Research On Refocusing Method Of Maneuvering Moving Targets Under Low SNR Environment

As an active microwave imaging technology,synthetic aperture radar(SAR)has the advantage of high-resolution,all day,and all weather,which plays an increasingly important role in target detection and recognition.Recently,with the improvement of SAR resolution and the development of parameter estimation technology,the detection and recognition of ground non-cooperative moving target have become one of the key research areas of national defense and have received great attention from military powers in the world.However,due to the non-cooperative of the ground moving target and the complex movement(time-dependent characteristic)in the synthetic aperture time,the energy of the moving target is defocused in the SAR image and is annihilated in the background clutter,which makes the target detection performance limited.Therefore,it is necessary to further refocus the moving target to improve its signal-to-noise ratio(SNR),and followed by the foundation for subsequent target detection and recognition.However,the existing refocusing algorithms require operations such as interpolation and multi-dimensional search,resulting in high computational complexity,which is not conducive to engineering realization.In addition,the existing target motion parameter estimation methods only exploit the amplitude information of the signal,making its parameter estimation performance limited under low SNR.Therefore,it is necessary to further study a fast moving target refocusing method under low SNR to improve the detection and recognition performance of time-dependent moving targets.Aiming at the above-mentioned problems,the main research contents and innovations are as follows:(1)The key issues and influencing factors for the refocusing of SAR moving targets are researched.First,according to the different motion characteristics within the SAR synthetic aperture time,the geometric and signal model of the time-dependent target movement are analyzed.Second,the range cell migration(RCM)and azimuth Doppler frequency modulation(DFM)of the SAR moving target are analyzed,where the applicable boundary conditions are derived.Finally,the above analyses are verified by computer simulation.(2)Owing to the interpolation and multi-dimensional search which has high computational complexity during correcting the range cell migration(RCM),a fast maneuvering target refocusing method based on principal component analysis(PCA)and coherently integrated cubic phase function(CICPF)by exploring the geometric information of RCM is proposed.First,the target movement is modeled as a high-order motion model.Further,the RCM is corrected by using phase difference(PD)and PCA method to focus the energy of the target in the same range unit.Second,the azimuthal signal of the target is modeled as a multi-component linear frequency modulation(LFM)signal.The azimuthal Doppler modulation parameters are accurately estimated by using the proposed CICPF method to realize the fast refocusing of the maneuvering target.Compared with the existing methods,the proposed method has the following advantages:(1)By exploiting the geometric characteristics of the signal,the multi-dimensional parameter searches and interpolation operations can be effectively avoided,which reduce the computational complexity of the algorithm.(2)The target motion is modeled as a higher-order model to accurately describe the large maneuverability of the target,achieving accurate refocusing processing.Finally,the simulation and the measured data verify the effectiveness of the proposed method.(3)For long-distance,small/stealth time-dependent moving targets,the echoes have low signal-clutter-noise-ratio(SCNR),which invalid the existing parameter estimation methods.A coherently integrated smoothed cubic phase function(CISCPF)method for estimating the parameters is proposed.First,by exploring the prior information that the self-term energy of the cubic phase function(CPF)presents a symmetrical distribution and the energy of the cross term and the pseudo peak presents an irregular distribution,a new kernel function with smooth CPF(SCPF)is constructed to suppress the cross terms and false peaks.Second,the coherent accumulation of self-term energy is realized by Fourier transform(FT).Compared with the existing methods,the proposed method accurately realizes estimation of motion parameters under low SCNR by simultaneously mining and utilizing the amplitude and phase information of the echo signal.Finally,it is applied to the refocusing of time-dependent targets and good focusing results are obtained.The effectiveness and correctness of the proposed method are verified through simulation and real data.