fractional Fourier Transform ◽  
Structural Features ◽  
Doppler Signal ◽  
Frequency Resolution ◽  
Time Frequency ◽  
Doppler Signals ◽  
Aerial Vehicle ◽  
Frequency Features

The micro-Doppler signal generated by the rotors of an Unmanned Aerial Vehicle (UAV) contains the structural features and motion information of the target, which can be used for detection and classification of the target, however, the standard STFT has the problems such as the lower time-frequency resolution and larger error in rotor parameter estimation, an FRFT (Fractional Fourier Transform)-FSST(STFT based synchrosqueezing)-based method for micro-Doppler signal detection and parameter estimation is proposed in this paper. Firstly, the FRFT is used in the proposed method to eliminate the influence of the velocity and acceleration of the target on the time-frequency features of the echo signal from the rotors. Secondly, the higher time-frequency resolution of FSST is used to extract the time-frequency features of micro-Doppler signals. Moreover, the specific solution methodologies for the selection of window length in STFT and the estimation of rotor parameters are given in the proposed method. Finally, the effectiveness and accuracy of the proposed method for target detection and rotor parameter estimation are verified through simulation and measured data.

LFM Signal Detection Method Based on Fractional Fourier Transform

2014 ◽  
Vol 989-994 ◽  
pp. 4001-4004 ◽  
Author(s):  
Yan Jun Wu ◽  
Gang Fu ◽  
Yu Ming Zhu
Keyword(s):  
Fourier Transform ◽  
Signal Detection ◽  
Frequency Analysis ◽  
Experimental Analysis ◽  
Fractional Fourier Transform ◽  
Detection Method ◽  
Time Frequency Analysis ◽  
Time Frequency ◽  
Frequency Information ◽  
Strong Impulse

As a generalization of Fourier transform, the fractional Fourier Transform (FRFT) contains simultaneity the time-frequency information of the signal, and it is considered a new tool for time-frequency analysis. This paper discusses some steps of FRFT in signal detection based on the decomposition of FRFT. With the help of the property that a LFM signal can produce a strong impulse in the FRFT domain, the signal can be detected conveniently. Experimental analysis shows that the proposed method is effective in detecting LFM signals.

scholarly journals Parameter estimation of linear and quadratic chirps by employing the fractional fourier transform and a generalized time frequency transform

Sadhana ◽  
2015 ◽  
Vol 40 (4) ◽  
pp. 1049-1075 ◽  
Author(s):  
SHISHIR B SAHAY ◽  
T MEGHASYAM ◽  
RAHUL K ROY ◽  
GAURAV POONIWALA ◽  
SASANK CHILAMKURTHY ◽  
...  
Keyword(s):  
Fourier Transform ◽  
Parameter Estimation ◽  
Fractional Fourier Transform ◽  
Time Frequency ◽  
Generalized Time

scholarly journals Efficient Rotational Angular Velocity Estimation of Rotor Target via Modified Short-Time Fractional Fourier Transform

2021 ◽  
Vol 13 (10) ◽  
pp. 1970
Author(s):  
Wantian Wang ◽  
Yong Zhu ◽  
Ziyue Tang ◽  
Yichang Chen ◽  
Zhenbo Zhu ◽  
...  
Keyword(s):  
Fourier Transform ◽  
Angular Velocity ◽  
Frequency Spectrum ◽  
Hough Transform ◽  
Fractional Fourier Transform ◽  
Velocity Estimation ◽  
Frequency Resolution ◽  
Time Frequency ◽  
Angular Velocity Estimation ◽  
Short Time

