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Some Statistical Properties of the Ambient Noise in the Baltic Sea and Its Relation to Passive Sonar

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Some Statistical Properties of the Ambient Noise in the Baltic Sea and Its Relation to Passive Sonar Some statistical properties of the ambient noise in the Baltic Sea and its relation to passive sonar Johan Fridstrom¨ A thesis presented for the degree of Master of Science Royal Institute of Technology Sweden 2015 This thesis is part of an EU project financed by LIFE+ I Abstract The Baltic Sea Information on the Acoustic Soundscape (BIAS) is an European Union financed research project coordinated by FOI. The goal is to determine the soundscape of the Baltic Sea. This study is a part of BIAS and was focused on generating Wenz curves for the Bothnian Sea, which is a part of the Baltic Sea. Wenz curves describe the spectral noise level at different sea states. The investigation of the soundscape was done for both summer and winter conditions when the hydrographical situations differ. Further investigations of the noise dependencies of the natural and anthropogenic sound sources were performed. Wind and ships were dominating in a broad frequency band. The influence of ship noise on the ambient noise is dependent of frequency and distance. Ships within 5 km distance dominates the recorded noise levels and are not part of the ambient noise. At distances longer than 5 km a single ship becomes non-distinguishable and part of the range independent noise floor. Passive sonar ranges were calculated for two different sources. The range was shown to be clearly dependent on the sea state. With an increase of wind speed from sea state 0.5 to 3 the range increased with about 100%. The results of this study will be used in BIAS and in related research projects. It may be used for marine biologics but also for development of sonar and underwater systems. II Sammanfattning Statistisk beskrivning av Ostersj¨onsljudlandskap¨ { och dess p˚averkan p˚ar¨ack- vidderna f¨orpassiva hydrofonsystem BIAS ¨arett EU finaniserat projekt som koordinaeras av FOI och syftar till att beskriva ljudlandskapet i Ostersj¨on.¨ Denna uppsats ¨aren del av BIAS med fokus p˚aatt gener- era Wenzkurvor f¨orBottenhavet, vilket ¨aren del av Ostersj¨on.¨ Wenzkurvor beskriver spektrala ljudegenskaper f¨orolika v¨aderlekar. Kurvorna ¨arframtagna f¨orb˚adesommar- och vinterf¨orh˚allanden.De dominerande ljudk¨allornasinverkan p˚aljudbilden studerades. Resultaten visar att vind och fartyg ¨arde dominerande faktorerna. Fartygens bidrag till bakgrundsljudet visade sig bero p˚ab˚adefrekvens och avst˚andettill m¨atpunkten. Fartyg innanf¨oren radie p˚a5 km dominerade de uppm¨attaljudniv˚aerna. Utanf¨ordenna radie kunde inte enskilda fartyg med s¨akerhet idenfieras i ljuddata. Far- tygens ljud f¨orsvann in i trafikmullret som st¨andigtfinns i Bottenhavet. Utifr˚ande olika hydrografiska karakt¨arernaber¨aknadesr¨ackvidden f¨ortv˚aljudk¨allorf¨or en passiv sonar. R¨ackvidden var klart beroende av v¨aderf¨orh˚allandet.Med en ¨okad vind- hastighet fr˚ansj¨otills˚and0.5 till 3 ¨okade maximala detektionsavst˚andetf¨orsonaren med ungef¨ar100%. Resultaten fr˚anden h¨arstudien kommer anv¨andasinom BIAS. De kan ocks˚akomma att anv¨andasav marinbiologer inom forskning p˚adjurlivet i Ostersj¨onmen¨ kan ¨aven anv¨andasf¨orutveckling av sonarsystem och andra undervattenssystem. III Preface The work of this thesis was carried out at Totalf¨orsvarets Forskningsinstitut in Kista, Stockholm. The task was a part of BIAS but also supported by FOI Underwater depart- ment. Professor Peter Sigray led the work with good help from PhD Leif K.G. Persson. First I want to thank the entire Underwater department at FOI for all interesting discus- sions, nice coffee breaks and a very pleasant stay. Extra thank to PhD J¨orgenPihl who helped me with sonar calculations. Also PhD Mats Nordin has earned extra gratitude for without any doubt recommended me for this job and for all good and guiding discussions during my entire study time at KTH. I want to send special thanks to Professor Jakob Kuttenkeuler at KTH for the encour- agement and enthusiastic support during the work and MsD Sebastian Thun´efor all the profitable discussions. I am most grateful for the help I got from Professor Peter Sigray and PhD Leif K.G. Persson who have helped me daily by answering question, provided me with good liter- ature, discussed solutions and results but most of all always prioritized my time before their own making the time at FOI in Kista a very stimulating and funny period of my life. Of course I also want to thank my parents, Inger and H˚akan, who always and doubtless supported me and made it possible to complete the Master Degree in Science. Also my girlfriend Sandra owns my gratitude for all the positive support. Stockholm June 2015 Johan Fridstr¨om IV Contents 1 Glossary and abbreviation 1 2 Introduction 4 3 Goals and structure of this thesis 7 4 Limitations 8 5 Theory Part I: Underwater acoustics 9 5.1 Basic acoustic properties . .9 5.2 Relevant sources of noise in the Baltic Sea . 