JTF Characteristics Recovery And Suppression Of Wind Farm Clutter For Short CPI Air Surveillance Radar

Air traffic control(ATC)surveillance radar plays an extremely important role in air transportation.Its role is to monitor the position of aircraft targets in real time and ensure flight safety.With the rapid development of global wind power generation,the impact on the performance of the ATC surveillance radar has become more and more serious.The wind turbines in the wind farm may generate strong scattering clutter with a certain spectrum broadening.The clutter may cover up the aircraft targets,leading to an increase in the probability of false alarms and missed alarms for air traffic control radar.Therefore,the research on the wind farm clutter suppression technology for air traffic control radar is of great significance for improving the target detection probability of the ATC surveillance radar,reducing the false alarm rate,and ensuring air traffic safety.This essay firstly presents the signal models of aircraft target and wind turbine clutter,which provides data source for the sparse feature analysis and clutter suppression.Secondly,on the basis of the radar signal model,the sparse characteristics of the aircraft target and wind turbine clutter in different transform domains are analyzed.At the same time,the influence of a short coherent processing interval(CPI)on the sparse characteristics of wind turbine clutter is analyzed,which provides the theoretical basis for the subsequent discussion of wind farms clutter suppression.Secondly,the clutter suppression method of wind farms for air ATC radar is analyzed and discussed based on morphological component analysis(MCA).According to the sparse characteristics of the target and clutter in different transform domains,the algorithm is iteratively optimized and the different signal components can be reconstructed in the two transform domains to complete the separation of the clutter and the target.The suppression of wind farms and the extraction of the aircraft target can be achieved when wind turbine clutter is in the same distance unit with the target,However,on the condition of the low signal-to-noise ratio(SCR),the performance of the MCA algorithm is difficult to guarantee,so basis pursuit de-noising(BPDN)algorithm is proposed to reconstruct clutter components and signal components in different transform domains to achieve clutter suppression for wind turbines.The experiment results of simulation and measured data show that the BPDN algorithm can effectively solve the problem of clutter suppression in wind farms under low SCR conditions.Finally,in view of the performance degradation of the air traffic control surveillance radar clutter suppression method under the short CPI condition,the suppression method of the wind farm clutter based on the combination of joint time frequency domain(JTF)feature restoration and MCA is presented.JTF feature restoration is firstly performed before MCA,which can effectively solve the problem of the lack of obvious sparse features of short CPI radar echoes which will lead to the degradation of MCA performance.The experimental results of simulation and measured data show that JTF feature restoration can effectively improve the sparse features of radar echoes in the corresponding transform domain,and then MCA is used to suppress wind farms clutter.This proposed method can effectively solve the problem of reduced target detection probability caused by wind farm clutter for short CPI ATC radar.