As a special micro-motion feature of rotor target, rotational angular velocity can provide a discriminant basis for target classification and recognition. In this paper, the authors focus on an efficient rotational angular velocity estimation method of the rotor target is based on the combination of the time–frequency analysis algorithm and Hough transform. In order to avoid the problems of low time–frequency resolution and cross-term interference in short-time Fourier transform and Wigner–Ville distribution algorithm, a modified short-time fractional Fourier transform (M-STFRFT) is proposed to obtain the time-FRFT domain (FRFD)-frequency spectrum with the highest time–FRFD–frequency resolution. In particular, an orthogonal matching pursuit (OMP)-based algorithm is proposed to reduce the computational complexity when estimating the matched transform order in the proposed M-STFRFT algorithm. Firstly, partial transform order candidates are selected randomly from the complete candidates. Then, a partial entropy vector corresponding to partial transform order candidates is calculated from the FRFT results and utilized to reconstruct the complete entropy vector via the OMP algorithm, and the matched transform order can be estimated by searching minimum entropy. Based on the estimated matched transform order, STFRFT is performed to obtain the time–FRFD–frequency spectrum. Moreover, Hough transform is employed to obtain the energy accumulation spectrum, and the micro-Doppler parameter of rotational angular velocity can be estimated by searching the peak value from the energy accumulation spectrum. Both simulated data and measured data collected by frequency modulated continuous wave radar validate the effectiveness of the proposed algorithm.

scholarly journals An Efficient ISAR Imaging of Targets with Complex Motions Based on a Quasi-Time-Frequency Analysis Bilinear Coherent Algorithm

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2814
Author(s):  
Cao Zeng ◽  
Mengyi Qin ◽  
Dong Li ◽  
Hongqing Liu ◽  
Yi Chai
Keyword(s):  
Parameter Estimation ◽  
Frequency Analysis ◽  
Frequency Resolution ◽  
Cubic Phase ◽  
Noise Resistance ◽  
Time Frequency Analysis ◽  
Time Frequency ◽  
Coherent Integration ◽  
Isar Imaging ◽  
The Cross

The inverse synthetic aperture radar (ISAR) imaging for targets with complex motions has always been a challenging task due to the time-varying Doppler parameter, especially at the low signal-to-noise ratio (SNR) condition. In this paper, an efficient ISAR imaging algorithm for maneuvering targets based on a noise-resistance bilinear coherent integration is developed without the parameter estimation. First, the received signals of the ISAR in a range bin are modelled as a multicomponent quadratic frequency-modulated (QFM) signal after the translational motion compensation. Second, a novel quasi-time-frequency representation noise-resistance bilinear Radon-cubic phase function (CPF)-Fourier transform (RCFT) is proposed, which is based on the coherent integration of the energy of auto-terms along the slope line trajectory. In doing so, the RCFT also effectively suppresses the cross-terms and spurious peaks interference at no expense of the time-frequency resolution loss. Third, the cross-range positions of target’s scatters in ISAR image are obtained via a simple maximization projection from the RCFT result to the Doppler centroid axis, and the final high-resolution ISAR image is thus produced by regrouping all the range-Doppler frequency centroids. Compared with the existing time-frequency analysis-based and parameter estimation-based ISAR imaging algorithms, the proposed method presents the following features: (1) Better cross-term interference suppression at no time-frequency resolution loss; (2) computationally efficient without estimating the parameters of each scatters; (3) higher signal processing gain because of 2-D coherent integration realization and its bilinear function feature. The simulation results are provided to demonstrate the performance of the proposed method.

Frequency hopping signal detection based on wavelet decomposition and Hilbert–Huang transform

2017 ◽  
Vol 31 (19-21) ◽  
pp. 1740078 ◽  
Author(s):  
Yang Zheng ◽  
Xihao Chen ◽  
Rui Zhu
Keyword(s):  
Signal Detection ◽  
Frequency Analysis ◽  
Wavelet Decomposition ◽  
Frequency Hopping ◽  
Detection Algorithm ◽  
Frequency Resolution ◽  
Hilbert Huang Transform ◽  
Time Frequency ◽  
Low Probability ◽  
Simulation Results

Frequency hopping (FH) signal is widely adopted by military communications as a kind of low probability interception signal. Therefore, it is very important to research the FH signal detection algorithm. The existing detection algorithm of FH signals based on the time-frequency analysis cannot satisfy the time and frequency resolution requirement at the same time due to the influence of window function. In order to solve this problem, an algorithm based on wavelet decomposition and Hilbert–Huang transform (HHT) was proposed. The proposed algorithm removes the noise of the received signals by wavelet decomposition and detects the FH signals by Hilbert–Huang transform. Simulation results show the proposed algorithm takes into account both the time resolution and the frequency resolution. Correspondingly, the accuracy of FH signals detection can be improved.

