Precise center-fixing of tropical cyclones (TCs) is critical for operational forecasting, intensity estimation and visualization. Current procedures are usually performed with manual input from a human analyst, using multispectral satellite imagery as the primary tools. While adequate in many cases, subjective interpretation can often lead to variance in the estimated center positions. In this paper we present an objective, robust algorithm for resolving the rotational center of TCs: the Automated Rotational Center Hurricane Eye Retrieval (ARCHER). The algorithm finds the center of rotation using spirally-oriented brightness temperature gradients in the TC banding patterns in combination with gradients along the ring-shaped edge of a possible eye. The microwave-based algorithm is calibrated and validated using 85-92 GHz passive microwave imagery because of this frequency's relative ubiquity in TC applications. We have now extended this approach to geostationary longwave infrared and visible imagery. The algorithm is successful at resolving center positions for each separate sensor type, and we will show that this approach works best when the separate sensors are used complementarily.