A method and system for intelligent processing of complex dynamic multi-target micro-motion signals

Abstract

The invention discloses a method and device for intelligently processing complex dynamic multi-target micro-motion signals. The steps of the method include: S1. Obtaining radar echoes for multi-target detection and converting them into two-dimensional time-frequency images; S2. The multi-modal micro-motion curves of multiple targets in the image are separated at the target level, and each single-target micro-motion curve is separated; S3. Decoupling the micro-motion signals of each mode contained in each single-target micro-motion curve, and decomposing to obtain Micro-motion signals of each mode; S4. Extract micro-motion features from the decomposed micro-motion signals of each mode, and use a pre-trained classifier based on a deep learning neural network model to identify the extracted micro-motion features. The invention has the advantages of simple implementation method, the ability to realize the extraction and classification recognition of dynamic multi-target micro-movement features, and the classification recognition accuracy is high, the robustness is good, and the like.

Description

technical field [0001] The invention relates to the technical field of radar target characteristic detection, in particular to an intelligent processing method and system for complex dynamic multi-target micro-motion signals. Background technique [0002] The radar micro-Doppler effect refers to the additional frequency modulation of the echo signal by the target fretting. The micro-movement of the target includes the precession and nutation of the target, as well as the rotation and swing of the target structural components. As an important target feature, micro-motion feature has high military and civilian value in the field of radar target detection and target recognition, and can effectively extract the motion characteristics and structural features of ground targets and air targets. With the improvement of the resolution of ISAR (Inverse Synthetic Aperture) radar, the extraction and refined interpretation of target micro-motion features using Doppler radar has become a...

AI Technical Summary

Problems solved by technology

For the characteristics of micro-moving targets, at present, the deep learning network method is usually used directly to identify specific single target features, and the micro-Doppler information generated by dynamic multi-targets will cause serious aliasing within the analysis bandwidth. A single deep learning network method to achieve dynamic multi-target micro-motion signal classification is not only complicated to implement, but also has low classification accuracy and poor robustness, especially in the background of strong noise. The recognition rate will drop rapidly

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