Method for imaging actual aperture foresight on basis of subspace projection

Abstract

The invention discloses a method for imaging an actual aperture foresight on basis of subspace projection, which mainly solves the high resolution imaging problem of a right ahead object of a flightpath. The method has the detection processes that: 1) radar beams are sent out at equal intervals for carrying out sequence overlap scanning on a ground monitoring area to obtain the radar return data; 2) a modular arithmetic is utilized to extract the intensity vector of the return data; 3) the autocorrelation matrix of the intensity vector of the return data is gained; 4) eigen decomposition is carried out on the autocorrelation matrix; 5) the corresponding eigenvector of a small eigenvalue is used for forming a noise subspace; 6) a pattern search vector is defined; 7) the pattern search vector is projected into the noise subspace; 8) the peak values of a spatial spectrum function are calculated; and 9) the number of the signal is determined according to the number of the peak values of the spatial spectrum function for realizing foresight imaging. The method has the advantage of improving the resolution precision of an adjacent target in a main lobe, and can be used for an airborne radar monitoring system in the imaging field for realizing the detection and the recognition for a target on a track line.

Description

technical field [0001] The invention relates to the field of imaging, in particular to the problem of high-resolution imaging of a target directly in front of a flight track, which can be used in an airborne radar monitoring system to detect and identify targets along the direction of the flight track. Background technique [0002] In the ever-changing modern high-tech warfare environment in the future, battlefield information is complex and changeable, and fighters are fleeting. Timely and correct battlefield detection and tactical reconnaissance are related to the success or failure of the war. Therefore, it is necessary to require the radar imaging system to have a certain imaging accuracy and imaging range. However, when the antenna beam is close to coincident with the track line, since the ground targets distributed on both sides of the track have the same Doppler history, aliasing is likely to occur, and the Doppler change rate of the target is very small, the azimuth ...

AI Technical Summary

Problems solved by technology

Although monopulse angle measurement has high measurement accuracy in theory, in practical applications, there are often the following limitations: when a complex-shaped target moves relative to the radar, it will cause the deviation between the apparent center of the target and the actual center of the target, Angular flicker phenomenon occurs, which restricts the imaging quality; the single-pulse forward-looking imaging technology cannot measure the angles of different scattering centers in the same range unit, and can only obtain the positions of equivalent scattering points, which reduces the accuracy of angle measurement; when the same beam memory When there are many targets, the angle measurement accuracy will drop sharply and even the position of the target cannot be detected accurately, especially when there are two or more targets with similar energy in the beam azimuth range within a certain distance unit, the angle measurement accuracy is especially Low; in monopulse forward-looking imaging, each angle-measuring coordinate plane usually uses two independent receiving branches, namely two branches in the azimuth plane and two branches in the elevation plane, and the system is complex

However, there are also certain problems in the deconvolution process: single-channel deconvolution is prone to produce ill-conditioned solutions, and the algorithm requires a high signal-to-noise ratio. When the signal-to-noise ratio is less than 30dB, the target resolution effect is poor; To reduce the influence of ill-conditioned effects, Berenstein et al. developed multi-channel deconvolution technology for information reconstruction of linear shift invariant systems, which can transform part of the deconvolution problem into a good state, but not all convolution sets Satisfy the strong coprime condition. When the multi-channel cannot satisfy the strong coprime condition, the signal-to-noise ratio will still be greatly reduced after deconvolution. Therefore, the use of multi-channel deconvolution technology also has great limitations.

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