IF estimation in multi-sensor scenario with unknown sensor array geometry
Signal Processing, ISSN: 0165-1684, Vol: 206, Page: 108911
2023
- 3Citations
- 5Captures
Metric Options: CountsSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Article Description
An instantaneous frequency (IF) estimator for multi-sensor recordings has been developed for a scenario where the array geometry is unknown at the receiver. The method involves two stages. In the first stage, the IFs, as well as the mixing matrix (steering matrix), are iteratively estimated through the application of the ridge tracking method in combination with joint time-frequency and spatial filtering. In the second stage, the IF estimates are further refined by converting a multi-component IF estimation problem into a mono-component. For the N source signal, the IFs of all the components are re-estimated by removing N -1 components from the mixture signal. The process of re-estimation is repeated till IFs do not change in two consecutive iterations or a specified number of iterations have been reached. Experimental results indicate that the proposed method outperforms the state of art algorithms.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S0165168422004509; http://dx.doi.org/10.1016/j.sigpro.2022.108911; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85145264961&origin=inward; https://linkinghub.elsevier.com/retrieve/pii/S0165168422004509; https://dx.doi.org/10.1016/j.sigpro.2022.108911
Elsevier BV
Provide Feedback
Have ideas for a new metric? Would you like to see something else here?Let us know