ISAR high resolution imaging method based on maximum mutual information criterion

Abstract

The invention discloses an ISAR high resolution imaging method based on maximum mutual information criterion to mainly solve the problem about high resolution ISAR imaging for a target under clutter and noise. According to the technical scheme, the method comprises the following steps that environment and target information is obtained; optimal transmitting waveform energy spectrum are solved based on the maximum mutual information criterion; imaging signal are modulated based on the energy spectrum; optimized waveform are transmitted and echo thereof are recorded; a distance dictionary is constructed according to the optimized waveform, and optimized waveform echo signal waveform is subjected to the variational bayesian algorithm to reconstruct a range image matrix; and an azimuth dictionary is constructed, and the range image matrix is subjected to the variational bayesian algorithm for reconsitution to obtain targeted high resolution two-dimensional imaging results with excellent focusing effect. Suppression of clutter and noise under clutter and noise is achieved. Targeted and optimized waveform echo mutual information is improved. High resolution two-dimension ISAR imaging results of the target are obtained and are used for target feature extraction and recognition.

Description

technical field [0001] The invention belongs to the technical field of radar, and further relates to ISAR imaging and waveform optimization, in particular to an ISAR high-resolution imaging method based on the maximum mutual information criterion, which can be used for high-resolution imaging of space targets in complex electromagnetic environments. Background technique [0002] Under the condition of high signal-to-noise ratio, the existing inverse synthetic aperture radar (ISAR) can obtain well-focused images, but when the electromagnetic environment is complex, it is difficult to achieve high-resolution imaging of space targets. The traditional radar system has a fixed transmission waveform, and does not use the environment and target information to optimize the design of the transmission waveform, which limits the imaging performance of the radar to the target in environments such as clutter and interference. Cognitive Inverse Synthetic Aperture Radar (Cognitive ISAR) ca...

AI Technical Summary

Problems solved by technology

Bell first proposed the wave design method of the maximum output signal-to-noise ratio criterion under the noise background, which designed the launch waveform through the eigenvalue decomposition method of the target and noise covariance matrix, and the eigenvector corresponding to the maximum eigenvalue of the covariance matrix is ​​the launch waveform. The basic form, and then Pillai et al. proposed the maximum output signal (clutter) noise ratio waveform design method under the clutter background, which uses the relationship between the transmit waveform and the output signal (clutter) noise ratio of the matched filter, and solves the transmit waveform through an iterative algorithm , but the process of this method is complex, and the amount of calculation is huge, and the side lobe of the optimized transmission waveform is higher than that of the unoptimized transmission waveform, which leads to defocusing of the range image after the range pulse compression and reduces the quality of two-dimensional imaging

[0005] In summary, the waveform optimization design algorithm based on cognitive inverse synthetic aperture radar can improve the suppression performance of noise and clutter, but the waveform optimization method based on ambiguity functions cannot suppress clutter; the waveform optimization design based on the maximum signal-to-noise ratio criterion The algorithm can suppress clutter and noise, but it is relatively complicated. The optimized waveform is generally only suitable for target tracking and detection. For imaging tasks, the high sidelobe of the optimized waveform will reduce the imaging quality

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