Adaptive detection method for distance expanded object based on variable-element generalized structure

Abstract

The invention discloses an adaptive detection method for a distance expanded object based on a variable-element generalized structure, belongs to the field of radar signal processing. Aimed at solving the problem that a covariance matrix estimation method and an adaptive distance expansion detector are hard to adapt to a transitional clutter environment, clutter non-Gaussian characteristic information is utilized reasonably, a unified covariance matrix fusion estimation framework is constructed, an adaptive detector of the distance expanded object is constructed in a product fusion form on the basis of general characteristics of detection statistics of present optimal distance expanded objects in the specific clutter environment, a single parameter is utilized to realize design of the detector for the distance expanded object in the transitional clutter environment as well as synchronous control of the corresponding clutter covariance matrix estimation method, the detector structure matches the corresponding clutter covariance matrix estimation method, parameters are set in a concise manner, the detection performance of a broadband radar in the complex clutter environment is improved effectively, and the popularization and application values are high.

Description

technical field [0001] The invention belongs to the field of radar signal processing, and in particular relates to an adaptive detection method for a distance-extended target based on a variable-parameter generalized structure. Background technique [0002] Compared with traditional low-resolution narrowband radar, wideband radar has larger bandwidth and higher distance resolution, and has obvious advantages in anti-jamming, anti-reconnaissance, precise detection and imaging, high-precision tracking, and target recognition. It has gained wide attention and application in modern military and civilian fields, and has become an important direction of modern radar development. Due to the low range resolution of traditional narrow-band radar, its range resolution unit is much larger than the geometric size of common targets. The target echo signal only occupies one range resolution unit, and the actual target is often treated as a "point target". Different from the "point target...

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Problems solved by technology

[0005] The current sampling covariance matrix estimation method only considers the Gaussian clutter background, and the normalized sampling covariance matrix or approximate maximum likelihood estimation method also only considers the composite Gaussian background. detection problem, these covariance matrix estimation methods only consider a single specific case of Gaussian or compound Gaussian, and the sampling covariance matrix estimation method only matches the generalized adaptive matched filter in the Gaussian background, while the normalized sampling The covariance matrix or approximate maximum likelihood estimation methods are only compatible with the generalized adaptive accumulation detector in the compound Gaussian background, that is, the existing covariance matrix estimation methods and adaptive range extension detectors are difficult to adapt to the transitional clutter environment. features

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