DTIC ADA573518: Adaptive Noise Reduction Techniques for Airborne Acoustic Sensors

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Adaptive Noise Reduction Techniques for
Airborne Acoustic Sensors
A thesis submitted in partial fulfillment
of the requirements for the degree of
Master of Science in Engineering
by
Ryan M. Fuller
B.S. Applied Mathematics, Rochester Institute of Technology, 2006
2012
Wright State University
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2012 2. REPORT TYPE 00-00-2012 to 00-00-2012
4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER
Adaptive Noise Reduction Techniques for Airborne Acoustic Sensor
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7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) 8. PERFORMING ORGANIZATION
Wright State University,Department of Electrical REPORT NUMBER
Engineering,Dayton,OH,45435
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14. ABSTRACT
Ground and marine based acoustic arrays are currently employed in a variety of military and civilian
applications for the purpose of locating and identifying sources of interest. An airborne acoustic array
could perform an identical role, while providing the ability to cover a larger area and pursue a target. In
order to implement such a system, steps must be taken to attenuate environmental noise that interferes
with the signal of interest. In this thesis, we discuss the noise sources present in an airborne environment,
present currently available methods for mitigation of these sources, and propose the use of adaptive noise
cancellation techniques for removal of unwanted wind and engine noise. The least mean squares, affine
projection, and extended recursive least squares algorithms are tested on recordings made aboard an
airplane in-flight, and the results are presented. The algorithms provide upwards of 37dB of noise
cancellation, and are able to filter the noise from a chirp with a signal to noise ratio of -20db with minimal
mean square error. The experiment demonstrates that adaptive noise cancellation techniques are an
effective method of suppressing unwanted acoustic noise in an airborne environment, but due to the
complexity of the environment more sophisticated algorithms may be warranted. iii
15. SUBJECT TERMS
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ABSTRACT OF PAGES RESPONSIBLE PERSON
a. REPORT b. ABSTRACT c. THIS PAGE Same as 80
unclassified unclassified unclassified Report (SAR)
Standard Form 298 (Rev. 8-98)
Prescribed by ANSI Std Z39-18
WrightStateUniversity
GRADUATESCHOOL
August7,2012
I HEREBY RECOMMEND THAT THE THESIS PREPARED UNDER MY SUPER-
VISIONBYRyanM.FullerENTITLEDAdaptiveNoiseReductionTechniquesfor
AirborneAcousticSensors BE ACCEPTED IN PARTIAL FULFILLMENT OF THE RE-
QUIREMENTSFORTHEDEGREEOFMasterofScienceinEngineering.
BrianD.Rigling,Ph.D.
ThesisDirector
KefuXue,Ph.D.
DepartmentChairofElectricalEngineering
Committeeon
FinalExamination
BrianD.Rigling, Ph.D.
KefuXue, Ph.D.
FredGarber, Ph.D.
AndrewT.Hsu,Ph.D.
Dean,GraduateSchool
ABSTRACT
Fuller, Ryan M. , M.S.Egr, Department of Electrical Engineering, Wright State University,
2012. AdaptiveNoiseReductionTechniquesforAirborneAcousticSensors.
Ground and marine based acoustic arrays are currently employed in a variety of military and
civilian applications for the purpose of locating and identifying sources of interest. An airborne
acousticarraycouldperformanidenticalrole,whileprovidingtheabilitytocoveralargerareaand
pursueatarget. Inordertoimplementsuchasystem,stepsmustbetakentoattenuateenvironmental
noise that interferes with the signal of interest. In this thesis, we discuss the noise sources present
inanairborneenvironment,presentcurrentlyavailablemethodsformitigationofthesesources,and
proposetheuseofadaptivenoisecancellationtechniquesforremovalofunwantedwindandengine
noise. Theleastmeansquares,affineprojection,andextendedrecursiveleastsquaresalgorithmsare
testedonrecordingsmadeaboardanairplanein-flight,andtheresultsarepresented. Thealgorithms
provide upwards of 37dB of noise cancellation, and are able to filter the noise from a chirp with a
signal to noise ratio of -20db with minimal mean square error. The experiment demonstrates that
adaptive noise cancellation techniques are an effective method of suppressing unwanted acoustic
noiseinanairborneenvironment,butduetothecomplexityoftheenvironmentmoresophisticated
algorithmsmaybewarranted.
