Content area
In response to the problem of poor imaging quality caused by amplitude and phase errors in synthetic aperture imaging, this study develops an aperture radar-assisted technology based on an array of mathematical models and statistical characteristic calculations. Two error correction algorithms, active correction and iterative self-correction, are proposed by designing error correction algorithms based on the matrix space spectrum correction error concept. Simulation experiments showed that the mean square error of the two correction algorithms has decreased by an average of 36.23% compared to before correction, and the peak signal-to-noise ratio has increased by an average of 33.43% compared to before correction. Compared with other methods, the proposed two algorithms had an average increase of 139.51% in peak signal-to-noise ratio in two-dimensional imaging. The results indicate that it is feasible to use the traditional matrix space spectral correction method for comprehensive aperture imaging error correction. The designed error correction preprocessing algorithm based on an array of mathematical models and statistical characteristic calculations can improve imaging quality, reduce the impact of amplitude and phase errors, and has positive application value in synthetic aperture imaging technology.
Article highlights
Two new error correction algorithms are proposed to effectively reduce the amplitude and phase errors in SAR imaging;
A new signal processing framework is provided by introducing array mathematical models and statistical features;
The method is capable of significantly correcting imaging errors in 2D imaging with superior application potential.