Clutter suppression method for airborne bistatic mimo radar based on sparse recovery

Abstract

The invention belongs to the field of double-base MIMO radar clutter rejection technologies, and particularly relates to an airborne double-base MIMO radar clutter rejection method based on sparse recovery. The airborne double-base MIMO radar clutter rejection method based on sparse recovery comprises the following steps that echo data, obtained after filtering, of each distance door are obtained through matched filtering; the amplitude of clutter in each receiving-transmitting-Doppler space is calculated through a sparse recovery method; a covariance matrix of each distance door and corresponding received data, except for transmitted waveforms, of each distance door are obtained; the corresponding received data, except for the transmitted waveforms, of each distance door are registered to obtain compensated data of the corresponding distance door; an optimal weight vector is obtained according to the compensated data of each distance door; weighting summation is carried out on the corresponding received data, except for the transmitted waveforms, of each distance door through the optimal weight vectors to obtain echo data generated after clutter rejection.

Description

technical field [0001] The invention belongs to the technical field of bistatic MIMO radar clutter suppression, in particular to an airborne bistatic MIMO radar clutter suppression method based on sparse restoration, which can be used for suppressing ground clutter and realizing detection of ground targets. Background technique [0002] Radar is an indispensable electronic equipment in modern military. Bistatic radar has the advantages of concealed detection, anti-jamming and anti-fading due to the separate structure of receiver and transmitter systems, and it is also conducive to the detection of stealth targets. But also because of this geometric structure, the distribution of the clutter power spectrum changes with the distance, showing the non-stationary characteristics of distance, that is, the clutter sampling data of different range gates do not satisfy the independent and identical distribution condition, that is, the clutter spectrum has distance dependence. Moreov...

AI Technical Summary

Problems solved by technology

The present invention only matches the data of each range gate through the method of sparse recovery, and directly recovers the covariance matrix of each range gate without solving the correlation, and then uses the registration method to solve the problem of distance dependence, and realizes the ground Real-time processing of object detection

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