Research On Maneuvering Target Detection And Motion Parameter Estimation Techniques

Modern national defenses have higher requirements for the detection and motion parameter estimation of maneuvering weak targets.Prolonging the coherent integration time is an effective means to improve the target detection ability and motion parameter estimation accuracy of radar.However,during the long integration time,the range migration(RM)and Doppler frequency migration(DFM)induced by the target's motions have great impact on the coherent integration,and further deteriorate the target detection and parameter estimation performances.To detect maneuvering targets and estimate their motion parameters,the RM and DFM should be corrected.We do research on this project,and the main work is summarized as follows:1.For the detection and motion parameter estimation of maneuvering target moves at a uniform radial acceleration,a new algorithm based on jointly second-order keystone transform and Lv's distribution(SKT-LVD)is proposed.The SKT-LVD employs the velocity search and SKT to correct the RM.Owing to the azimuth signal of accelerating maneuvering target can be modeled as linear frequency modulated(LFM)signal,the LVD is thus applied to estimate the target's acceleration,further to compensate the DFM.Compared with the Radon fractional Fourier transform(RFRFT),SKT-LVD can effectively reduce the computational complexity thanks to the elimination of multiple dimensional search.Moreover,the proposed algorithm can removes the energy loss caused by range sampling,so the anti-noise performance is also improved in comparison with the RFRFT.Finally,simulations and raw data processing results verify the effectiveness of this algorithm.2.A new algorithm based on the modified integrated cubic phase function(MICPF)for the quadratic frequency modulated(QFM)signal parameter estimation is proposed.The QFM signal energy can be accumulated into a peak in a 2-dimensational space via the MICPF,and then the chirp rate(CR)and quadratic chirp rate(QCR)of the QFM signal are estimated by the peak coordinate.The proposed MICPF is bilinear,which indicates that it has a higher anti-noise performance and cross term suppression.Due to the azimuth echo of target with jerk motion can be modeled as QFM signal,whose CR and QCR are respectively determined by the target's radial acceleration and jerk,we apply the MICPF to maneuvering target detection and motion parameter estimation,and present a new algorithm,i.e.,SKT-MICPF.SKT-MICPF applies the velocity search and SKT to correct the RM,the MICPF is then utilized to estimate the target's radial acceleration and jerk,followed by the DFM compensation.Simulations and raw data processing results demonstrate the SKT-MICPF can effectively realize the detection and motion estimation of maneuvering target with jerk motion.3.To reduce the computational complexity of the detection and motion parameter estimation for the accelerating maneuvering target.By defining a new slow time correlation function,a novel fast algorithm is proposed.Firstly,the echo energy has been expanded to the range frequency-slow time-lag time three-dimensional(3-D)space after the correlation operation in the slow time domain.And then,the proposed extended keystone transform(EKT)is applied to remove the coupling among the range frequency,slow time,and lag time variable,after that,the fast Fourier transform(FFT)is utilized to realize the energy accumulation along the slow time axis.Thereafter,the scaled inverse Fourier transform(SIFT)is employed to eliminate the coupling between the range frequency and lag time variable,and realize the energy accumulation along the range frequency axis.Finally,the FFT along the lag time axis is performed to realize the energy accumulation along the lag time axis.In the new 3-D space,the echo energy of accelerating target has been accumulated into a peak,so the target's radial velocity and acceleration can be estimated based on the peak location,by constructing a function,the RM and DFM will be eliminate simultaneously.The cross term generated by multiple targets is also analyzed and verified by simulation,which demonstrate that this algorithm can also be applied in multiple targets scenarios.Comparisons with other representative algorithms in computational complexity and anti-noise performance indicate that this proposed algorithm achieves a good balance between the computational complexity and detection performance.The experiment with raw data is carried out to verify the effectiveness of this algorithm.4.A new algorithm for the detection and motion parameter estimation of maneuvering target with jerk motion based on range frequency correlation is proposed.In this algorithm,the SKT is firstly applied to removes the quadratic coupling between the range frequency and slow time,a 3-D space is obtained after the range frequency correlation operation.Then,the addition operation along the range frequency axis,scaled Fourier transform along the slow time axis,and inverse fast Fourier transform are successively performed to realize the energy accumulation.Finally,the echo energy can be accumulated into a peak in a 2-D space,the target's range and radial velocity information can be estimated by the peak location.With the estimated parameters,the target azimuth signal can be extracted,and the MICPF can be applied to estimate the target's radial acceleration and jerk.Finally,the coherent integration can be implemented via the FFT,followed by the DFM compensation.Theoretical derivation and experimental results demonstrate the cross term cannot influence the detection of the auto-terms,which indicates that this algorithm is also applicable in multiple targets scenarios.Comparisons with other representative algorithms in computational complexity and anti-noise performance indicate that this algorithm can greatly reduce the computational complexity with acceptable anti-noise performance loss.The raw data processing results validate the effectiveness of this algorithm.