Research On Constant False Alarm Detection Method Of Ground Reconnaissance Radar

As one of the important equipment of battlefield reconnaissance and key areas monitoring,ground radar has the advantages of all-day,all-weather and long detection distance.Due to the complexity of the ground environment,ground clutter,caused by tall buildings,trees and hills which are both strong features,can seriously interfere with the radar target detection.As the key technology of radar system,constant false alarm detection algorithm performance has played a decisive role in radar’s performance.For improve the target detection performance,the research of Constant False Alarm Rate(CFAR)detection algorithm used in ground radar is of great significance.This paper introduces the basic theory of the mean level and order statistics CFAR algorithms.The theoretical property is and the performance in different environment is simulated,which provides the basis for the following research.Due to the iterative weighted amplitude CFAR algorithm cannot adapt to all nonhomogeneous environment,combining variable index statistic,kurtosis statistic and an adaptive weighted factor which can adjust to the current environment automatic,the adaptive iterative weighted amplitude CFAR algorithm is proposed.This algorithm can solve the problem of performance degradation caused by the fixed factor and meet the expected requirements in various environment,compared with the iterative weighted amplitude CFAR.On the issue of large amount of calculation in adaptive iterative weighted amplitude CFAR,by using the variable index statistic and kurtosis statistics to control the number of iterations to simplify and improve the iteration process,the simplified adaptive iterative weighted amplitude CFAR algorithm is put forward.This modified algorithm’s performance maintains well and the disadvantage of implication is reduced.Aiming at the truncated statistics CFAR algorithm’s performance deterioration in the clutter edge environment,combining with the maximum and minumum value in truncated cells adaptively to improve the truncation process,adaptive weighted truncated statistics CFAR algorithm is proposed.The problem of the false alarm rate’s increase in clutter edge environment is solved and the detection performance is improved a lot.