Time-Frequency Analysis Of Multicomponent Linear Frequency-Modulated Signals

The studies of real-world ISAR imaging data of airplanes indicate that, because of the time-varying speeds and poses of the targets, the scatters?signals are nonstationary, which in many cases can be approximated as multicomponent Linear Frequency- Modulated signals( LFM, Chirp). Therefore, for the maneuvering targets, it is necessary to obtain the correct time-frequency structure of each scatter for instantaneous imaging. LFM signal not only appears but also is widely used in multitudinous signal processing areas, such as Radar. Communications, Sonar, Medicine, and so on, which makes its studies meaningful in both theories and applications. Time-frequency Distribution (TFD) provides a direct and effective way to analyze the time-frequency structures of nonstationary signals. The crossterms, however, which arise in the TFD of multicomponents, make it difficult to identify and explain the tine- varying spectrum of each component. Suppression of the crossterms is always -a hot potato in time-frequency analysis. With respect to multicomponent LFM signals, the dissertation is mainly concerned with looking for ways to suppress the crossterms appearing in the TFD of multicomponent signals, in order to obtain a TFD with high time-frequency resolution. The following is the summarization of the main work: <~- With respect to multicomponent LFM signals, a new kind of TFD-ada~ve Gaussian kernel distribution (AGD), is proposed. in which the Gaussian kem~l is designed adaptively based on the signals ambiguity function. A simple and effective algorithm to estimate the kernel is given, and the experiments with simulated and real-world data confirm the effects of the AGD in suppressing crossterms and keeping high time-frequency concentration. ~- With the AGD as an example. the influence of the adaptive-kernel distribution based on ambiguity domain and the kernel estimation on the crossterms and signalterms is analyzed, which consequently explains the advantages of adaptive kernels over fixed kernels. The method to adaptively design kernel based on the -Iv- ambiguity function of muliticomponent LFM signals is generalized and the effect of different kind of kernels on TFD is also discussed. ~ Based on the 揅LEANZ~ algorithm, with respect to muliticomponent LFM signals. in which each component has slowly-varying envelope and different time duration, a new method called FC-WVD to suppress crossterrns in Wigner distribution is presented. The basic idea of FC-WVIY is to first decompose the multicomponents into separate subcomponents by use of band-pass filters with the 揅LEAN? algorithm in frequency domain, and then each subcomponent is analyzed using TFD. The influence of the band-pass filter on different component and its Wigner distribution is discussed in detail, and the experiment with simulated and real- world cl~a show satisfactory results of the FC-WVD in improving the time- frequency resolution of multieomponent signals. FC-WVD is also suitable for the time-frequency analysis of signals close to LFMs?or sinusoids. ~ The relationship between the decomposition algorithm based on the 揅LEAN?in the frequency domain and the Fractional Fourier Trax~form (FRFT), the Radon- Wigner Transform (RWT) is analyzed. Furthermore, the comparison between FC- WVD and RWI?Filtered Back-projection algorithm is n~mde. These work makes the FC-WVD method more meaningful...