Institutional Repository
Technical University of Crete
Technical University of Crete
EN
|
EL
| URI: | http://purl.tuc.gr/dl/dias/330CE5C6-8460-45D2-948B-0C2506CB07D4 | ||
| Year | 2017 | ||
| Type of Item | Master Thesis | ||
| License |
|
||
| Bibliographic Citation | Dimitrios Paraschos, "Modern methods of sound signal processing at sea using hydrophone arrays", Master Thesis, School of Production Engineering and Management, Technical University of Crete, Hellenic Army Academy, Chania, Greece, 2017 https://doi.org/10.26233/heallink.tuc.68224 | ||
| Appears in Collections |
Sonar systems have been in practical use since the turn of the 20th century, and they are considered to be one of the most developed engineering systems. The main research subjects have concerned with detection and tracking tasks. In this work, the research is focused in the development of a signal processing algorithm, for passive sonar system, based on modern and intelligent methods. Each method has been briefly discussed as more details can be found through the references at the end.Detection in passive sonar systems, is one of the most challenging areas in the military field. In passive sonar system, received noises with SNR as low as -15dB are very common at the receiver (Urick 1983). Generaly the challenge of sonar signal processing is to detect/classify targets with very weak noises as this is an important factor in modern naval battles. In addition to the long-range detection, primary advantages of passive sonar systems are the stealthy monitor and the low complexity together with low power consumption of the sensors. On this paper, the signal is being processed both in time and space (subspace methods). For space processing the DOA (Direction Of Arrival) reveals the energy peak in relation to scanning angle, allowing us to detect target position. For time processing, there are two methods applied. First of all, by downsampling, the recorded noise is being significantly reduced due to the fact that noise follows a random frequency distribution whereas signal does not. After that the overlapping of time windowed spectra, leads to an improvement of the initial lofargram that is being produced. Both simulated and real data’s are being processed and the result are quite promising.
Copyright © DIAS 2013
