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
It has been shown that analog-to-information conversion(AIC) is an efficient scheme to perform sub-Nyquist sampling of pulsed radar echoes. However, it is often impractical, if not infeasible, to reconstruct full-rang...It has been shown that analog-to-information conversion(AIC) is an efficient scheme to perform sub-Nyquist sampling of pulsed radar echoes. However, it is often impractical, if not infeasible, to reconstruct full-range Nyquist samples because of huge storage and computational load requirements. Based on the analyses of AIC measurement system, this paper develops a novel segment-sliding reconstruction(Seg SR) scheme to effectively reconstruct the Nyquist samples. The Seg SR performs segment-by-segment reconstruction in a sliding mode and can be implemented in real time. An important characteristic that distinguishes the proposed Seg SR from existing methods is that the measurement matrix in each segment satisfies the restricted isometry property(RIP) condition. Partial support in the previous segment can be incorporated into the estimation of the Nyquist samples in the current segment. The effect of interference introduced from adjacent segments is theoretically analyzed, and it is revealed that the interference consists of two interference levels with different impacts to the signal reconstruction performance. With these observations, a two-step orthogonal matching pursuit(OMP)procedure is proposed for segment reconstruction, which takes into account different interference levels and partially known support of the previous segment. The proposed Seg SR scheme achieves near-optimal reconstruction performance with a significant reduction of computational loads and storage requirements. Theoretical analyses and simulations verify its effectiveness.展开更多
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.
基金supported by National Natural Science Foundation of China (Grant Nos. 61171166, 61401210, 61571228)China Postdoctoral Science Foundation (Grant No. 2014M551597)
文摘It has been shown that analog-to-information conversion(AIC) is an efficient scheme to perform sub-Nyquist sampling of pulsed radar echoes. However, it is often impractical, if not infeasible, to reconstruct full-range Nyquist samples because of huge storage and computational load requirements. Based on the analyses of AIC measurement system, this paper develops a novel segment-sliding reconstruction(Seg SR) scheme to effectively reconstruct the Nyquist samples. The Seg SR performs segment-by-segment reconstruction in a sliding mode and can be implemented in real time. An important characteristic that distinguishes the proposed Seg SR from existing methods is that the measurement matrix in each segment satisfies the restricted isometry property(RIP) condition. Partial support in the previous segment can be incorporated into the estimation of the Nyquist samples in the current segment. The effect of interference introduced from adjacent segments is theoretically analyzed, and it is revealed that the interference consists of two interference levels with different impacts to the signal reconstruction performance. With these observations, a two-step orthogonal matching pursuit(OMP)procedure is proposed for segment reconstruction, which takes into account different interference levels and partially known support of the previous segment. The proposed Seg SR scheme achieves near-optimal reconstruction performance with a significant reduction of computational loads and storage requirements. Theoretical analyses and simulations verify its effectiveness.
