We propose a method that uses linear chirp modulated Gaussian functions as the elementary functions, by adaptively adjusting variances, time frequency centers and sweep rates, to decompose signals. By taking WVD, an ...We propose a method that uses linear chirp modulated Gaussian functions as the elementary functions, by adaptively adjusting variances, time frequency centers and sweep rates, to decompose signals. By taking WVD, an improved adaptive time frequency distribution is developed, which is non negative, free of cross term interference, and of better time frequency resolution. The paper presents an effective numerical algorithm to estimate the optimal parameters of the basis. Simulations indicate that the proposed approach is effective in analyzing signal's time frequency behavior.展开更多
Aim To find an effective and fast algorithm to analyze undersampled signals. Methods\ The advantage of high order ambiguity function(HAF) algorithm is that it can analyze polynomial phase signals by phase rank reduct...Aim To find an effective and fast algorithm to analyze undersampled signals. Methods\ The advantage of high order ambiguity function(HAF) algorithm is that it can analyze polynomial phase signals by phase rank reduction. In this paper, it was first used to analyze the parameters of undersampled signals. When some conditions are satisfied, the problem of frequency confusion can be solved. Results and Conclusion\ As an example, we analyze undersampled linear frequency modulated signal. The simulation results verify the effectiveness of HAF algorithm. Compared with time frequency distribution, HAF algorithm reduces computation burden to a great extent, needs weak boundary conditions and doesn't have boundary effect.展开更多
A method is presented for the detection and parameter estimation of a single Linear Frequency Modulation (LFM) signal in spread spectrum systems based on Wigner Hough Transform (WHT) , followed by the theoreti...A method is presented for the detection and parameter estimation of a single Linear Frequency Modulation (LFM) signal in spread spectrum systems based on Wigner Hough Transform (WHT) , followed by the theoretical analysis. A simulation result is given to show the effectiveness of this method.展开更多
文摘We propose a method that uses linear chirp modulated Gaussian functions as the elementary functions, by adaptively adjusting variances, time frequency centers and sweep rates, to decompose signals. By taking WVD, an improved adaptive time frequency distribution is developed, which is non negative, free of cross term interference, and of better time frequency resolution. The paper presents an effective numerical algorithm to estimate the optimal parameters of the basis. Simulations indicate that the proposed approach is effective in analyzing signal's time frequency behavior.
文摘Aim To find an effective and fast algorithm to analyze undersampled signals. Methods\ The advantage of high order ambiguity function(HAF) algorithm is that it can analyze polynomial phase signals by phase rank reduction. In this paper, it was first used to analyze the parameters of undersampled signals. When some conditions are satisfied, the problem of frequency confusion can be solved. Results and Conclusion\ As an example, we analyze undersampled linear frequency modulated signal. The simulation results verify the effectiveness of HAF algorithm. Compared with time frequency distribution, HAF algorithm reduces computation burden to a great extent, needs weak boundary conditions and doesn't have boundary effect.
文摘A method is presented for the detection and parameter estimation of a single Linear Frequency Modulation (LFM) signal in spread spectrum systems based on Wigner Hough Transform (WHT) , followed by the theoretical analysis. A simulation result is given to show the effectiveness of this method.
