強(qiáng)混響噪聲背景下的弱目標(biāo)信號(hào)檢測技術(shù).pdf

1、東南大學(xué)碩士學(xué)位論文強(qiáng)混響噪聲背景下的弱目標(biāo)信號(hào)檢測技術(shù)姓名：洪子毅申請(qǐng)學(xué)位級(jí)別：碩士專業(yè)：信號(hào)與信息處理指導(dǎo)教師：方世良郭延芬20070111AbstractInrecentyearsactivesonaranditssignalprocessingtechniqueinshallowwaterhavecaughtmoreandmoreattentionsThedetectionandclassificationofburiedobj

2、ectswithactivesonarhasbeenaremarkableprojectwithoutfavorablesolutionsforcouplesofyearsReverberationespeciallytheshallowwaterreverberation，generatedbyamassofasymmetricalscatteB，istheprimarynoiseinthedetectionproblemconcer

3、nedinthispaperReverberation，acolornonstationarystochasticprocessrelatingtothetransmittedsignalhasitsownparticularityTheechoofburiedobjectownslowsignalnoiserote，andisinundatedinthereverberationThedetectionofburiedobjectsi

4、sdiscussed，andthealgorithmsofweaksignaldetectioninshallowwaterareinvestigatednthispaperThestructureofthispaperislistedasfollowInthefirstchapter，thebackground，theproblemsandthemainideasareintroducedInChapter2，thecharacter

5、isticsorfeaturesofreverberationisdiscussedandanalyzedInChapter3，thedetectionalgorithmsrelatedtotheestimationofmodelparametersareinvestigated，respectivelyontheautocorrelmionandhigherordercumulantsestimationInthelastchapte

6、rthealgorithmbasedonsubspaceseparationbyprincipalcomponentinverseisdiscussedTheperformancesofalgorithmsisanalyzedandcomparedbytheexperimentalresultsofrealandsimulateddataKeyWords：SignalDetection，ReverberationModelParamet