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Information entropy-based multi-radar hybrid detection method

A detection method and information entropy technology are applied in the field of multi-radar hybrid detection based on information entropy, which can solve the problems of different echo SNRs, affecting detection efficiency, and performance deterioration of square-law detectors, so as to improve detection performance and improve detection results. Effect

Active Publication Date: 2017-02-22
INFORMATION SCI RES INST OF CETC
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Problems solved by technology

However, the echo SNR of each channel will be different under the influence of factors such as different scattering cross-sectional areas of targets and different distances between radars and targets.
When the SNR variance of each channel is large, the performance of the square law detector will deteriorate, thus affecting the detection efficiency

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  • Information entropy-based multi-radar hybrid detection method

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Embodiment Construction

[0034] The specific implementation manners of the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0035] In the multi-radar hybrid detection method based on information entropy proposed by the present invention, the multi-channel echo signals are respectively subjected to square law detection and information entropy detection, and the output detection results are judged whether there is a target through the "or" judgment criterion. When the square law detection or When the information entropy detects the target, the judgment result is that the target exists, so that the target can be detected well under the SNR difference of different channels.

[0036] For the convenience of description, the multi-radar binary hypothesis testing model is set as follows in this impleme...

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Abstract

The invention discloses an information entropy-based multi-radar hybrid detection method. The method includes the following steps that: S1, square-law detection is performed on multi-channel echoes formed by a plurality of radars, so that post-detection signals can be obtained; S2, square-law detection is performed according to the post-detection signals, so that a first detection result can be obtained, information entropy detection is performed on the post-detection signals, so that a second detection result can be obtained; and S3, whether a target exists is judged based on the first detection result and the second detection result. According to the information entropy-based multi-radar hybrid detection method of the invention, the information entropy detection and the square-law detection are combined together, and therefore, targets can be well detected under the SNR (signal noise ratio) differences of different channels, and multi-radar target detection performance can be greatly improved.

Description

technical field [0001] The invention relates to the technical field of radar signal processing, in particular to an information entropy-based multi-radar hybrid detection method. Background technique [0002] Multi-radar detection is the use of multiple radars distributed in space. Each radar not only receives the echoes of its own transmitted signals, but also receives the echoes of other radar transmitted signals, so as to obtain target echo signals independent of each other in different directions to suppress the radar target space. Instability of detection performance caused by fluctuations. [0003] In multi-radar detection, a commonly used detection method is the square-law detection method. When the signal-to-noise ratio (SNR) of each channel is the same, the square-law non-coherent accumulation detector has the best detection effect. However, the echo SNR of each channel will be different under the influence of factors such as different scattering cross-sectional ar...

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Application Information

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IPC IPC(8): G01S7/41G01S7/36
CPCG01S7/36G01S7/41
Inventor 葛建军李春霞
Owner INFORMATION SCI RES INST OF CETC
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