Thermal ion retarding potential analyzers (RPAs) are used to measure in situ auroral ionospheric plasma parameters. This article analyzes data from a low-resource RPA in order to quantify the capability of the sensor. The RPA collects a sigmoidal current-voltage (I-V) curve, which depends on a non-linear combination of Maxwellian plasma parameters, so a forward-modeling procedure is used to match the best choice plasma parameters for each I-V curve. First, the procedure is used, given constraining information about the flow moment, to find scalar plasma parameters-ion temperature, ion density, and spacecraft sheath potential-for a single I-V curve interpreted in the context of a Maxwellian plasma distribution. Second, two azimuthally separated I-V curves from a single sensor on the spinning spacecraft are matched, given constraining information on density and sheath potential, to determine the bulk plasma flow components. These flows are compared to a high-fidelity, high-resource flow diagnostic. In both cases, the procedure's sensitivity to variations in constraining diagnostics is tested to ensure that the matching procedure is robust. Finally, a standalone analysis is shown, providing plasma scalar and flow parameters using known payload velocity and International Reference Ionosphere density as input information. The results show that the sensor can determine scalar plasma measurements as designed, as well as determine plasma DC flows to within hundreds of m/s error compared to a high-fidelity metric, thus showing their capability to replace higher-resource methods for determining DC plasma flows when coarse-resolution measurements at in situ spatial scales are suitable.