简介:Thispaperdescribestheinverstigationdevotedtoestablishsuitableweightsinafeed-forwardneuralnetworkrealizingthenarrow-bandfilteringmapinthecaseofadaptivelineenhancement(ALE)bytheutilityoftheoptimumcommonlearningratebackpropagation(OCLRBP)algorithm.Itisfoundthatafeed-forwardnetworkwith64linearinputandoutputneurons,and8oddsigmoidneuronsinthehiddenlayer,i.e.an(64→8→64)architecture,couldestablishthespecificinput-outputfunctioninthecaseofrelativelylowsignal-to-noiseradio.Onlyisaninputsignalconsistingofmixedperiodicandbroad-bandcomponentsavailabletothenetworksystem.Afterlearning,boththe"fanning-in-connectionpatterns",eachofwhichconsistsofweightsfanningintoahidden-neuronFromalltheoutputsofinput-neurons,andthe"fanning-out-connectionpatterns",eachofwhichconsistsofweightsfanningoutfromahidden-neurontoalltheinputsofoutput-neurons,aretunedtotheperiodicsignals.Thenonline
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简介:Arrayprocessingistoprocessthesignalscarriedbythepropagatingwavesreceivedatanarrayofsensors.Whenthesignalspropagatethroughthepracticalrandomtime-variantmedium,theirwavefrontscanshowtheprogres-sivelossesofcoherencewithincreasingspatialseparation.Thesedecorrelationsofwavefrontsresultinanangularspreadinthewavenumberspectrumcenteredaboutthetruesignaldircction-of-arrival.Thispaperputstheemphasisuponthearrayprocessingoftheangular-spreadsignalwhichiscalledtheGeneral-izedDirectional(GD)signalandaimstomatcharrayprocessingtothissignalmodelintheenergysense.Inthispaper,wealsopresentamethodofthecom-putersimulationorthegeneralizeddirectionalsignalmodel.Someresultsofcomputersimulationexperimentsandlake-tcstsinXinanjiangRiveraregiven.
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简介:Usingtheextremedifferenceofself-similarityandkurtosisatlargelevelscaleofwavelettransformapproximationbetweenthePTFM(PulseTrainsofFrequencyModulated)signalsanditsreverberation,afeature-basedmatchedfiltermethodusingtheclassify-before-detectparagriamisproposedtoimprovethedetectionperformanceinreverberationandmultipathenvironments.Processingthedataoflake-trailsshowedthattheprocessinggainoftheproposedmethodisbiggerthanthatofmatchedfilterabout10dB.Inmultipathenvironments,detectionperformanceofmatchedfilterbecomebadlypoorer,whilethatoftheproposedmethodisimprovedbetter.Itshowsthatthemethodismuchmorerobustwiththeeffectofmultipath.
简介:一个信号处理方法为高速度在水下图象的声学的传播被介绍。它有二部分。第1部分介绍信号处理为在水下声学的协调通讯。第1部分包括3个技术的点。(1)Doppler移动compensation.Chirp信号在数据包裹之间被插入。在二个拷贝关联函数之间的关联进程给吝啬的Doppler移动的更多的精确评价。然后,它能被采样补偿数据。在适应决定反馈均衡器(DFE)一个适应阶段赔偿者与快,自我优化的最不吝啬的广场(FOLMS)改编算法被利用与第二顺序阶段锁环算法比赔偿者导致更好的运动忍耐。吝啬的Doppler移动赔偿和适应阶段赔偿者的联合的表演相当好。(2)差异combiner(DC)在均衡器之前使用了。combiner和适应DFE基于FOLMS改编算法。这导致减少的计算复杂性和更好的性能。(3)串联了均衡器,涡轮架子编码了调整(TCM)解码器和重复算法。一个新bitsymbol变换器基于软产量Viterbi算法(SOVA)被学习。与传统的决定作比较,编码并且印射算法,在将近2的新变换器罐头还原剂小点错误率(BER)订。第2部分主要在一个柔韧的图象压缩算法附近。基于分离小浪变换并且修理了长度编码,为声学的图象的一个柔韧的压缩算法被学习。算法包括4个技术的点。(1)利用小浪基于转变图象的CDF9/7。(2)分析subband系数的精力分发。合适的转变层数字是3。(3)根据他们的精力分发把不同量子化步用于不同subbands。(4)使用修理了长度编码阻止错误繁殖。结果证明算法在图象质量,压缩率,和大多数之中完成平衡重要,坚韧性到BER。灰色的规模的压缩的位率声学的图象是0.85小点/象素。当BER比10-3低时,图象质量仍然保持好。当BER起床到10-2时,在那里削减一些小脏点。基于提及的上面的信号处理技术,一在水下声学的通讯系统是运作的频率乐队是的
简介:Noncoherentunderwateracousticcommunicationchannelinadverseconditionsismodeledasaphase-randomRayleighfadingchannel,anditscapacitycurveisderived.Toapproachthechannelcapacitycurve,theconcatenatedcodeofthenonbinaryLDPCcodeandtheconstantweightcodeisproposedfornoncoherentcommunicationwhichcanlatebeiterativelydecodedintheprobabilitydomain.Withoutinformationofchannelamplitudeorphaseinthereceiver,statisticparametersoftherespectivesignalandnoisebinswereestimatedbasedonthemomentestimationmethod,theposteriorprobabilitiesoftheconstantweightcodewordswerefurthercalculated,andthenonbinaryLDPCcodewasdecodedwiththenonbinaryfactorgraphalgorithm.Itisverifiedbysimulationsthatbyutilizingtheproposedconcatenatedcodeanditsprocessingalgorithm,gaptochannelcapacitycurveisreducedby3dBwhencomparedtotheexistingmethod.Underwatercommunicationexperimentswerecarriedoutinbothdeepocean(verticalcommunication,5km)andshallowlake(horizontalcommunication,near3km,delayspreadlargerthan50ms),inwhichthesignalfrequencybandwas6kHzto10kHz,andthedatatransmissionrateWas357bps.Theproposedschemecanworkproperlyinbothexperimentswithasignal-to-noiseratiothresholdof2dB.TheperformanceoftheproposedalgorithmWaswellverifiedbytheexperiments.
