SAR (Synthetic Aperture Radar) imaging method based on weighted sparsity bayesian recovery via iterative minimum algorithm
A sparse Bayesian and reconstruction algorithm technology, applied in the field of radar and synthetic aperture radar imaging, can solve problems such as difficult to improve, influence, resolution limitation, etc.
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 The present invention mainly adopts the method of computer simulation for verification, and all steps and conclusions are verified correctly on MATLAB-R2014b. The specific implementation steps are as follows:
 Step 1. Initialize SAR system parameters:
 The initial SAR system parameters include: the platform velocity vector is recorded as The initial position vector of each element of the linear array antenna, denoted as Among them, n is the serial number of each array element of the antenna, which is a natural number, n=1,2,...,N, N=4096 is the total number of array elements of the linear array antenna, and the length of the linear array antenna is recorded as L=3m; Frequency f c =30GHz; the frequency modulation slope f of the radar transmitting signal dr =3×10 14 Hz / s; the pulse repetition time is recorded as PRI=2ms; the pulse repetition frequency of the radar system PRF=500Hz; the bandwidth of the radar emission signal B r =1.5=10 8 Hz, the p...
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