Recent developments in imaging systems have seen the implementation of a radar matched-filtering approach. The goal of the imaging system is to obtain information about an unknown object embedded in the system, by controlling the parameters of the input and measuring the response to the known input. The main merit of using matched filtering in imaging systems is the improvement of Signal to Noise Ratio (SNR). However, the correlation process used in matched filtering may result in a loss of resolution. One way to compensate for lost resolution is via pulse compression. Linear frequency modulated sinusoidal waveforms (chirps) have the property of pulse compression after correlation. Hence, both SNR and resolution can be enhanced by matched-filtering and pulse compression with a chirp. However, the theory behind the effect of chirp parameters on resolution is still not clear. In this paper, a one-dimensional theory of matched-filter imaging with a pulse compressed linear frequency modulated sinusoidal chirp is developed. The effect of the chirp parameters on the corresponding signal is investigated, and guidelines for choosing the chirp parameters for resolution considerations are given based on the developed theory and simulations. The results showed that by manipulating the center frequency, bandwidth, and duration of the chirp, the resolution can be easily enhanced.

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