Method and Electronic Device for Estimating Frequencies of Multiple Sinusoids

Technology: Frequency Estimator Engine;

Industry & Application: ICT, Wireless;

Market: The global frequency converter market is projected to grow at a CAGR of 9.1% during 2024-2032.

In the present instant, there is a recent talk on unbiased estimators like s maximum likelihood (ML) estimator has the lowest threshold but is computationally the most expensive.
There are many estimating methods like Estimation of Signal Parameters via Rotational Invariance Technique (ESPRIT), Multiple Signal Classification (MUSIC), Minimum Norm (Min-Norm), etc. are being used having flaws in terms of signal to noise ratio (SNR) & threshold values.
Hence, there is a need to address the issues.

The present invention describes a method for estimating frequencies of multiple sinusoids.

Said method comprises a few steps stated hereinbelow:

Receiving a signal, by an electronic device & estimating an initial frequency of each of the multiple sinusoids present in the received signal.
Further, determining first candidate parameter is less than zero, wherein the candidate parameter is function of an estimated signal to noise ratio (SNR) & estimated threshold.
Moreover, following steps states that performing zero-padding on the received signal, & re-estimating frequencies obtained from zero-padded version of the received signal.
Furthermore, validating the re-estimated frequencies obtained from zero-padded version of received signal based on validation criteria.
Thereafter predicting the re-estimated frequencies or the initial frequencies as optimal frequencies based on the validation.
The electronic device is shown in Fig 2. The present invention provides the solution is based on subspace based approach.

Technical Perspective:

The frequency estimator engine includes an initial frequency estimator, an energy-based zero-padding controller, an outlier detector, and an optimal frequency estimator.
The method includes refining re-estimated frequencies using iterative filtering.
Performing zero-padding on the received signal if a first candidate parameter is less than zero.
Re-estimate frequencies obtained from the zero-padded version of a received signal and validate the re-estimated frequencies.
Decide whether the re-estimated frequencies or the initial frequencies as optimal frequencies based on the validation. (Refer Fig.2)

Industrial Perspective:

The updated estimated is improved and the procedure is iterative & cost-effective during each iteration.

Prof. Ramalingam C S

Department of Electrical Engineering

TRL-4

Proof of concept tested in Lab;

Technology Transfer