Study On Jamming Suppression And Target Detection For FDA-MIMO Radar

With the increasing complexity of the modern battlefield electronic environment,the radar received echo contain many useless signals such as multiple noises and jamming,which seriously constrain the radar performance and throughout the entire process of radar detection and tracking.Therefore,conducting research on jamming suppression and target detection algorithms under complex conditions holds great practical significance for expanding algorithm applications,enhancing system reliability and usability.The Frequency Diversity Array Multiple-Input Multiple-Output(FDA-MIMO)radar,which adds frequency offsets between radiation elements,has the ability to couple distance and angle in the twodimensional beamforming of transmitted beams and flexibly control degrees of freedom.It has broad application prospects in target detection and tracking,clutter and interference suppression,parameter estimation,and RF stealth.This dissertation focuses on the radar working process and fully utilizes the advantages of FDA-MIMO radar to conduct research work on three aspects,such as target detection in non-Gaussian noise environment,target detection and tracking under jamming conditions.The main content and innovations of this dissertation are summarized as follows:1.Aiming at the problem of Smeared Spectrum interference generating suppression and deception effects that seriously affects the radar detection performance,a jamming suppression algorithm based on maximum entropy estimation and Blind Source Separation(BSS)is proposed.The algorithm is divided into three stages.Firstly,the maximum entropy estimation is used to eliminate the jamming signals from angles outside the main lobe.Secondly,the BSS is used to separate the interference and target signals into different channels.At last,it takes full advantage of the range-angle coupling characteristics of FDAMIMO radar to perform matched filtering on signals in different channels,detecting the true target echo signal.Through the processing of the three steps,the three-dimensional coordinates of the true target are obtained while suppressing interference signals,providing conditions for the subsequent tracking.Simulation results show that the detection probability of FDA-MIMO radar is significantly better when applying the proposed algorithm compared to typical phased array and MIMO radar systems.2.Aiming at the problem that Range Gate Pull-Off(RGPO)interference affects the center of the track gate,leading to a decrease in radar tracking quality or target loss,a jamming suppression method based on extended tracking range is proposed.Firstly,the method adopts multi-waveform separation processing and Secondary Range Dimension Compensation to eliminate the distance dependence of FDA-MIMO radar echo.Then,a strategy of expanding the tracking range ensures coverage of real targets,Multiple distance sectors are processed in a joint manner using beamformers,causing a misalignment of interference signals,thereby achieving forward interference elimination of RGPO.Finally,real target distance information is obtained using advanced tracking methods within the enlarged range region.Simulation results show that the algorithm can suppress RGPO interference signals across pulse repetition intervals with a certain degree of adaptivity through adaptive beamforming.Furthermore,the method also has good performance against suppressive jamming.3.Similarly,to address the issue of RGPO mainlobe jamming signals,a suppression method based on interference discrimination and elimination is proposed.The method constructs a Gray-level Co-occurrence Matrix from the Range-Doppler image of the echo,extracts the multi-dimensional image texture features of the current echo,discriminates whether there is RGPO interference in the current echo after decision-level fusion processing.Using the tracking accuracy of the radar to construct range constraints,the eigenvalues of large values are eliminated from the covariance matrix of the echo data,retaining the true target echo signal.This method can suppress forward and backward RGPO interference signals within a pulse repetition interval,increasing the received signal-to-noise ratio and improving radar tracking quality.4.Aiming at traditional Constant False Alarm Rate(CFAR)detector mismatch in the nonGaussian white noise and small Radar Cross-Section(RCS)of stealthy targets drastically compressing radar power,a target detection algorithm based on Robust Principal Component Analysis(RPCA)is proposed.This method leverages the limitation of a single stealth penetration mode,adopting a subarray frequency diversity based Multiple-Input MultipleOutput(MIMO)radar configuration.By reading dynamic RCS data in real-time according to the target flight status,it establishes an echo signal model under Symmetric α-Stable(Sa S)distribution noise conditions.It employs a robust principal component analysis algorithm to decompose the data matrix of received signals into a target matrix with low-rank characteristics and a noise matrix with sparse characteristics,thereby improving radar detection probability and performance.Furthermore,for typical detection scenarios,realtime optimization of constraints on low-rank and distance can be performed during algorithm application,effectively saving radar resources,and reducing algorithm complexity.The research content of this dissertation solves several realistic problems of FDA-MIMO radar in the process of detection and tracking,expands the application scenarios of FDAMIMO radar,and provides a theoretical basis for the application of FDA-MIMO technology in military radar equipment.