10 5.2.1 Sound propagation, refraction and absorption . 15 5.3 Ambient noise . 16 5.3.1 Rule of fives . 16 5.3.2 Acoustics of the Baltic Sea . 16 6 Theory Part II: Signal processing and analysing 19 6.1 Stationarity . 19 6.2 Outliers . 20 6.3 Correlation . 21 6.4 Spectral analysis . 22 6.5 Fourier analysis . 22 6.6 Power Spectral Density . 22 6.7 Bandwidth . 23 7 Theory Part III: Passive sonar 24 7.1 Purpose and use of passive sonar . 25 7.2 Passive sonar equation . 25 8 Method 28 8.1 Data collection . 28 8.1.1 Noise recordings . 28 8.1.2 Meteorological data . 30 8.1.3 AIS data . 30 8.2 Signal processing . 30 8.2.1 Pre-processing . 30 8.2.2 Grubbs' test . 31 8.2.3 Kolmogorov-Smirnov two sample test of stationarity . 32 8.2.4 Averaging . 32 V 8.3 Handling of different data sets . 33 8.3.1 Combining ambient noise and meteorological data . 33 8.3.2 Combining ambient noise and shipping data . 34 8.4 Method of determining ambient noise and its dependencies . 35 8.4.1 Transformation from time to frequency plane . 35 8.4.2 Correlation of wind, waves and ambient noise . 35 8.4.3 Wenz curves based on wind speed . 36 8.4.4 Ambient noise dependency of significant wave height . 36 8.4.5 Ambient noise dependency of hydrography . 37 8.5 Sonar range calculations . 37 9 Results and discussion 39 9.1 Signal processing results . 39 9.2 Meteorological conditions at the measuring location . 43 9.3 Ambient noise in different meteorological conditions . 46 9.4 Shipping and ambient noise . 51 9.5 Range of passive sonar . 55 10 Conclusions 59 References 61 A About the project A1 A.1 BIAS . A1 B The location A2 B.1 Weather at the position . A2 B.2 Hydrography of the location . A4 VI 1 Glossary and abbreviation Ambient noise Ambient noise is the noise background that is observed with a non-directional hydrophone excluding self-noise or identifiable localized source of [22]. In total absence of anthro- pogenic sounds the term natural ambient noise is used [23]. Anthropogenic Means that (in this case) noise has its origin in the influence of human activity. Bandwidth Bandwidth is the range between frequency upper and lower frequency content of a signal. It is measured in Hz [23]. Noise Noise is sound of random nature, which means that the spectrum contains no clear de- fined frequency components. Noise can also refer to unwanted signals. What is regarded as noise depends on the receiver and the context. [23]. Power Spectral Density: A power representation of a signal with the amplitude energy/frequency. Often used for stationary random signals [20]. Octave An octave is a doubling of frequency. Octave band is a frequency band with the mid frequency determining the name [25]. Refraction The bending of sound due to environmental changes in the medium [5]. 1 Root mean square The squared mean value of the signal. It is often used to describe a quantity of a signal with both positive and negative values [1]. Sea States Sea states is defining different weather conditions at sea. It is ranged from zero to eight based on wind speed and significant wave height [5]. Sound Acoustic energy radiated through a medium from an object that vibrates. It can be either desired signals or noise [23]. Sound pressure levels The acoustic pressure relative the reference pressure 1 mPa squared measured in a loga- rithmic scale. Often used to express sound with a quantity [20]. Stationary A signal whose statistical properties does not change with time is stationary [20]. Transient signal A signal with a limited duration and a clear start and stop [25]. 2 AIS Automatic Identification System BIAS Baltic Sea information on the Acoustic Soundscape CDF Cumultative Distribution Function DFT Discrete Fourier Transform DSP Digital Signal Processing FMV F¨orsvarets Materiellverk (Swedish Defence Material Administration) FOI Totalf¨orsvarets Forskningsinstitut (Swedish Defence Research Agency) HELCOM Helsinki Commission, Baltic Marine Environment Protection Commission HIRLAM High Resolution Limited Area Model LOFAR Low Frequency Analysis Recorder PSD Power Spectral Density PSU Practical Salinity Unit [g/kg = ppt] RMS Root Mean Square SMHI Sveriges Meteorologiska och Hydrologiska Instut (Swedish Meteorological and Hydrological Instute) SOFAR Sound Fixing and Ranging SONAR Sound Navigation and Ranging SPL Sound Pressure Level SS Sea State 3 2 Introduction The Element of Surprise is an effective tactic in warfare which was described in the Liad by Homeros. In the marine environment covert vessels will undoubtedly have a point of advantage. The Swede Torsten Nordenfelt realized this fact and in 1883 he was the first person to build and design a steam engine driven torpedo-carrying submarine [27].
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