Knowing the location of polar bears (Ursus maritimus) in their winter dens is crucial for minimizing disturbance during this critical period in their life cycle. Previous research has used Forward Looking Infrared (FLIR) technology to detect bear dens but has only achieved a detection accuracy of 45% for single flights. The thermal nature of FLIR means that some bears are never detected nor are detectable using FLIR. In this paper we explore the use of Synthetic Aperture Radar (SAR) as an alternative polar bear detection technology in a simple pilot study in Churchill, Manitoba, Canada, during October 2021. In this experimental study, we focused on the detection of polar bears on the surface in the SAR images. The result of this study can inform future efforts to proceed to den-detection experiments. In this study, we achieved a polar bear identification accuracy of 66%, albeit with a small sample size. Many of the challenges we encountered involved low signal-to-noise ratios and imprecise flight paths. Concurrent research from other parties shows that neural networks and other machine learning techniques can overcome these challenges to some degree, suggesting that SAR may be a promising candidate to become an effective tool for polar bear detection, particularly when coupled with other sensors such as FLIR.