Abstract
This work investigates a new approach for frequency estimation of multiple complex sinusoids in the presence of noise. The algorithm is based on the optimization of the least squares (LS) cost function using a gradient ascent algorithm. The paper studies the performance of the proposed method and compares it to other estimation techniques such as root-multiple signal classification (root-MUSIC) and the discrete-time Fourier transform (DTFT). Simulation results show the performance gains provided by the proposed algorithm in different scenarios.
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Acknowledgements
This work is supported by: the COMET-K2 “Center for Symbiotic Mechatronics” of the Linz Center of Mechatronics (LCM), funded by the Austrian federal government and the federal state of Upper Austria.
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Guzman, Y.E.G., Lunglmayr, M., Huemer, M. (2020). A Gradient Ascent Approach for Multiple Frequency Estimation. In: Moreno-Díaz, R., Pichler, F., Quesada-Arencibia, A. (eds) Computer Aided Systems Theory – EUROCAST 2019. EUROCAST 2019. Lecture Notes in Computer Science(), vol 12014. Springer, Cham. https://doi.org/10.1007/978-3-030-45096-0_3
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DOI: https://doi.org/10.1007/978-3-030-45096-0_3
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