Research On Cognitive Waveform Optimal Design Technologies In Radar

Radar cognitive technique can overcome the effect of increasingly severe electromagnetic environment,improve the radar detection performance of stealth target and weak small target,and the anti-jamming performance,also is a topic of general interest in the field of modern radar research.The core of radar cognitive technique is cognitive waveform design technologies,which means to design and modify the parameters of transmitted waveform based on the priori knowledge of environment.This thesis aims to improve the radar detection performance of weak small target and anti-jamming performance in complex environment,by studying low range sidelobe waveform design,orthogonal waveform design,and joint design of waveform and filter as technique approach,employing traditional Single-Input Single-Output(SISO)radar and Multiple-Input Multiple-Output(MIMO)radar as the basic platform and combining with precision strikes of low altitude small target,stealth target and other application background,which is entitled “research on cognitive waveform optimal design technologies in radar”.Chapter 1 analyzes the significance of radar cognitive waveform design technologies from a military point of view.Research status is summarized and several hot issues in the field of radar cognitive waveform are analyzed.The organization and the work architecture of this thesis are listed at last.Chapter 2 studies the SISO radar cognitive waveform with low range sidelobes optimal design technology.The optimal design criteria are presented at first.For the design purpose of suppressing waveform range sidelobes in the desired intervals,the synthesized auto correlation function is defined based on prior information,the auto correlation function and power spectral density of waveform are related in the form of a simple operation,and a cyclic iterative algorithm based on PSD fitting is proposed.Simulation results demonstrate that the proposed algorithm can generate waveform with lower range sidelobe level and less CPU time,compared with the state-of-the-art algorithm.For the design purpose of waveform optimization in the crowded spectrum environment,the sub-objective functions are formulated based on minimizing the difference between the true PSD and the ideal PSD,and minimizing the weighted integrated sidelobe level of the waveform.The balancing weight parameter is introduced and the low range sidelobe waveform with sparse frequency constraint design method is proposed.Simulation results illustrate the spectrum and range sidelobe performance of the optimal waveform using the proposed approach.Chapter 3 studies the orthogonal waveform optimization of MIMO radar.Firstly,considering single pulse waveform optimization,for the design purpose of suppressing waveform auto correlation and cross correlation sidelobe,the ideal correlation matrix is defined.Using the transformation relationship between the time domain and the frequency domain,the fast iterative algorithm based on PSD fitting is proposed.Numerical examples illustrate that the proposed approach offers performance superior to that of the state-of-the-art algorithm in terms of both cross correlation and CPU time.For the design purpose of waveform optimization in the crowded spectrum environment,the objective function is formulated based on minimizing the difference of PSD and minimizing the weighted integrated sidelobe level,the design method of orthogonal waveform with sparse frequency constraint is proposed.Simulation results illustrate the spectrum and orthogonal performance of the optimal waveform using the proposed approach.Secondly,considering multiple pulses waveform optimization,for the design purpose of completely orthogonal waveform,using the theory of space-time coding in wireless communications and the design of coding matrix and decoding matrix,based on coherent accumulation,pulse compression and Doppler filter bank,the design approach of orthogonal waveform with multiple pulse train coding is proposed.Using the auto correlation and cross correlation properties of the complete complementary sequence,the design approach of the orthogonal waveform is proposed,which can completely eliminate the auto correlation sidelobe and cross correlation.The simulation results show the effectiveness of the proposed algorithm.Chapter 4 studies the joint design of cognitive waveform and filter of SISO and MIMO radar.The similarity constraint of waveform is introduced and the objective function is formulated based on minimizing the mean-square error of the estimates of the scattering coefficients.Using the theory of optimization and rank-one decomposition,the approach of joint design of waveform and filter of SISO radar is proposed.Considering the moving scene,the objective function is also formulated based on minimizing the mean-square error of the estimates of the scattering coefficients,the fractional programming iteration is used and the joint design algorithm of waveform and filter in the presence of Doppler shifts is proposed.Considering the MIMO radar platform,the objective function is formulated based on maximizing the SINR at the output end,the randomization method,the fractional programming and the power-method like method are used and the approach of joint design of waveform and filter of MIMO radar is proposed.The simulation results demonstrate the performance of the joint design algorithms.Chapter 5 presents the conclusion and the innovative research results of the dissertation,while the possible further works are pointed out.