Target detection is the first stage of automatic target recognition（ATR）. A rapid Constant False Alarm Rate （CFAR） detection algorithm is proposed in this paper. This detection algorithm is based on Rayleigh clutter distribution assumption and is composed of two stages: a horizontal CFAR and a vertical CFAR. The superposition of the reference windows of adjacent pixels is used to speed up the estimation of clutter mean

and the characteristic of clutter distribution is used to speed up the estimation of clutter variance. The standard variance characteristic of target data is used to reduce false alarm rate. A weighted counter filter is used to eliminate the sparse bright pixels

and the connected regions whose area is within a certain bound are detected as region of interest. Experiment using the MSTAR pubic data set shows the power of this approach in SAR target detection.