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Knowledge-aided Adaptive Fusion Detection Method Based on Geometric Mean Estimation

A geometric mean, knowledge-assisted technology, applied in radio wave measurement systems, instruments, etc., can solve the problems of unsatisfied assumptions and damage to the uniformity of the clutter covariance matrix structure, so as to improve the target detection performance, enhance the detection ability, The effect of improving adaptability

Active Publication Date: 2022-04-01
NAVAL AVIATION UNIV
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  • Application Information

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Problems solved by technology

In the aforementioned two clutter models, it is assumed that the clutter components have the same covariance matrix structure. The uniformity of the clutter covariance matrix structure among distance units will be further destroyed, and the assumption that the clutter components in the uniform, partially uniform and non-Gaussian clutter models have the same covariance matrix structure will not be satisfied

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  • Knowledge-aided Adaptive Fusion Detection Method Based on Geometric Mean Estimation
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  • Knowledge-aided Adaptive Fusion Detection Method Based on Geometric Mean Estimation

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Embodiment 1

[0044] Refer to the attached figure 1 , the specific implementation of embodiment 1 is divided into the following steps:

[0045] Step A1 uses the ground detection radar to irradiate the target-free range around the area to be detected, and obtain the complex amplitude of the echoes of the range units adjacent to the range unit to be detected that do not contain the target, and form K ground clutter-only Auxiliary data y k (k=1,2,...K), the auxiliary data is sent to the intermediate matrix calculation module (1); in the intermediate matrix calculation module (1), the matrix R is calculated according to formula (3) k (k=1,2,…K), and the matrix R k (k=1,2,...K) is sent to the geometric mean estimation module (2) of the clutter covariance matrix structure probability density function; in the geometric mean estimation module (2) of the clutter covariance matrix structure probability density function, Calculate the geometric mean estimate of the probability density function of t...

Embodiment 2

[0051] Refer to the attached figure 1 , the specific implementation of embodiment 2 is divided into the following steps:

[0052] Step B1 uses the sea detection radar to irradiate the target-free range around the sea area to be detected, and obtain the echo complex amplitude of the range unit adjacent to the range unit to be detected that does not contain the target, and forms K distance units containing only pure sea clutter. Auxiliary data y k (k=1,2,...K), the auxiliary data is sent to the intermediate matrix calculation module (1); in the intermediate matrix calculation module (1), the matrix R is calculated according to formula (3) k (k=1,2,…K), and the matrix R k (k=1,2,...K) is sent to the geometric mean estimation module (2) of the clutter covariance matrix structure probability density function; in the geometric mean estimation module (2) of the clutter covariance matrix structure probability density function, Calculate the geometric mean estimate of the probabilit...

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Abstract

The invention discloses a knowledge-assisted adaptive fusion detection method based on geometric mean estimation, which belongs to the field of radar signal processing. Aiming at the non-uniform structure of the clutter covariance matrix between different distance units in the actual heterogeneous clutter environment, a reasonable prior distribution that is easy to handle mathematically is constructed, and the clutter prior information and the heterogeneous clutter information contained in the auxiliary data are efficiently combined. Fusion, constructing a geometric mean estimation method of the probability density function of the heterogeneous clutter covariance matrix structure that is easy to handle mathematically, and then constructing a closed-form point target knowledge-assisted adaptive fusion detector, which improves the traditional narrowband radar's ability to detect heterogeneous clutter The ability to adapt to the environment improves the target detection performance under heterogeneous clutter, and improves the detection ability of narrowband radars for weak and small targets in complex electromagnetic environments, which has the value of popularization and application.

Description

technical field [0001] The invention belongs to the field of radar signal processing, and in particular relates to a knowledge-assisted self-adaptive fusion detection method based on geometric mean estimation. Background technique [0002] Narrowband radar point target adaptive detection is affected by various factors such as the complex and changeable natural environment of the target, electromagnetic interference, etc., and the statistical characteristics of clutter no longer meet the independent and identically distributed uniform environment assumptions, making it difficult for existing point target detection methods to achieve ideal results. Detection effect. Existing clutter models mainly include uniform environment, partially uniform environment, non-Gaussian clutter environment, and heterogeneous clutter environment. Among them, in a partially homogeneous environment, it is assumed that the clutter components in the range unit data to be detected (also called main d...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01S7/41
CPCG01S7/414
Inventor 简涛王海鹏张杨何友李刚李恒刘传辉沈剑王哲昊
Owner NAVAL AVIATION UNIV