We present an embedded real-time 1D position tracking device at a nanometer precision. The embedded algorithm extracts the most appropriate region of the signal without manual intervention and estimates the position based on the phase shift from the signal's first Fourier harmonic. Using simulated datasets, we demonstrate that the proposed approach can achieve a similar precision to the state-of-the-art maximum likelihood fitting-based method while executing over four orders of magnitude faster. We further implemented this algorithm on a low-power microprocessor and developed a simple, compact, and low-cost embedded position tracking device. We demonstrate nanometer tracking precision in real-time drift tracking experiments.