Font Size: a A A

Research On The ISAR Imaging Based On The Non-searching Estimation Technique Of Motion Parameters

Posted on:2016-10-15Degree:DoctorType:Dissertation
Country:ChinaCandidate:J B ZhengFull Text:PDF
GTID:1108330464468871Subject:Signal and Information Processing
Abstract/Summary:PDF Full Text Request
Radar imaging has characteristics of all-weather, day/night and long range, and has great values in civilian and military applications. Due to differences of the Radar’s working mechanism and imaging mode, the imging radar can be divided into two categories-the inverse synthetic aperture Radar(ISAR) and the synthetic aperture Radar(SAR). In the ISAR imaging of the maneuvering target and the target with complex motions, the echo after motion compensation can be characterized as the model of multi-component polynomial phase signals, i.e., the linear frequency modulated(LFM) signal and the cubic phase signal(CPS). In the realistic application of the ISAR imaging, we determine the corresponding model for the target based on its motion character. Thereafter, the effective signal processing algorithm is utilized to obtain the ISAR image with a high quality. For the maneuvering target and the target with complex motions, we do the reaseach on the ISAR imaging based on the non-searching estimation technique of motion parameters. The main work is summarized as follows:1. Based on the non-searching estimation technique of motion parameters, the centroid frequency- chirp rate distribution(CFCRD) is proposed for the ISAR imaging of the maneuvering target. The CFCRD utilizes the modified scaled Fourier transform(MSCFT) to eliminate the linear coupling of the self-term after the symmetric instantaneous autocorrelation function and completes the energy accumulation through the fast Fourier transform(FFT). The innovation of the CFCRD is the MSCFT, which introduces a zoom factor to resolve the spectrum aliasing problem of the traditional scaled Fourier transform. Therefore, compared to the published ISAR imaging algorithm based on the modified Wigner-Ville distribution(M-WVD), the ISAR imaging algorithm based on the CFCRD can be utilized for extreme cases, such as the rough sea surface and high maneuvering scatterers. The real data simulation and performance analyses validate the CFCRD and the corresponding ISAR imaging.2. Based on the non-searching estimation technique of motion parameters, a fast ISAR imaging algorithm with the Generalized Scaled Fourier Transform(GSCFT) is proposed for the target with complex motions. For the CPS model, the Chirp Rate(CR) and the quadratic chirp rate(QCR), which deteriorate the azimuth focusing quality due to theDoppler frequency shift, need to be estimated with a parameter estimation algorithm. By employing the proposed generalized scaled Fourier transform(GSCFT) and the nonuniform fast Fourier transform(NUFFT), a fast parameter estimation algorithm is presented for the CPS. Compared to the scaled Fourier transform based algorithm, advantages of this fast parameter estimation algorithm include(1) the computational cost is lower due to the utilization of the NUFFT; and(2) the GSCFT has a wider applicability in ISAR imaging applications. The CPS model and the algorithm implementation are verified with the real radar data. In addition, the cross-term, which plays an important role in correlation algorithms, is simulated and analyzed for the fast parameter estimation algorithm. Through the simulation of the real radar data and the analysis of the computational cost, we verify the effectiveness of the fast parameter estimation algorithm and the corresponding ISAR imaging algorithm.3. According to analyses of the Lv’s Distribution(LVD) and the instantaneous autocorrelation function of the CPS, two non-searching estimation algorithms for the CPS, which are the keystone time-CR distribution(KTCRD) and the CR-QCR distribution(CRQCRD), are proposed. Based on these two non-searching estimation algorithms, two ISAR imaging algorithms are presented for the target with complex motions. The KTCRD utilizes the keystone transform to eliminate the linear coupling in the self-term of the time-CR distribution. Thereafter, the FFT is utilized to complete the energy accumulation along the slow time axis. Due to the utilization of the FFT based chirp-z transform, the keystone transform avoids the interpolation and the KTCRD only needs the complex multiplication and the FFT operation. Based on the proposed generalized keystone transform(GKT) and the parametric instantaneous autocorrelation function, a novel distribution of the CPS, known as the CRQCRD, is presented. The GKT can also be completed with the FFT based chirp-z transform. Thus, the implementation of the CRQCRD only needs the complex multiplication, the FFT operation and the NUFFT operation. Thanks to the application of the NUFFT, the computational cost is saved and the searching procedure is unnecessary for the nonuniformly spaced signal. Compared to other published estimation algorithms for CPSs, the KTCRD and the CRQCRD can acquire a higher anti-noise performance and no error propagation, are searching-free and more suitable for the situation of multi-CPSs. After several simulations and analyses of these two algorithms, we presented corresponding ISAR imaging algorithms for the target with complex motions, and simulations with the synthetic data and the real datavalidate the effectiveness of these two ISAR imaging algorithms.4. After the research of existing estimation algorithms for the CPS and the non-searching estimation technique of motion parameters, a fast bilinear parameter estimation algorithm is proposed and applied in ISAR imaging for the target with complex motions by employing the cubic phase bilinear function, NUFFT and the parameter space switching method. The cubic phase bilinear function guarantees the bilinearity for the proposed fast bilinear algorithm, the NUFFT speeds up the Fourier transform along the nonuniformly spaced lag-time axis, and the parameter space switching method eliminates the brute-force two-dimensional searching procedures of the energy accumulation. Compared to two existing representative parameter estimation algorithms for the CPS, the advantages of this proposed fast bilinear algorithm include(1) the computational cost is lower due to utilizations of the NUFFT and the parameter space switching method; and(2) the bilinearity and the energy accumulation operation guarantee a higher anti-noise performance and a better suppression on cross-terms. Through simulations on synthetic models and the real radar data, we verify the effectiveness of this fast bilinear parameter estimation algorithm and the corresponding ISAR imaging algorithm.
Keywords/Search Tags:inverse synthetic aperture Radar(ISAR), synthetic aperture Radar(SAR), linear frequency modulated(LFM) signal, cubic phase signal(CPS), parameter estimation
PDF Full Text Request
Related items