A Reconstruction Method of Micro-Motion TFR Based on Adaptive Parameter Estimation
LI Kaiming
WANG Huan
XIE Yan
CHEN Zhuo
GAO Zeyue
Abstract：In view of the time-frequency representation(TFR)reconstruction of the micro-motion signals under conditions of incomplete data,a reconstruction method of micro-motion is proposed based on the adaptive parame-ter estimation.Firstly,the missing micro-motion TFR reconstruction problem is modeled on the Lp norm minimi-zation sparse reconstruction problem,and by introducing Hadamard product parameter(HPP),the Lp norm min-imization sparse reconstruction problem is transferred to a joint minimization problem with multiple L2 norm,and solved by using iterative Tikhonov regularization.Simultaneously,the regularization parameter is estimated adap-tively in each iteration based on reconstruction results.Finally,the amplitude decay of the reconstructed TFR is reduced by the de-biasing process.Compared with the traditional micro-motion echo time-frequency representation reconstruction method,the proposed method avoids the disadvantage of setting the regularization parameter manu-ally,and the reconstructed TFR is more complete.The effectiveness and robustness of the proposed method is verified by simulation and measured data processing.
Keywords：micro-Doppler effectsignal reconstructionsparse optimizationparameter estimationtime-frequency analysis
Publication Date：2024-10-25
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：8( 107-114 )