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To address the performance degradation of the conventional linear frequency modulation signal ranging method in the presence of impulse noise, this paper proposes a novel technique that integrates a sliding-window tracking differentiator (TD) with the fractional Fourier transform (FrFT) ranging method. First, the sliding-window TD filtering algorithm is used to suppress the noise in the echo. Subsequently, the filtered signal is subjected to FrFT to calculate the time delay based on the difference in the peak point positions in the fractional domain for realizing target ranging. The simulation results show that the proposed method can effectively suppress impulse noise of different intensities and achieve an accurate and robust ranging of the target. [ABSTRACT FROM AUTHOR]

LFM signals are widely applied in radar, communication, sonar and many other fields. LFM signals received by these systems contain a lot of noise and outliers. In order to suppress the interference of strong impulse noise on target signals and realize the accurate estimation of LFM signal parameters, the impulse noise of echo signals need to be filtered. In this paper, to solve the problem of poor performance of LFM signal parameter estimation based on fractional Fourier transform in impulse noise, alpha stable distribution is used to establish the mathematical model of impulse noise. The proposed fastest tracking differentiator with an adaptive tracking factor is used to suppress the strong impulse noise, and fractional Fourier transform is used to estimate the parameter of the LFM signals. The experimental results show that the proposed fastest tracking differentiator with an adaptive tracking factor has a good filtering performance. It can effectively filter the impulse noise in the echo signal and allows the FrFT method to accurate estimate the parameters of the LFM signals in strong impulse noise. [ABSTRACT FROM AUTHOR]

Accuracy and speed of parameters estimation for radar signal is very important in optical wireless communications. In order to implement high accuracy and fast speed of parameters estimation, a new estimation algorithm is presented in the paper. The method is based on quadratic phase function (QPF) and fractional Fourier transform (FRFT), which is used to estimate parameters for the chirp signal. In order to avoid two-dimensional searching during FRFT, chirp rate is directly estimated by QPF method, and then the optimum transform order of FRFT is calculated by estimating the chirp rate. Finally, center frequency and amplitude of the chirp signal are estimated by FRFT. Simulation results show that the proposed QPF-FRFT method is faster than the FRFT method and two step maximum modulus searching method. Otherwise, when the SNR is higher than -4dB, the center frequency, chirp rate and amplitude of chirp signal can be estimated by QPF-FRFT method more accurately than FRFT method. In conclusion, results on experimental of chirp signal illustrate the efficient performance of the algorithm. [ABSTRACT FROM AUTHOR]

The parameters estimation of linear frequency modulation (LFM) signals, which also called chirp signals, have been widely applied in optical communication, LIDAR and many other fields. Fractional Fourier transform (FRFT) is one of the most important methods for estimating the frequency of chirp signals. However, the traditional estimation methods based on FRFT are incapable of high-precision parameter estimation for chirp signals, especially multi-component LFM signals. Therefore, we present a novel parameter estimation method based on the Otsu ratio, i.e., the interclass ratio of impulse signal to noise. An algorithm is used to determine this ratio, and then the frequency parameters of chirp signals are estimated by using the ratio as the fitness function. The parameter estimation of single-component and multi-component chirp signals is simulated. The results show that the proposed method has higher estimation accuracy than the traditional FRFT method. [ABSTRACT FROM AUTHOR]