Micro-motion target parameter estimation method based on matrix correlation

Abstract

The invention relates to a micro-motion target parameter estimation method based on matrix correlation. The method comprises steps that 1, a one-dimensional distance image is acquired; 2, a time-distance distribution matrix is constructed through continuous observation; 3, an autocorrelation matrix of the time-distance distribution matrix is calculated; 4, autocorrelation matrix peak value extraction is carried out; 5, micro-motion period estimation is carried out; and 6, an average value is solved through continuous observation. The method is advantaged in that one-dimensional correlation is generalized to be two-dimensional correlation, micro-motion period estimation is more stable and reliable, and the method is simple and practical; micro-motion period estimation has no false component, and influence of a signal to noise ratio is relatively small; and the method is suitable for micro motion targets such as spinning, procession, swinging and nutation.

Description

technical field [0001] The invention belongs to the field of radar signal processing, and in particular relates to a method for estimating parameters of a micro-moving target based on matrix correlation—a method for obtaining the micro-movement period of a micro-moving target based on matrix theory and micro-motion theory. Background technique [0002] The space target maintains stability through spin stabilization. Due to external interference, it may precess, while for an uncontrolled target, it will swing or roll. The difference between the two micro-motion modes can effectively distinguish the target. The micro-motion feature is considered to be an effective feature in space target recognition, and the micro-motion feature of the target can be estimated by both narrow-band radar and wide-band radar signal processing methods. The fast Fourier transform processing of the narrowband radar target echo sequence has false frequency components, and the estimation result fluctua...

AI Technical Summary

Problems solved by technology

The fast Fourier transform processing of the narrowband radar target echo sequence has false frequency components, and the estimation result fluctuates greatly; the time-frequency analysis of the narrowband echo sequence can obtain the time-frequency distribution, which can be obtained by extending the Hough transform and other methods. The period of the standard sinusoidal FM signal is obtained, but for the space micro-movement target, the echo signal is often a non-sinusoidal FM signal, and the Hough transform method has difficulties such as high parameter space dimension and large amount of calculation.

[0003] Broadband radar has high resolution capability and can obtain the one-dimensional range image of the target. The length of the one-dimensional range image of the micro-moving target will also change periodically, and the target can also be obtained by performing fast Fourier transform processing on the length of the one-dimensional range image. fretting period, but there are also false components, and are greatly affected by the signal-to-noise ratio

Wang Qi et al. proposed a single one-dimensional range image correlation The fretting period estimation method based on the above method can obtain high estimation accuracy under high signal-to-noise ratio conditions, but when the signal-to-noise ratio is low and the target characteristics fluctuate, the parameter estimation is unstable

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