Coherent detection method under complex Gaussian model based on inverse gamma texture

Abstract

The invention belongs to the radar target detection technology field and discloses a coherent detection method under a complex Gaussian model based on an inverse gamma texture. By using the method, adaptive detection of a target under an uniform sea clutter background can be realized and detection performance is increased. The method comprises the following steps that a radar emits a pulse signal through a radar transmitter and receives an echo signal through a radar receiver; according to echo data, an observation vector of a detection unit and an observation vector of a reference unit are constructed; according to the observation vector of the detection unit and the observation vector of the reference unit in the echo data, a generalized likelihood ratio detector is constructed; a parameter in the generalized likelihood ratio detector is estimated so as to obtain an optimal coherent detector; according to a preset false alarm probability, a detection threshold is calculated; according to the detection threshold, the optimal coherent detector is used to detect a target.

Description

technical field [0001] The invention belongs to the technical field of radar target detection, and in particular relates to a coherent detection method based on an inverse gamma texture compound Gaussian model, which can be used for target detection under the background of sea clutter. Background technique [0002] When the high-resolution radar works at a small grazing angle, the sea clutter shows strong non-Gaussian characteristics, and the composite Gaussian model can be used to simulate the sea clutter. The composite Gaussian model uses the product of two independent processes to describe sea clutter: one process is called texture component or slowly varying component, which is a non-negative random variable; the other process is called speckle component or rapidly varying component, which is Complex Gaussian process with zero mean. Under the composite Gaussian model, when the texture component of the clutter obeys the gamma distribution, the corresponding sea clutter a...

AI Technical Summary

Problems solved by technology

[0005] The premise of the above optimal detection method is to assume that the detection unit and the reference unit have independent and identically distributed texture components. In the background of uniform clutter (texture components are completely correlated), this detector is no longer optimal

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