Performance analysis of the weighted window CFAR algorithms [radar signal processing]

With the deterioration of radar operation environment and the enhancement of menace to radar, the task of radar target detection becomes more complicated. Such as the detection of airplane, ship or cruise missile in over the horizon radar (OTHR), and the detection of moving targets in synthetic aperture radar (SAR). Therefore, it is necessary to make a further study of CFAR algorithms. The performance of the conventional cell averaging (CA) algorithm is the best in a 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, severe 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 a 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 a complicated environment and lower SNR situation. In this paper, a weighted window techniques such as rectangle, stepped and trapezium windows are discussed. The analysis results show that the weighted window technique can greatly improve in a homogeneous background and obtain an immune ability to interfering targets to some extent.