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The linear frequency modulated (LFM) waveforms for medical imaging have been explored previously. Although the chaotic waveforms are used for radar applications, their benefits for medical imaging applications are not adequately analyzed. In this work, we propose using chaos for microwave medical imaging. Firstly, we consider waveforms generated from two chaotic systems: the Lang-Kobayashi and the Lorenz. Through auto-correlation analysis, we show that these waveforms possess good medical imaging properties. Then, we model the received signal from a prototype of the body tissue consisting of multiple layers (media). This received signal incorporates the transmission and reflection coefficients which are a function of the intrinsic impedance of the media. Lastly, the received signal is cross-correlated with the transmitted signal, i.e., the matched filtering operation. The resultant sharp correlations peaks serve as input to the inversion algorithm that estimates the media's intrinsic impedance, which can further be used to assess the healthy/unhealthy nature of the body part.
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