Research On Intelligent Optimization Algorithm Of Radar Anti-Co-Frequency Interference

With the rapid development of radar technology,the modern battlefield presents a complex electromagnetic environment,and the electromagnetic spectrum is increasingly crowded,resulting in a substantial increase in the probability of radar co-frequency interference.At the same time,as the battlefield environment becomes more and more diverse,a single radar can no longer meet the needs of battlefield detection.Therefore,radars usually appear in the form of collaborative detection in formations.Since the radars in the formation are relatively close,co-frequency interference will occur when their frequencies are the same or similar.This will seriously affect the detection ability of the radar,and even cause damage to the radar,resulting in unpredictable losses.Therefore,how to eliminate the co-frequency interference between radars has always been a research hotspot in the modern military field.Low probability of intercept radar is a kind of radar that is not easy to be found.It has excellent anti-reconnaissance and anti-jamming capabilities.While ensuring the detection of targets,it can minimize the probability of being intercepted.Therefore,it is widely used in modern warfare.Compared with traditional radar,low probability of intercept radar has more important research value and practical significance.This thesis takes the low probability of intercept radar in the complex battlefield environment as the research object,and conducts a specific research on the problem of co-frequency interference between radars.The main research contents are as follows:(1)Firstly,the research status of low-probability radar and co-frequency interference between radars at home and abroad is introduced,and then the common radar anti-co-frequency interference methods are summarized,and the range gate avoidance method,anti-asynchronous algorithm and the coherent accumulation avoidance method is analyzed,and the advantages and disadvantages of each method are analyzed.(2)From the perspective of future radar networking,in view of the problem of co-frequency interference between radars with the same or similar frequencies in the formation,the conventional orthogonal waveform coding is improved,and a radar orthogonal signal design based on an improved water wave optimization algorithm is proposed.method.The algorithm uses inversion exchange strategy,cross mutation operator and neighborhood search strategy to redefine the motion of water waves,and set the global and local search capabilities of the adaptive parameter balance algorithm.A mathematical model is established by the autocorrelation and cross-correlation functions of the signal,and the improved algorithm is used to optimize the model to obtain a radar FM coded signal set that satisfies the quadrature characteristics.The simulation results show that the designed frequency modulation coded signal set can effectively avoid the generation of co-frequency interference in the process of radar networking,and achieve the purpose of resisting co-frequency interference in the process of one’s own radar formation.(3)Aiming at the problem of co-frequency interference of active radars,from the perspective of signal separation,an independent component analysis method based on improved crow search algorithm is proposed to separate co-frequency signals.First,improve the crow search algorithm,use the initial population of the reverse learning optimization algorithm,design the global and local search capabilities of the dynamic perception probability balance algorithm,and introduce the golden sine operator and the Levy flight strategy to iteratively update the individual.Secondly,a mathematical model is established based on the kurtosis of the radar signal,and an improved algorithm is used to optimize the model,and a signal separation matrix is obtained to achieve the separation of the co-frequency signal.The simulation results show that the above method can effectively separate the co-frequency signal,eliminate the influence of the co-frequency interference signal on the target echo signal,and achieve the purpose of filtering the co-frequency interference signal intentionally generated by the enemy in active service radar.(4)Aiming at the situation that there are multiple co-frequency jamming radars in the battlefield environment,a co-frequency signal separation method based on the improved gray wolf algorithm and the independent component analysis method with negative entropy as the optimization objective is proposed.As the number of radars increases,the kurtosis will be more susceptible to outliers,resulting in unstable separation.Therefore,the improved method uses relatively stable negative entropy as the objective optimization function.At the same time,considering that the increase in the number of radars will greatly increase the problem dimension,the Givens transform is used to optimize the required separation matrix,reducing the problem dimension and reducing the amount of calculation.The optimization algorithm adopts the gray wolf optimization algorithm with fewer parameters,and uses the Circle chaotic map,nonlinear convergence factor,Cauchy Gaussian mutation and elimination selection strategy optimization algorithm to improve the optimization ability of the algorithm.The simulation results show that in the case of a large number of radars,the proposed method can effectively separate the co-frequency signals,and achieve the purpose of filtering all the co-frequency signals from unknown sources in complex battlefield environments.