ISAR sparse frequency band imaging method based on variation Bayesian learning algorithm

Abstract

The invention discloses an ISAR sparse frequency band imaging method based on a variation Bayesian learning algorithm. The ISAR sparse frequency band imaging method based on the variation Bayesian learning algorithm can mainly solve a problem of accurately solving the Bayesian model and realizes high definition imaging of an object under a low signal to noise ratio condition. The ISAR sparse frequency band imaging method comprises steps of 1) receiving ISAR echoes of high and low sub-frequency-bands and performing pre-processing, 2) performing azimuth compression and combination on a signal after pre-processing to obtain observation data, 3) generating a dictionary matrix corresponding to the observation data and using high and low sub-frequency-band distance Doppler images to perform pruning on the dictionary matrix, 4) solving a coefficient vector of an azimuth unit having the echo according to the observation data and the pruned dictionary matrix and reconstructing a full-frequency echo, and 5) performing distance compression on a reconstructed full-frequency-band echo to realize a high definition distance Doppler image. The ISAR sparse frequency band imaging method of the invention realizes high definition two-dimensional ISAR imaging which is good in focusing while reducing imaging complexity, and can be applied to feature extraction and identification of an object.

Description

technical field [0001] The invention belongs to the technical field of radar, and further relates to a sparse frequency band high-resolution two-dimensional ISAR imaging method, which can be used for object shape feature extraction and recognition. Background technique [0002] With the rapid development of Inverse Synthetic Aperture Radar (ISAR), although existing imaging radars can provide higher range resolution, higher resolution is required when observing space objects such as space debris, small satellites, and spacecraft. 2D radar imagery to accurately describe its features. Target Range - The range resolution of the Doppler image is determined by the bandwidth of the transmitted signal. There are two ways to obtain high-range resolution: one is to use ultra-wideband radar, but it has high requirements for hardware systems and requires high cost; the other is to use existing multiple radars in different frequency bands to detect The target is observed at the same ti...

AI Technical Summary

Problems solved by technology

However, this method uses the traditional spectral estimation method, which is sensitive to noise, and the performance of the algorithm depends on the accuracy of the model order estimation, and the model order is difficult to estimate accurately

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