For cognitive radio sensor networks (CRSNs) that use underlay-based spectrum access, the location of the primary user (PU) plays an important role in the power control of the secondary users (SUs), because the SUs must keep the minimum interference level required by the PU. Received signal strength (RSS)-based localization schemes provide low-cost implementation and low complexity, thus it is suitable for the PU localization in CRSNs. However, the RSS-based localization schemes have a high localization error because they use an inexact path loss exponent (PLE). Thus, applying a RSS-based localization scheme into the PU localization would cause a high interference to the PU. In order to reduce the localization error and improve the channel reuse rate, we propose a RSS-based PU localization scheme that uses distance calibration for CRSNs using underlay model-based spectrum access. Through the simulation results, it is shown that the proposed scheme can provide less localization error as well as more spectrum utilization than the RSS-based PU localization using the mean and the maximum likelihood calibration.