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Contents
1 Introduction 1
1.1 Contribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.2 Outline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
2 PreviousWork 5
2.1 PassiveMeansofAttenuatingEnvironmentalInterference . . . . . . . . . . . . . . 5
2.2 ActiveMethodsforAttenuationofEnvironmentalInterference . . . . . . . . . . . 6
2.2.1 SpatialFiltering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
2.2.2 AdaptiveNoiseCancellationforSignalEnhancement . . . . . . . . . . . . 7
2.3 CurrentlyAvailableSystems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
2.3.1 HelicopterAlertandThreatTermination(HALTT) . . . . . . . . . . . . . 8
2.3.2 Boomerang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
2.3.3 LowCostScoutUAVAcousticsSystem(LOSAS) . . . . . . . . . . . . . 8
2.3.4 ShotSpotter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
2.3.5 ShotStalker . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
3 AcousticFundamentalsandRecording 10
3.1 SoundPropagationThroughAtmosphere . . . . . . . . . . . . . . . . . . . . . . 10
3.2 ClassificationofSoundSources . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
3.3 AudioRecording . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
3.3.1 AudioMicrophonesandPreamplifiers . . . . . . . . . . . . . . . . . . . . 16
3.3.2 AudioRecorders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
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4 NoiseinanAirborneEnvironment 22
4.1 EnvironmentalNoiseInterference . . . . . . . . . . . . . . . . . . . . . . . . . . 22
4.1.1 WindNoise . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
4.1.2 AircraftNoise. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
4.2 AirborneTestPlatforms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
4.2.1 SuperCubTestPlatform . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
4.2.2 MonocoupeTestPlatform . . . . . . . . . . . . . . . . . . . . . . . . . . 26
5 AdaptiveNoiseCancellation 31
5.1 FundamentalsofAdaptiveNoiseCancellation . . . . . . . . . . . . . . . . . . . . 31
5.2 AdaptiveAlgorithms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
5.2.1 LeastMeanSquaresAlgorithm . . . . . . . . . . . . . . . . . . . . . . . 36
5.2.2 AffineProjectionAlgorithm . . . . . . . . . . . . . . . . . . . . . . . . . 37
5.2.3 ExtendedRecursiveLeastSquaresType-1Algorithm . . . . . . . . . . . . 38
6 ExperimentalValidationofEffectivenessofAdaptiveAlgorithms 40
6.1 PreliminaryExperiments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
6.2 FlightTestSetup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
6.3 FlightTest . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
6.4 Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
6.4.1 NoiseCancellation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
6.4.2 SignalEnhancementforAdditiveChirp . . . . . . . . . . . . . . . . . . . 50
7 Conclusion 56
A MatlabCodeforAdaptiveAlgorithms 58
A.1 NormalizedLeastMeanSquaresProgram . . . . . . . . . . . . . . . . . . . . . . 58
A.2 AffineProjectionProgram . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
A.3 ExtendedRecursiveLeastSquaresType-1Program . . . . . . . . . . . . . . . . . 62
Bibliography 65
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List of Figures
3.1 Illustrationofinversesquarelawrelationofsoundintensitytodistance. . . . . . . 11
3.2 Attenuationofsoundinairincreaseswithfrequency(figurefrom[1]). . . . . . . . 12
3.3 Attenuation of 250Hz sound in air decreases with increasing temperature (figure
from[1]). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
3.4 Attenuation of 1kHz sound in air decreases with increasing humidity (figure from
[1]). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
3.5 Audiblefrequencyrangeandhearingrangeofvarioussources(figurefrom[2]). . . 14
3.6 Approximateintensityofvarioussoundsources(figurefrom[2]). . . . . . . . . . 14
3.7 Soundpressurelevelofconversation,withareferenceSPLof65dBat1meter,asa
functionofdistance.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
3.8 Directionality of microphone types: (a) omnidirectional; (b) subcardioid; (c) car-
dioid;(d)supercardioid;(e)bidirectional;(f)shotgun. . . . . . . . . . . . . . . . . 17
3.9 Frequency response of Audio Technica Pro 42 boundary microphone (figure from
[3]). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
4.1 Comparisonofturbulentandlaminarfluidflow. . . . . . . . . . . . . . . . . . . . 23
4.2 SuperCubLPRTFRCAirplane[4] . . . . . . . . . . . . . . . . . . . . . . . . . 25
4.3 SuperKraftMonocoupe90ARCairplane. . . . . . . . . . . . . . . . . . . . . . . 27
4.4 AccesspanelforfuselageofMonocoupe90A. . . . . . . . . . . . . . . . . . . . . 27
4.5 Soundspectrumofmonocoupein-flight(RelativeIntensity(dB)vs. Frequency(Hz)). 29
4.6 SpectrogramofMonocoupein-flightusingaHanningwindowoflength4096(Fre-
quency(kHz)vs. Time(s)). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
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4.7 SpectralbandsproducedbyMonocoupeengineusingaHanningwindowoflength
16384(Frequency(Hz)vs. Time(s)). . . . . . . . . . . . . . . . . . . . . . . . . 30
5.1 Blockdiagramofgenericadaptivenoisecancellationconcept. . . . . . . . . . . . 32
5.2 Blockdiagramofgenericadaptivefilter. . . . . . . . . . . . . . . . . . . . . . . . 33
6.1 Recordingdevicesetup. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43
6.2 PlacementofthemicrophoneswithinMonocoupechassis. . . . . . . . . . . . . . 44
6.3 PlacementoftherecorderandGPSwithinMonocoupechassis. . . . . . . . . . . . 44
6.4 Recordedflightpathforexperimentwithsecondoflatitude/longitudelinesinpink 47
6.5 Recordedaltitude(abovesealevel)andvelocityduringexperiment. . . . . . . . . 48
6.6 Spectrogram of reference signal of low-speed recording with 9-second chirp and
SNR=-20dBusingaHanningwindowoflength4096(Frequency[kHz]vs. Time[s]). 52
6.7 Spectrogram(usingHanningwindowoflength4096)ofcruisespeedrecordingwith
-20dBchirp,filteredwithLMS(Frequency[kHz]vsTime[s]). . . . . . . . . . . . 54
6.8 Spectrumofcruisespeedrecordingwith-20dBchirp,filteredwithLMS. . . . . . . 54
6.9 Spectrumofcruisespeedrecordingwith-20dBchirp,filteredwithAPA. . . . . . . 55
6.10 Spectrumofcruisespeedrecordingwith-20dBchirp,filteredwithERLS-1. . . . . 55
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Acknowledgement
AirForceResearchLaboratory-AirVehiclesDirectorate
RaymondBortner
BryanCannon
AirForceResearchLaboratory-PropulsionDirectorate
KeithNumbers
AirForceResearchLaboratory-711thHumanPerformanceWing
FrankMobley
KenJohnson
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Dedicatedto
JamesandAmyFuller
and
JillianMarconi
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