Research On Coherent Integration Technique For The Radar Signal Of Maneuvering Target

With the development of stealth technology,the demand for the weak target detection ability is becoming higher and higher.Generally,prolonging the integration time can enhance the output signal-to-noise ratio(SNR)for a linear frequency modulated(LFM)pulse radar.However,during a long observation time,the echo energy of the moving target will span over multiple range cells,which will cause range migration.Additionally,the echo energy of the maneuvering target will span over multiple Doppler frequency cells in the slow time dimension,which will cause Doppler frequency migration.Both range migration and Doppler frequency migration will deteriorate the coherent integration performance of the maneuvering target radar signal,this thesis deeply studies the algorithms to solve the above problems and the main contributions are as summarized as follows.1.For the maneuvering target with the third-order motion model,a signal integration algorithm based on the third-order Keystone transform(TOKT),dual frequency cross correlation(DFCC)and Lv's distribution(LVD)is proposed.The proposed algorithm firstly adopts TOKT to correct the range curvature caused by acceleration,then utilizes DFCC to eliminate the residual range migration and the slow time third-order phase,lastly realizes coherent integration of the target's energy via LVD.In order to avoid the trajectory split phenomenon when the high maneuvering target's Doppler spectrum spans over two neighboring pulse repetition frequency(PRF)bands,the proposed algorithm performs TOKT,DFCC and LVD after constructing a compensation function to shift the spectrum into one PRF band.The proposed algorithm can realize the long time coherent integration without conducting parameter search,and has a better anti-noise performance than the adjacent cross correlation function(ACCF)iteratively algorithm which has the same computational cost with the proposed algorithm.The simulation results verify the effectiveness of the proposed algorithm.2.Considering that LVD cannot compensate the third-order phase term of the quadratic frequency modulated(QFM)signal,a modified LVD(MLVD)algorithm is proposed to realize the time frequency analysis.Compared with LVD,MLVD can fulfill the energy coherent integration and high-order parameter estimation of the QFM signal without increasing the computational cost.It also has good performances of anti-noise and cross term suppression.For the maneuvering targets which are adjacent to the scene center in the synthetic aperture radar-ground moving target indication(SAR-GMTI)system,the Radon-MLVD(RMLVD)algorithm is proposed to realize target focusing via combining the Radon trajectory search and MLVD.The proposed algorithm firstly utilizes the platform parameters to construct a compensation function to correct range curvature,then realizes the residual trajectory search and energy coherent integration via RMLVD.The simulation results verify the effectiveness of the proposed algorithm in the ground maneuvering target detection.3.Considering that the compensation function method in the existing literatures can only correct the range curvature of the targets which are adjacent to the scene center,a coherent integration algorithm based on subscene division is proposed to effectively detect the targets which distribute at different locations in the scene.The proposed algorithm firstly conducts the discrete polynomial-phase transform(DPT)to degrade the order of the slow time variable in the pulse compressed signal and remove range curvature.Then,a compensation function is constructed according to the divided subscene,in order to correct the range walk of the target which distributes in the corresponding subscene.Lastly,the target's energy is coherently integrated via the azimuth LVD processing.The proposed algorithm can correct the target's range migration via DPT and the compensation function construction,which only need two 2-dimensional(2-D)complex multiplications and have a lower computational cost than the traditional high-order KT and trajectory search methods.In addition,compared with the existing SAR-GMTI algorithms,the proposed algorithm can realize the range migration correction and energy coherent integration of the multiple targets which distribute at different locations in the scene.The simulation results verify the effectiveness of the proposed algorithm.4.For the maneuvering target in the axisymmetric slow time model,a non-searching energy integration algorithm combining parameter separation(PS),the second-order Keystone transform(SOKT)and nonuniform fast Fourier transform(NUFFT)is proposed.The proposed algorithm firstly isolates the target's acceleration from other motion parameters,then utilizes SOKT to correct range curvature,and realizes coherent integration of the target's energy via the slow time NUFFT.Compared with the PS-acceleration search(PS-AS)algorithm which is also based on PS,the proposed PS-SOKT-NUFFT algorithm can detect the target without search and has a lower computational complexity.The simulation results verify the effectiveness of the proposed algorithm.5.In order to solve the problem that PS-SOKT-NUFFT cannot remove the trajectory split phenomenon via frequency shifting method,a ground maneuvering target detection and parameter estimation algorithm based on PS and two fast 2-D parameter searches is proposed.The proposed algorithm firstly utilizes PS to extract the target's range and acceleration,then conducts Radon-fractional Fourier transform(FRFT)and Radon-fast Fourier transform(FFT)to estimate the target's parameters.In order to increase the speed of each search,the algorithm adopts the proposed local mapping sparse Fourier transform(LMSFT)to accelerate FRFT and FFT,thus a higher operation speed can be obtained compared with the algorithm implemented by discrete Fourier transform(DFT).For the sake of limiting the search times,the search range and step of the parameters are set reasonably.Both theoretical analysis and simulation experiments validate that the proposed algorithm has good multiple targets detection and anti-noise performances,and has a high efficiency.