Time Frequency Analysis of Femoral Doppler Ultrasound Signals by AR Modelling

2013 ◽  
Vol 302 ◽  
pp. 319-325
Author(s):  
Latfaoui Mahieddine ◽  
Bereksi Reguig Fethi
Keyword(s):  
Moving Average ◽  
Frequency Resolution ◽  
Doppler Spectrum ◽  
Autoregressive Moving Average ◽  
Ultrasonic Signals ◽  
Time Frequency ◽  
Power Spectral ◽  
Doppler Signals ◽  
Short Time ◽  
The Impact

In this study, we have compared the efficiency of the short time Fourier transform (STFT) and autoregressive modelling (AR) and autoregressive moving average (ARMA) of the femoral Doppler artery ultrasonic signals, in order to determine the spectral broadening index (SBI). Our aim is to detect the impact of the two modelling approaches on sonograms and of power spectral density- frequency diagrams obtained from femoral arterial Doppler Signals. The sonograms have been then used to compare the methods in terms of their frequency resolution and effects in determining the stenosis of femoral artery. In this paper we have used generated frequency envelopes from the Doppler spectrum to determine an index showing the degree of severity of stenosis cases. This index called broadening spectral index is calculated for various real cases.

Detection and Parameter Estimation of Chirp Signal Based on Time-Frequency Analysis

2014 ◽  
Vol 989-994 ◽  
pp. 3989-3992
Author(s):  
Guang Zhi Wu ◽  
Gang Fu ◽  
Yan Jun Wu
Keyword(s):  
Fourier Transform ◽  
Parameter Estimation ◽  
Fractional Fourier Transform ◽  
Chirp Signal ◽  
Wigner Transform ◽  
Time Frequency ◽  
The Relationship ◽  
Generic Time ◽  
Time Frequency Distribution ◽  
Better Than

Based on the relationship between the Radon-Wigner transform and fractional Fourier transform and the time frequency distribution, using the property that Radon-Wigner transform has better performance in time and frequency domain, detection and parameter estimation of Chirp signal have been done by Radon-Wigner transform or fractiona1 Fourier transform. The theoretica1 analysis and simulation prove that two techniques are better than generic time-frequency transform, such as Wigner-Ville transform.

Image encryption based on Fractional wavelet transform, Arnold transform with the double random phases in HSV color domain

2020 ◽  
Vol 13 ◽  
Author(s):  
Aarushi Shrivastava ◽  
Janki Ballabh Sharma ◽  
Sunil Dutt Purohit
Keyword(s):  
Wavelet Transform ◽  
Image Encryption ◽  
Fractional Fourier Transform ◽  
Color Image ◽  
Random Phase ◽  
Arnold Transform ◽  
Time Frequency ◽  
Key Space ◽  
Secret Keys ◽  
Fractional Wavelet Transform

Objective: In the recent multimedia technology images play an integral role in communication. Here in this paper, we propose a new color image encryption method using FWT (Fractional Wavelet transform), double random phases and Arnold transform in HSV color domain. Methods: Firstly the image is changed into the HSV domain and the encoding is done using the FWT which is the combination of the fractional Fourier transform with wavelet transform and the two random phase masks are used in the double random phase encoding. In this one inverse DWT is taken at the end in order to obtain the encrypted image. To scramble the matrices the Arnold transform is used with different iterative values. The fractional order of FRFT, the wavelet family and the iterative numbers of Arnold transform are used as various secret keys in order to enhance the level of security of the proposed method. Results: The performance of the scheme is analyzed through its PSNR and SSIM values, key space, entropy, statistical analysis which demonstrates its effectiveness and feasibility of the proposed technique. Stimulation result verifies its robustness in comparison to nearby schemes. Conclusion: This method develops the better security, enlarged and sensitive key space with improved PSNR and SSIM. FWT reflecting time frequency information adds on to its flexibility with additional variables and making it more suitable for secure transmission.

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