| The vibration,rotation and other small amplitude motions of a target or its components except for the translational motion of the main body are called “micro-motion”.Micro-motion possesses motion attributes unique to the target,which can reflect the fine characteristics of target motion.Therefore,micro-motion features can provide a sound basis for radar target recognition,and has a wide range of applications in both military and civil fields.In terms of military use,the recognition technology based on micro-motion feature extraction is key to the missile defense system.The difference in mass distribution between the warhead and decoy gives rise to their markedly different micro-motion features.This contributes to distinguishing true warheads from false ones by extracting the micro-motion features of targets.Regarding civil use,radar has numerous advantages such as all-day,all-weather,strong penetration ability and long-distance detection.It can emit electromagnetic wave to detect micro-motion features of the human body,thereby realizing the non-contact life signal detection,which is of vital use in natural disaster rescue,medical and health-care fields.Based on the above background,this paper conducts a systematic research on the application of micro-motion feature extraction and parameter estimation in military and civil use.The main contents can be summarized as the following five aspects:(1)The scattering center micro-motion model of the cone ballistic target,and the human respiration and heartbeat micro-motion model are establishedIn this paper,the application of micro-motion in the military field mainly focuses on the cone ballistic target.Based on the general scattering center model and the equivalent scattering center model,the micro-motion features of ballistic target in spin,precession and nutation states are analyzed.Then the expression of wideband echo of the cone ballistic target is obtained and verified by simulation experiment.The application of micro-motion for civil use in this paper concentrates on the human respiration and heartbeat micro-motion target.Based on the movement mechanism of respiration and heartbeat process,the model of human respiration and heartbeat micro-motion is established,and the wideband echo expression of the chest is derived.The micro-motion target model established in this part lays the foundation for the following research work.(2)Micro-motion feature extraction and parameter estimation of a single ballistic target based on phase-derived rangeAiming at the problem of low resolution of micro-motion parameter extraction based on high-resolution range profile(HRRP)envelope information,a method of micro-motion feature extraction and parameter estimation based on phase-derived range is proposed.According to the scattering center micro-motion model of the cone ballistic target,the envelope information and phase information of HRRP sequence of the ballistic target wideband echo is analyzed respectively.Limited by the range resolution of radar,the envelope information will result in reduced accuracy of micro range measurement.In contrast,the employment of phase information in ranging based on the principle of phase-derived range can increase the estimation accuracy to the level of half a wavelength.On this basis,a method of micro-motion parameter estimation of the ballistic target based on phase-derived range is proposed,and the effectiveness of the algorithm is verified by simulation experiments.(3)Micro-motion multi-target resolution and feature extractionTo address the problem that most traditional micro-Doppler feature extraction technologies can hardly achieve multi-target resolution,a novel curve overlap extrapolation algorithm for wide-band resolution of the micro-motion multi-target is proposed.For the micro-motion multi-target model,the micro-motion curves of each scattering center will overlap,which brings inconvenience to the subsequent micro-motion feature extraction and multi-target resolution.According to the relative distance between filtering data points and the historical slope information of each curve,the point trace behind the overlapping location can be extrapolated to realize the data association of micro-motion curves for each signal component.Consequently,the multi-target resolution can be performed by analyzing the difference in micro-motion characteristics between each curve.(4)2-D joint sparse reconstruction and micro-motion parameter estimation for ballistic target based on compressive sensingAiming at the problem of micro-motion feature extraction of the cone ballistic target in the sparse frequency band signal system,a 2-D joint sparse reconstruction and micro-motion parameter estimation method based on the compressed sensing(CS)theory is proposed.For the 2-D joint sparse reconstruction signal model,combining the CS theory with the strong anti-jamming ability and low computational complexity of the sparse frequency band signal,a micro-motion feature parameter dictionary of ballistic target is established,and the optimization function of 2-D joint sparse reconstruction and micro-motion parameter estimation is generated.The optimization function is solved by the improved orthogonal matching pursuit(OMP)algorithm,thereby realizing the micro-motion parameter estimation and sparse reconstruction simultaneously.The proposed algorithm makes the most of the coupling information and coherent accumulation between 2-D data,so as to obtain high-precision HRRP and micro motion curves of the ballistic target.(5)3-D trajectory reconstruction and parameter estimation of the micro motion target In order to solve the problem of coordinate distortion when using three-dimensional interferometry to extract target trajectory under squint condition,a method of micro-motion trajectory extraction and parameter estimation in squint correction interferometry is proposed.According to the three-dimensional interferometry,the algorithm performs ranging and angle measuring for each antenna receiving echoes in an L formation array.Moreover,the squint distortion is calibrated and 3-D trajectories of scattering centers are obtained by establishing binary quadratic nonlinear equations as well as coordinate transformation.According to the reconstructed 3-D trajectory of each scattering center and the physical structure of the ballistic target,the parameter estimation of the ballistic target is achieved.The effectiveness and robustness of the proposal is confirmed via extensive experiments.(6)Non-contact life signal extraction and reconstructionMicro-motion feature extraction and parameter estimation can not only find its application in the military anti-missile system,but also in the civil field,such as life signal detection.Due to the complex environmental factors of life signals,respiration and heartbeat micro signals are often submerged in noise and clutter.To solve this problem,a novel life signal extraction and reconstruction algorithm based on MTI-Autocorrelation-EEMD(MAE)is proposed.Based on the human respiration and heartbeat micro-motion model,the life signal echo is preprocessed.This technique utilizes a moving target indicator(MTI)algorithm to eliminate the interference of fixed object clutter on the echo signal after pulse compression.According to the marked difference in the distribution form of autocorrelation functions of the signal and noise,the range unit of the human body can be accurately located,and the echo of human life signals can be extracted from the environment of high interference and noise.The ensemble empirical mode decomposition(EEMD)algorithm is employed to adaptively decompose the extracted echo of human life signals,leading to the high-precision reconstruction of respiration and heartbeat micro signals. |
PDF Full Text Request