An Efficient Two Dimensional Multiple Real-Valued Sinusoidal Signal Frequency Estimation Algorithm

Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 221)


In order to alleviate the effect of additive noise and to reduce the computational burden, we proposed a new computationally efficient cross-correlation based two-dimensional frequency estimation method for multiple real valued sinusoidal signals. Here the frequencies of both the dimensions are estimated independently with a one-dimensional (1-D) subspace-based estimation technique without eigendecomposition, where the null spaces are obtained through a linear operation of the matrices formed from the cross-correlation matrix between the received data. The estimated frequencies in both the dimensions are automatically paired. Simulation results show that the proposed method offers competitive performance when compared to existing approaches at a lower computational complexity. It has shown that proposed method perform well at low signal-to-noise ratio (SNR) and with a small number of snapshots.


2-D frequency estimation Sub-space based method: Real-valued sinusoidal model Cross-correlation 


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Copyright information

© Springer India 2013

Authors and Affiliations

  1. 1.Department of Electronics and Communication EngineeringNational Institute of TechnologyTrichyIndia

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