Key Techniques Research Of ISAR Imaging For Non-cooperative Targets With Complex Motion Under Low SNR

Inverse synthetic aperture radar(ISAR)is a significant imaging radar,which has the characteristics of all-weather,all-day and long-distance imaging,get the two-dimensional high-resolution image of the target,and provide the size and geometry of the observed target,which has great value in both military and civilian fields.After more than half a century of development,the basic theory of ISAR imaging have been developed comparatively mature.However,with the increasingly complicated observation scene and movement of imaging target,higher requirements are proposed for ISAR imaging system.The energy of scattering points of the target is distributed at different range cell,meanwhile each scattering point also produces a time-varying doppler frequency,which make the conventional range-Doppler algorithm is impossible to generate a well-focused ISAR image.Moreover,due to the far distance between the maneuvering target and the radar platform,atmospheric attenuation,the development of the stealth technique,the clutter and the noise,the received echo data has a low signal-to-noise ratio(SNR),which make traditional ISAR imaging methods failed.Furthermore,with the development of military and civilian demand,stricter requirements will be imposed on efficiency of ISAR system.This thesis focuses on the above problems,the main research contents and innovation points are as follows:(1)The performances of the traditional envelop-based range alignment method dramatically degrade due to low signal-to-noise ratio(SNR)of received echo signal.In this work,a parametric-based approach is proposed to perform joint range alignment and phase adjustment based on the intention of fully exploiting the energy of all the scatterers in the moving target and the two-dimensional(2-D)coherent accumulation gain of both range and azimuth compressions.To that end,first,translational motion is modeled as a polynomial signal,and inspired by the fact that all the scatterers in the moving target experience the same translational range history,the phase difference(PD)operation and Keystone transform(KT)are utilized to transform the energy of all the scatterers into one range cell.Second,by the virtue of the fractional Fourier transform(FrFT),the energy of all the scatterers is coherently accumulated into a peak point,and from which the polynomial coefficients can be obtained accurately.With the estimated polynomial coefficients,the dechirp operation and KT are applied to jointly compensate range misalignment and phase error.The proposed method improve the output SNR by utilizing the energy of all the scattering points to maintain performance under low SNR.In addition,the proposed method has low computational complexity due to avoiding multi-dimensional search.Finally,theoretical analysis and experimental data experiment verify the effectiveness of the proposed method.(2)The azimuth time-varying Doppler frequency,caused by the complex movement of maneuvering target,deteriorates the azimuth focusing quality.conventional Range-Doppler(RD)imaging algorithm,Wigner-Ville distribution(WVD)imaging algorithm and Radon-Wigner imaging algorithm,due to poor image quality and inefficient operation and so on,are unfit for ISAR imaging of the complex motion target.To solve these problems,this thesis proposes a coherent integration cubic phase function(CICPF)based on cubic phase function(CPF)and the sampling property of the Dirac delta function,which enhance the output SNR,suppress noise terms and cross terms.Besides,analyze and compare the existing LFM parameter estimation method with the CICPF in detail,and derive the Cramer-Rao Lower Bound(CRLB)and SNR gain.In the end,the CICPF is applied in ISAR imaging,compared with the start-of-the-arts methods,the proposed method can obtain well-focused ISAR image under low SNR environment.The simulation results also verify the effectiveness of the proposed algorithm.(3)The fourth part of the thesis propose a fast ISAR scaling method based on pseudo-polar fast Fourier transform(PPFFT).Firstly,the rotation relation of adjacent ISAR images is transformed into the transitional relation of pole angle by utilizing PPFFT.And then,based on that,a new cost function called integrated correction is defined to obtain the rotation angle velocity(RAV)coarse estimation.Finally,the optimal RAV can be estimated by using the golden section method.Compared with the available cross-range scaling algorithms,the proposed method avoids the problems of precision loss and high computational complexity caused by interpolation operation.Furthermore,the results of the scaling of the aircraft measured data are obtained in the simulation part.