简介:ThesynchrodoublepulsesignalmodeisfreuqentlyusedinShortBaseLine(SBL)underwaterpositioningsystemsoastoobtaintheinforma-tionofbothdistanceanddepthofatargetsimultaneously.Howerer,thissignalmodealsobringsaboutrangingindistinctnessresultinginashorterpositioningdistancemuchlessthanthatlimitedbytheperiodofthesynchrosignal.Thispaperpresentsahardwaredistance-gatedataacquiringscheme.Itputstheoriginaldatasenttothecomputerinorderof"directfirstpulse—depthinformationpulse(orfirstpulsereflectedbywatersurface)…"toguaranteetheeffectivepositioningdistanceofthesystem.Ithastheadvan-tageofreducingtheprocessingtimeofthecomputerthusensuringtherealtimefunctioningofthesystem.Afigureoftheorbitofanunderwatermovingtargetmeasuredinpracticeisattachedtotheendofthepaper.
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简介:Inthispaperthepropertiesofspace-timecorrelationfunctionofthenoisefieldofmovingsourceinlayeredstatisticinhomogeneousmediumarestudiedandtheeffectsofrandomfluctuatingboundaryarecon-sideredaswell.Ithasbeenshown,theoreticallyandexperimentally,multi-pathpropergatingeffectscausethedispersionofthecorrelationfunctionandfluctuationsofthemediumrefractionindexandtheboundarycausethefluctuationofit.Theeffectofthemovementofthenoisesourceontheoutputofreal-timecorrelatorisequivalenttoalow-passfilteraddedthedriftofspace-timecorrelationfunction.Thesepropertiesofthecorrelationfunctioncausegravedegradationofthesignalprocessinggainofnoiserangingsonarsystem.Thefluctuatingandthedistortionofconrrelationfunctionmadeitdifficulttorealizethenoiseranging.Sointhispaper,amethodofspacecorrelationrangingbyalineararrayoffourpointswithshortseparationandlongspanandatechnigueofdual-correlationsignalp
简介:InordertosolvetheproblemofDOA(directionofarrival)estimationofunderwaterremotetargets,anovelsubspace-decompositionmethodbasedonthecrosscovariancematrixofthepressureandtheparticlevelocityofacousticvectorsensorarrays(AVSA)wasproposed.Whereafter,usingspatio-temporalvirtualtapped-delay-line,aneweigenvector-basedcriteriaofdetectionofnumberofsourcesandofsubspacepartitionisalsopresented.ThetheoreticalanalysisshowsthatthenewsourcedetectionanddirectionfindingmethodisdifferentfromexistingAVSAbasedDOAestimationmethodsusingparticlevelocityinformationofacousticvectorsensor(AVS)asanindependentarrayelement.Itisentirelybasedonthecombinedinformationprocessingofpressureandparticlevelocity,hasbetterestimationperformancethanexistingmethodsinisotropicnoisefield.Computersimulationswithdatafromlaketrialsdemonstrate,theproposedmethodiseffectiveandobviouslyoutperformsexistingmethodsinresolutionandaccuracyinthecaseoflowsignal-to-noiseratio(SNR).
简介:以便解决DOA(到达的方向)的问题评价在水下远宽带目标,一个新奇协调signal-subspace方法基于十字光谱压力的矩阵和用声学的向量传感器数组(AVSA)的粒子速度在这份报纸被建议。建议方法与在把声学的向量传感器(AVS)的粒子速度信息用作一个独立人士的基于的DOA评价方法穿的存在AVSA不同元素。也就是,它完全基于压力和粒子速度的联合信息处理P-V生气光谱,在各向同性的噪音比存在方法有更好的DOA评价性能地。由理论分析,基于P-V集中原则和eigendecomposition理论的两个交叉光谱矩阵是given.At一样的时间,为数字察觉也是的来源的相应标准有从湖试用的数据的presented.Computer模拟证明建议方法是有效的并且显然超过存在在分辨率的方法和在低Signal-to-Noise比率(SNR)的情况中的精确性。