Abstract
Frequency and power estimation of sinusoidal signals, has captured the attention of researchers due to its important applications. This paper involves a frequency and power estimation method of unidentified number of source sinusoidal signals using Eigen technique. The eigenvector corresponding to the correlation matrix’s minimum eigenvalue yields the minimum power of the FIR filter’s output power. The corresponding roots are determined using the filter polynomial and root elimination technique is used to determine the pseudospectrum. Consequently, by deploying the pseudospectrum and filter polynomial, the real power spectrum is derived.
Highlights
Frequency and power evaluation of several sinusoids embedded in wide-band signals has been an important issue in engineering [1][2]
Two scenarios of input source signals are simulated with zero dBm noise level ( ) and 100 samples to show the effectiveness of the proposed method
Due to the importance of frequency and power estimation of sinusoidal signals, a new technique has been proposed in this paper using the eigen-approach
Summary
Frequency and power evaluation of several sinusoids embedded in wide-band signals has been an important issue in engineering [1][2]. [4][5] These methods are considered poor estimation techniques for certain applications of which the number of source signals is unknown. The usage of random search optimization processes towards estimating frequencies and power of sinusoidal signals has been offered; the author in [6] uses a population based stochastic method, Particle Swarm Optimization (PSO) to estimate diverse sinusoids’ frequencies along with their real power, without previous knowledge of the signals’ number, amplitude, nor phase [7]. The current paper presents a non-parametric method that estimates the frequency and power of several sinusoids without knowing the number of signals in advance using an eigen-approach. On the basis of this criteria, the locations of the roots and the real signal power are calculated by excluding one root at a time and recalculating the output signal power
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