A Scanning Radar Forward-Look Imaging Method Based on Spatial Embedded Mapping

Abstract

The invention discloses a scanning radar forward-looking imaging method based on spatial embedded mapping. Specifically, on the basis of echo range pulse compression and range walking correction, the problem of improving azimuth resolution is transformed into a matrix solution problem; Value decomposition theory, analyze the singular value distribution of the antenna measurement matrix, determine the order of the space embedding matrix and generate the space embedding matrix under the premise of retaining the information of the antenna measurement matrix to the greatest extent; use the space embedding matrix to extract the information of the antenna measurement matrix, Reconstruct the antenna measurement matrix and the echo signal, reduce the order of the matrix, increase the uncorrelated characteristics of the matrix, and improve the ill-conditionedness of the antenna measurement matrix; according to the data model of the spatial embedding mapping, reduce the order of the antenna measurement matrix, thereby reducing the complexity of the operation degree; use the principle of least squares to solve the scattering coefficient of the target, and realize high-resolution and fast imaging of the target azimuth.

Description

technical field [0001] The invention belongs to the technical field of radar imaging, in particular to a scanning radar forward-looking high-resolution imaging method. Background technique [0002] Radar forward-looking area imaging is of great significance to target detection, target strike, and material delivery. Due to the limitations of the imaging principle, the traditional synthetic aperture radar cannot realize the imaging of the radar's forward-looking area. At present, the real-aperture radar is mainly used to realize the imaging of the forward-looking area. However, the azimuth resolution of real-aperture radar is θ∝λ / D. To achieve higher azimuth resolution requires increasing the size of the radar antenna, which cannot be achieved in application scenarios with limited size such as airborne. Therefore, signal processing means are used to improve the azimuth resolution and achieve high resolution of forward-looking azimuth. [0003] Tikhonov proposed a regularizat...

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Problems solved by technology

Using the above algorithm, although the azimuth resolution can be improved, the above algorithm has high computational complexity, long calculation time, and large resource consumption.

Although the literature "Y. Zhang, Y. Zhang, W. Li, Y. Huang and J. Yang, Divide and conquer: A fast matrix inverse method of iterative adaptive approach for real beam superresolution, 2014 IEEE Geoscience and Remote Sensing Symposium, Quebec City, QC , 2014, pp.698-701.doi:10.1109 / IGARSS.2014.6946519" proposed a fast iterative adaptive deconvolution algorithm to improve computational efficiency, but the algorithm still requires a long computational time, especially in the processing of far When the distance is large and the scene is large, the calculation takes longer and consumes more resources, which is difficult to meet the application requirements.

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