Geometric Size Estimation Method of SAR Target Image Based on omp

Abstract

The invention discloses a synthetic aperture radar SAR target image geometric size estimation method based on the orthogonal matching pursuit algorithm OMP. The implementation steps are: (1) selecting the image slice matrix; (2) obtaining the target's atomic matrix and scattering center amplitude vector; (3) Obtain the reconstructed target image; (4) Project the reconstructed target image to the coordinate system to generate the target area; (5) Obtain the coordinate vector; (6) Rotate the coordinate vector; (7) Obtain the minimum circumscribed rectangle ; (8) Use the size value of the smallest circumscribed rectangle as the estimated value of the target geometric size. The invention is generally applicable to stationary radar observation targets. At the same time, the invention eliminates the negative impact caused by noise, has good noise robustness, and improves the estimation accuracy of the geometric size of the synthetic aperture radar SAR target.

Description

technical field [0001] The invention belongs to the technical field of communication, and further relates to a synthetic aperture radar SAR (Synthetic Aperture Radar) target image geometric size estimation method based on an orthogonal matching pursuit algorithm OMP in the technical field of radar target feature extraction. The invention can be used to extract the outer contour of a stationary target in a single image received by radar, and use the extracted contour to estimate the geometric size of the stationary target. Background technique [0002] The geometric size feature of the target is an intuitive physical feature of the radar target. For high-resolution radar image target slices, estimating the geometric size of stationary targets has important application significance in the process of SAR image target identification and classification. For the size estimation of high-resolution radar image targets, the actual high-resolution radar image data are generally affect...

AI Technical Summary

Problems solved by technology

However, the disadvantage of this method is that it needs to know the motion model of the target, which is not suitable for stationary targets, so this method cannot be generally applied

The disadvantage of this method is that since the method directly separates the target from the background according to the set threshold when performing target screening, it cannot eliminate the influence of noise on the estimation of the target geometric size, and it is not robust to noise.

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