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LPI radar signal detection method based on CNN

A detection method and radar signal technology, applied in neural learning methods, radio wave measurement systems, instruments, etc., can solve problems such as difficulty in perceiving and acquiring LPI radar signals, and algorithm performance degradation, and achieve good application prospects.

Active Publication Date: 2021-02-02
HARBIN ENG UNIV
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Problems solved by technology

Since the low probability of interception radar has outstanding advantages such as low peak power, large time-width bandwidth product, etc., and mostly uses complex signal modulation methods, it is difficult for non-partner radar interception receivers to perceive and acquire LPI radar signals, so that traditional signal detection algorithms Performance drop

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  • LPI radar signal detection method based on CNN
  • LPI radar signal detection method based on CNN
  • LPI radar signal detection method based on CNN

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Embodiment Construction

[0017] The specific embodiments of the present invention will be further described below in conjunction with the accompanying drawings.

[0018] The present invention proposes a signal detection method based on deep learning CNN, which uses CNN for signal detection, transforms the signal detection problem into a CNN-based feature extraction problem, samples the intercepted radar signal pulses, and converts the sampled discrete signal The in-phase component and quadrature component of the neural network can be directly input into the neural network, and high-accuracy signal detection within a certain error range can be realized. The present invention modifies the network structure that has been successfully used in image recognition to make it suitable for the sampling sequence of LPI radar signals. The ability to perform deep learning, extract features, and complete signal detection.

[0019] The technical solution of this invention is a CNN-based signal detection method and ...

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Abstract

The invention discloses an LPI radar signal detection method based on a CNN, and the method comprises the steps: carrying out signal detection through the CNN, converting a signal detection problem into a feature extraction problem based on the CNN, carrying out the sampling of intercepted radar signal pulses, directly inputting an in-phase component and an orthogonal component of a sampled discrete signal into a neural network, and realizing high-accuracy signal detection within a certain error range. According to the invention, the method has a generalization capability for LPI radar signaldetection under different SNRs; due to randomness of parameters such as signal bandwidth and carrier frequency, generalization of a test set can be ensured, which indicates that the method has certaingeneralization capability for untrained signals and has good application prospect.

Description

technical field [0001] The present invention relates to a method for detecting LPI radar signals, in particular to a method for detecting LPI radar signals based on CNN, belonging to non-cooperative detection algorithms for LPI radar signals. Background technique [0002] Low Probability of Intercept (LPI) radar signals are widely used due to their excellent concealment and anti-interference performance. In the face of complex electromagnetic environments, the analysis of LPI radar interception will also become an important content of electronic countermeasures. Traditional signal detection algorithms mainly include: time-domain energy detection method, frequency-domain energy detection method, signal detection method based on wavelet transform to remove noise, signal correlation detection method, etc. Since the low probability of interception radar has outstanding advantages such as low peak power, large time-width bandwidth product, etc., and mostly uses complex signal mod...

Claims

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Application Information

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IPC IPC(8): G01S7/285G01S7/292G06N3/04G06N3/08
CPCG01S7/285G01S7/292G06N3/08G06N3/045
Inventor 蒋伊琳尹子茹赵忠凯陈涛郭立民刘鲁涛
Owner HARBIN ENG UNIV
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