Summary: Window-based estimates for stochastic harmonic regression models are useful for cases where harmonic parameter appear to be time-varying. Least squares estimates for harmonic models with one fundamental have been studied and asymptotic variance expressions have been developed. This paper extends these results to weighted least squares for the multiple fundamental case, and presents an application in signal processing.