dc.contributor.author |
Skrapas, K |
en |
dc.contributor.author |
Boultadakis, G |
en |
dc.contributor.author |
Karakasiliotis, A |
en |
dc.contributor.author |
Frangos, P |
en |
dc.date.accessioned |
2014-03-01T02:43:40Z |
|
dc.date.available |
2014-03-01T02:43:40Z |
|
dc.date.issued |
2005 |
en |
dc.identifier.uri |
https://dspace.lib.ntua.gr/xmlui/handle/123456789/31491 |
|
dc.subject |
Estimation Method |
en |
dc.subject |
Image Resolution |
en |
dc.subject |
Spectrum |
en |
dc.subject |
Time Frequency Analysis |
en |
dc.subject |
Short Time Fourier Transform |
en |
dc.subject |
Time Dependent |
en |
dc.subject |
Time Frequency |
en |
dc.subject |
Time Varying |
en |
dc.subject.other |
Fourier transforms |
en |
dc.subject.other |
Image resolution |
en |
dc.subject.other |
Radar |
en |
dc.subject.other |
Radar target recognition |
en |
dc.subject.other |
Seismology |
en |
dc.subject.other |
Spectrographs |
en |
dc.subject.other |
Radar target imaging |
en |
dc.subject.other |
Short Time Fourier Transform (STFT) |
en |
dc.subject.other |
Time frequency analysis |
en |
dc.subject.other |
Radio waves |
en |
dc.title |
Time - Frequency analysis of radar signals for ISAR applications |
en |
heal.type |
conferenceItem |
en |
heal.identifier.primary |
10.1109/RAST.2005.1512657 |
en |
heal.identifier.secondary |
http://dx.doi.org/10.1109/RAST.2005.1512657 |
en |
heal.identifier.secondary |
1512657 |
en |
heal.publicationDate |
2005 |
en |
heal.abstract |
Time - frequency analysis is nowadays very frequently used for the evaluation of non - stationary signals, with applications in areas such as radar target imaging and identification, seismic signal interpretation etc. The corresponding two - dimensional (2D) time - frequency plots, usually called 'spectrograms', are sometimes very useful, because they provide the time - dependence of the signal spectrum, not available in other traditional spectrum estimation methods. In this paper we focus on several time - frequency techniques, like the Short - Time Fourier Transform (STFT). Furthermore, the performance of the Bilinear Time -Frequency Transforms is also carefully examined. The basic idea of time - frequency analysis is the characterization of the time-varying frequency content of a signal. In this way, additional signal information can be acquired, and ultimately improved target image resolution can be achieved. Finally, time - frequency transforms allow the use of variable parameters, which change according to the time and frequency, in order to achieve the desired target resolution. In this paper, we develop computer codes for the above methods, and simulated synthetic radar data are used for their implementation. ©2005 IEEE. |
en |
heal.journalName |
RAST 2005 - Proceedings of 2nd International Conference on Recent Advances in Space Technologies |
en |
dc.identifier.doi |
10.1109/RAST.2005.1512657 |
en |
dc.identifier.volume |
2005 |
en |
dc.identifier.spage |
699 |
en |
dc.identifier.epage |
703 |
en |