Sea-surface small target detection method based on front-back revenue reference particle filter

Abstract

The present invention discloses a sea-surface small target detection method based on front-back revenue reference particle filter which mainly solves the problem that a conventional technology is not suitable for detecting the sea-surface low-speed floating small targets. The method comprises the realization steps of 1) obtaining and partitioning the echo data; 2) selecting a to-be-detected distance unit Sd in an echo data block and dividing the to-be-detected distance unit Sd into the to-be-detected sub-units; 3) calculating the instantaneous frequency curve function estimation of the to-be-detected distance unit Sd; 4) calculating a Doppler steering vector h and the covariance matrix estimation of the k-th to-be-detected sub-unit zk; 5) utilizing the h and the covariance matrix estimation to calculate the generalized likelihood ratio test statistic amount of the sub-unit zk; 6) accumulating the generalized likelihood ratio test statistic amount of all to-be-detected sub-units to obtain the test statistic amount xi k of the to-be-detected distance unit Sd; 7) calculating a detection threshold T xi; 8) comparing the xi k and the T xi to determine the existence of the targets. The sea-surface small target detection method of the present invention enables the radar detection performance to be improved, and can be used to detect the sea-surface floating small targets.

Description

technical field [0001] The invention belongs to the technical field of signal processing, and in particular relates to a small target detection method on the sea surface, which can be used for identifying and tracking small targets floating at low speed on the sea surface. Background technique [0002] When radar detects targets on the sea surface, it will be affected by sea clutter. The strength of sea clutter varies with radar parameters, sea conditions, etc. With the improvement of radar resolution, sea clutter presents strong non-Gaussian characteristics. A large number of researches have continuously improved the statistical model of sea clutter, and many adaptive detection methods have been proposed on this basis. This type of detection method models the sea clutter as a composite Gaussian model, which is the product of the texture component and the speckle component of the sea clutter. In the background of high-resolution sea clutter whose texture components obey th...

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Problems solved by technology

Proposed in the document "Hu, J., Tung, W.W. and Gao, J.B.: Detection of low observable targets within sea clutter by structure function based multifractal analysis, IEEE Trans. Antennas Propag., 54(1):136-143, 2006." The detection method based on the fractal characteristics of the sea surface can effectively detect the target when the observation time is long. However, the observation time required by this method to obtain good detection performance is generally more than 4 seconds. Radar usually cannot detect a single wave position for such a long time. resident observations, so the fractal-based detection method is difficult to be extended to practical applications

Literature P.L.Shui, D.C.Li and S.W.Xu, "Tri-feature-based detection of floating small targets in sea clutter," IEEE Trans.Aerosp.Electron.Syst., vol.50, no.2, pp.1416–1430, Apr. .2014. A detection method based on

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