Radar weak target detecting method based on information geometry multiple autoregressive model

An autoregressive model, weak target detection technology, applied in the field of radar, can solve the problems affecting radar detection performance, filter bank contamination filter bank, etc.

Inactive Publication Date: 2014-05-07
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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Problems solved by technology

[0005] (3) The low resolution of the filter bank and the sidebands of the Doppler filter lead to dense non-uniform ground / sea clutter propagation polluting the entire filter bank
[0006] Thus affecting the detection performance of the radar

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  • Radar weak target detecting method based on information geometry multiple autoregressive model
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  • Radar weak target detecting method based on information geometry multiple autoregressive model

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Embodiment Construction

[0068] The information geometry approach is a purely geometric approach, applying Hermitian positive definite matrix space geometry. It is not optimal to deal with the covariance matrix of symmetric positive definite Doppler signals with flat metric and normed space, because the set of symmetric positive definite matrices of flat metric is not a geodesic complete space. The symmetric positive definite matrix set of information geometry measure is geodesic complete, and the information geometry measure defined by Fisher information matrix fully considers the statistical properties of the matrix. The performance of radar weak target detection methods can be improved by replacing the Fourier transform with a new tool called the information geometry method.

[0069] A radar weak target detection method based on the information geometric complex autoregressive model, based on the definition of Karcher mean and geodesics, it solves the problem of the mean value estimation of N covar...

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Abstract

The invention discloses a radar weak target detecting method based on an information geometry multiple autoregressive model. According to the method, mean value estimation of N covariance matrixes is achieved based on the definition of the Karcher mean value and the geodesic line, the clutter environment around a covariance matrix unit to be detected is iterate-estimated by means of the gradient descent algorithm, the multiple autoregressive model is introduced, a parallel iterative algorithm is defined with a covariance matrix block structure to calculate Siegel measurement, the distinguishable distance between the covariance matrix unit to be detected and the clutter environment around is estimated, the detection threshold is estimated with the Monte-Carlo method, and weak target signals are distinguished from clutters. According to the method, Fourier transform is replaced with the information geometry method, and the problem of Doppler frequency resolution reduction is avoided; meanwhile, windowing does not needed to be conducted on data series, resolution limitation, energy leakage and pollution to a whole filter bank by the clutter spectrum are avoided, and correct and efficient detection of a radar weak target is achieved.

Description

technical field [0001] The invention relates to the radar field, in particular to a radar weak target detection method based on an information geometric complex autoregressive model. Background technique [0002] New requirements for radar target detection: (a) detection of low-altitude targets (small size, stealth, strong maneuverability, asymmetry, etc.); (b) improvement of reaction time for ultra-lethal threat targets. The radar Doppler & array signal processing method has reached its limit, and the traditional constant false alarm (CFAR) faces many shortcomings in the detection of weak targets in dense non-uniform clutter. Especially for the case of clutter transitions, the detection results are sub-optimal directly due to not preserving edges well and considering the statistical properties of clutter. Ridges or complex terrains in exposed areas (threats: missile-capable helicopters, low-altitude cruise missiles, drones, asymmetric threats, etc.) correspond to clutter t...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01S7/41
CPCG01S7/41G01S13/02
Inventor 皮亦鸣徐政五刘通李晋
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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