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The phenomenon of frequency ambiguity may appear in radar or communication systems. S. Barbarossa(1991) had unwrapped the frequency ambiguity of single component uri-dersampled signals by Wigner-Ville distribution(WVD). But there has no any effective algorithm to analyze multicomponent undersampled signals by now. A new algorithm to analyze multicomponent undersampled signals by high-order ambiguity function (HAF) is proposed here. HAF analyzes polynomial phase signals by the method of phase rank reduction, its advantage is that it does not have boundary effect and is not sensitive to the cross-items of multicomponent signals. The simulation results prove the effectiveness of HAF algorithm.
The phenomenon of frequency ambiguity may appear in radar or communication systems. S. Barbarossa (1991) had unwrapped the frequency ambiguity of single component uri-dersampled signals by Wigner-Ville distribution (WVD). But there has no any effective algorithm to analyze multicomponent undersampled signals by now. A new algorithm to analyze multicomponent undersampled signals by high-order ambiguity function (HAF) is proposed here. HAF assays polynomial phase signals by the method of phase rank reduction, its advantage is that it does not have a boundary effect and is not sensitive to the cross-items of multicomponent signals. The simulation results prove the effectiveness of HAF algorithm.