Inverse Synthetic Aperture Radar Imaging With MATLAB Algorithms. Caner Ozdemir

Inverse Synthetic Aperture Radar Imaging With MATLAB Algorithms - Caner Ozdemir


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serial LFM waves is T, the frequency variation of such waveforms can be represented as in Figure 2.12a. The received signal arrives with a time delay of td. This time delay can be determined in the following manner: The difference in the frequency between the transmitted and the received signals, Δf, can be found as below:

      Of course, time delay td is related to the range, R, of the target by the following equation:

      (2.49)equation

Graphs depict of LFMCW radar: (a) time-frequency display of the transmitted and received LFMCW signals, (b) the difference in the frequency between the transmitted and the received signals.

      It is also obvious from Figure 2.12 that range ambiguity occurs when td > T. Therefore, the maximum difference in frequency can be Δfmax = KT, which means that the maximum unambiguous range can be determined as

Schematic illustration of radar block diagram.

      

      2.6.3 Stepped‐Frequency Continuous Wave

      (2.51)equation

      (2.52)equation

Schematic illustration of signal in time-frequency plane.

      (2.53)equation

      Here, Es is the scattered electric field, A is the scattered field amplitude, and k is the wavenumber vector corresponding to the frequency vector of f = [fo f1 f2fN−1]. The number 2 in the phase corresponds to the two‐way propagation between radar‐ to‐ target and target to radar. It is obvious that there is FT relationship between (2k) and (R). Therefore, it is possible to resolve the range, Ro, by taking the inverse Fourier transform (IFT) of the output of the SFCW radar. The resulted signal is nothing but the range profile of the target. The range resolution is determined by the Fourier theory as

Graph depicts profile of a point target is obtained with the help of SFCW radar processing.
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