Mitigation of anthropogenic impacts on North Atlantic right whales and other at-risk species is critical but challenging given the cryptic nature of whale behaviour and the limitations of conventional visual surveys. Using passive acoustic monitoring (PAM) to alert ocean users to whale presence in near real-time can provide an effective mitigation option. The Woods Hole Oceanographic Institution (WHOI) has developed the digital acoustic monitoring (DMON) instrument and low-frequency detection and classification system (LFDCS) to detect and classify baleen whales in near real-time from autonomous platforms (e.g., buoys and gliders). A limitation of many PAM systems, including the DMON/LFDCS, is the uncertainty in acoustic detection range from the PAM platform. Our goal was to determine the range-dependent probability of detection of the DMON/LFDCS on mobile and fixed platforms. Over a 4-week period in spring of 2017, we concurrently deployed a 4-element vertical line array (VLA), an 8-element horizontal line array (HLA), a DMON/LFDCS-equipped Slocum glider, and a DMON/LFDCS buoy at a shallow (~30m) site ~15 km southwest of Martha’s Vineyard, Massachusetts, USA. We used a normal mode back-propagation technique with the HLA/VLA data to localize right whale upcalls, and then conducted a quantitative call-by-call comparison among calls detected on the HLA/VLA and those detected by the glider or buoy using logistic regression to determine the range-dependent detection probability among platforms. The results improve our interpretation of DMON/LFDCS detection data from different platforms, which in turn informs how we use this tool to disseminate more accurate information about whale distribution and near real-time locations to research, government, and industry stakeholders.