Analysis of CFAR techniques

In radar the reflected signal is received by the antenna which is amplified, down converted and then the required signal is extracted (video signal). The video signal is then passed through Moving Target Indicator (MTI) processor which suppresses clutter. The post-MTI data is passed through Constant False Alarm Rate (CFAR) processor which qualifies echoes as targets or otherwise. The role of CFAR processor is to determine a threshold, above which any return can be considered to be from target. If this threshold is too low, more targets will be detected at the expense of more false alarms. Conversely, if the threshold is set too high, then fewer targets will be detected but the number of false alarms will be less. The distribution of the clutter can be approximated by certain probability distribution functions, where each medium follows a different probability distribution. We shall investigate important CFAR processing techniques in Gaussian noise and Rayleigh clutter. The threshold is set adaptive, that is the threshold is raised or lowered, to maintain a required Probability of False Alarm (Pfa). This paper discusses various CFAR processing techniques, by applying them to raw video of real radar, analyzing advantages and disadvantages of each technique.