Name
Abstract | ||
|---|---|---|
In this paper an algorithm for time of arrival estimation is proposed, which allows processing of spectrally sparse channel observations in order to provide highly accurate range estimations with a maximized resolution capability. The use of sparse waveforms in combination with the presented algorithm provides increased spectral efficiency with lower computational complexity due to reduced size of the observation matrices. Additionally, the ability of the algorithm to efficiently process spectral fragmentary data also gives the capability to efficiently cope with missing data caused by frequency selective fading or interferences. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/GlobalSIP.2013.6736985 | Global Conference Signal and Information Processing |
Keywords | DocType | ISSN |
compressed sensing,covariance matrices,polynomials,radar signal processing,signal resolution,time-of-arrival estimation,computational complexity,frequency selective fading,interferences,maximized resolution capability,observation matrices,polynomial rooting,range estimations,signal adaptive time of arrival estimation algorithm,sparse waveforms,spectral efficiency,spectral fragmentary data,spectrally sparse channel observations,parameter estimation,radar signal processing,sparse sensing,spectral efficiency,time of arrival estimation | Conference | 2376-4066 |
Citations | PageRank | References |
1 | 0.41 | 4 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Gerrit Kalverkamp | 1 | 3 | 0.91 |
| Erwin M. Biebl | 2 | 2 | 2.19 |