Maritime surveillance has been an essential requirement since ancient times. However, in the absence of technology, it could not be done so effectively at that time as is being done in today's era of science and technology. The advancement in remote sensing technology has made maritime surveillance quicker and more precise. Ship detection and identification are playing a crucial role in the field of maritime surveillance in order to dealing with sea border activity, illegal fishery, maritime traffic, illegal migration of humans, navy movements or oil spill detection and monitoring. The information provided by imaging radar is fundamentally different from sensors that operate in infrared and visible portions of electromagnetic spectrum. SAR images are found to be very much suitable for the identification of sea objects because of very bright appearance of sea objects in SAR images against dark sea surface in background. In this work RISAT-1 SAR image of Mumbai offshore region (acquired on September 15, 2016) and Radarsat-2 SGF W2 mode of Vancouver, Canada (acquired on August 14, 2008) has been used for the rapid detection of ship objects using CFAR (Constant False Alarm Rate) algorithm technique provided by SNAP (Sentinel Application Platform) software. Presence of detected ship objects has also been demonstrated using kurtosis graph generated from azimuth and range FFT (Fast Fourier Transform) images of final ship detection resulted images of each study area.