Research On Maneuvering Target Detection Methodologies Based On Joint Parameter Estimation

With the rapid development of aerospace technology,aircraft,missiles and other targets with complex motion characteristics emerge in large numbers.This kind of target is difficult to detect because of its high speed,small radar cross section(RCS)and weak echo signal.Long time coherent accumulation can effectively improve the performance of radar target detection,but the range migration(RM)and Doppler frequency migration(DFM)caused by target motion will affect the coherent accumulation and reduce the accuracy of target motion parameter estimation.In this paper,effective detection of maneuvering target and accurate estimation of its motion parameters are studied.1.Establish a complex maneuvering target signal model based on the characteristics of the radar echo signal.Analyzed the influence of target motion characteristics on the effect of coherent accumulation,studied the algorithm based on the Generalized Radon Fourier Transform(GRFT),and based on the adjacent cross-correlation function-Lv's Distribution(ACCF-LVD)algorithm,ACCF iteratively algorithm and other representative target detection algorithms,and the advantages and disadvantages of these algorithms are compared.2.Aiming at the echo signal model of a uniformly accelerating maneuvering target,a target detection and motion parameter estimation algorithm based on extended Keystone transform is introduced,which can compensate RM and DFM at the same time.Referring to the idea of this algorithm,a joint parameter estimation target detection algorithm based on twodimensonal nonuniform trilinear autocorrelation function(2D-NTAF)is proposed for maneuvering targets with uniform jerk.The algorithm can obtain the estimated values of target distance,acceleration and jerk at the same time.After using these parameter estimated values to compensate the target echo,the velocity of the target can be obtained through onedimensional parameter search.Constructing a compensation function according to the estimated values of target velocity,acceleration and jerk can achieve the purpose of compensating RM and DFM at the same time.3.The cross-term suppression performance,detection performance and computational cost of the 2D-NTAF target detection algorithm proposed in this paper are analyzed,and compared with the GRFT algorithm,ACCF-LVD algorithm,and iteratively algorithm.Simulation results show that compared with the three algorithms,the proposed algorithm can achieve a better balance in anti-noise performance and computational complexity,and is more suitable for the detection of maneuvering targets with jerk motion.