现代雷达2025，Vol.47Issue(10)：116-124,9.DOI:10.16592/j.cnki.1004-7859.2025061601
基于ECNN的进动锥体目标微动周期估计方法
A Method of Estimating the Micro-motion Period for Space Cone-shaped Target with Precessing Based on ECNN
摘要
Abstract
Micro-motion features are regarded as critical characteristics of space targets,providing essential references for target classification and identification.However,traditional micro-motion feature extraction methods rely on complicated signal processing techniques,which are computationally intensive and exhibit limited robustness,particularly for composite micro-motions such as precession.To address these challenges,a precision period estimation method for conical space targets(with and without empen-nages)based on an enhanced convolutional neural network(ECNN)is proposed in this paper.Time-frequency representation of narrowband radar echoes are utilized to accurately estimate the micro-motion periods in the proposed method.Notably,reliable es-timation results are achieved even under low signal-to-noise ratio(SNR)conditions.The feasibility and robustness of the proposed method are validated by the simulation experiments.关键词
空间目标/改进卷积神经网络/微动周期/参数估计Key words
space target/enhanced convolutional neural network/micro-motion period/parameter estimation分类
电子信息工程引用本文复制引用
王天润,李开明,苏令华,王聃,罗迎..基于ECNN的进动锥体目标微动周期估计方法[J].现代雷达,2025,47(10):116-124,9.基金项目
国家自然科学基金资助项目(62371468,61971434,62131020,61871396) （62371468,61971434,62131020,61871396）
