Performance Analysis of the Weighted Window CFAR Algorithms

摘要

With the deterioration of radar operation environment and the enhancement of menace to radar, the task of radar targets detection becomes more complicated. Such as the detection of airplane, ship or cruise missile in over the horizon radar (OTHR), and the detection of the moving targets in synthetic aperture radar (SAR). Therefore, it's necessary to make further study on CFAR algorithms. The performance of conventional cell averaging (CA) algorithm is the best in homogeneous background since it uses the maximum likelihood estimate of the noise power to set the adaptive threshold. But if the interfering target is present in the reference window with a target return in the test cell, sever masking of targets appears due to increased threshold. In order to overcome this problem, the ordered statistic (OS) and the trimmed mean (TM) algorithms using trimmed technique are proposed. If the reference sample number is not too big, the CFAR loss of OS and TM increase greatly. This case can usually be encountered in complicated environment and lower SNR situation. In this paper, weighted window techniques such as rectangle, steps and trapezium windows are discussed. The analysis results show that weighted window technique can improve greatly in homogeneous background and obtains an immune ability to interfering targets to some extent.