Abstract—This article presents a quartic polynomial based approach for frequency estimation of multiple real sinusoids in additive white Gaussian noise (AWGN). The estimation of the peak and ensemble of subsequent frequencies in the spectral data is achieved using a simple slope-based approach. The performance of the frequency estimation is studied by computing the estimation error for varying signal-to-noise ratio. The performance is also studied for varying values of signal length and frequency deviation. Simulation studies are presented to establish the validity of the estimation algorithm for multiple sinusoids. The proposed approach is fast and efficient, rendering it suitable for application to real-time implementations.