简介：认出无线网络的边界满足一些特定的需要，在一个网络在每个节点的1-hop邻居散布的节点的相对方位角角度被用来认出网络的边界。一个新奇识别算法基于本地概括的凸的壳被建议让一个节点决定是否它自我是一个边界节点。算法的灵活性，效率和一致性被广泛的模拟在它的表演显示出。

简介：Afocusingtransformbasedminimumvariancemethod(FTMV)isproposedforestimatingtheazimuthanglesofwidebandsignals.TheestimationerrorofDirectionofArrival(DOA)inthetraditionalMinimumVariance(MV)methodduringthearraydirectionchangingwiththeshipcanbeeliminatedbyfocusingthesamplecovariancematricesinwidebandontoasinglenarrowband,andaccumulatingthebeamformeroutputsonazimuth.Then,theazimuthanglesofsignalscanbeestimatedaccurately.ExperimentalresultsshowthattheFTMVmethodismoreefficientandrobustthantheMVmethodinthiscase.

简介：ConventionalSyntheticApertureRadar(SAR)systemscannotobtainhigh-resolutionandwide-swathilluminationareaduetothewell-knownminimumantennaareaconstraint.SinglePhaseCenterMultiBeam(SPCMB)techniquecanovercomethislimitationbyaddingspatialsamplingthroughmultiplereceiversinazimuthdirection.Unfortunately,thisapproachwillleadtoanincreaseofazimuthambiguities(interbeamambiguities),becauseeachreceivebeam’smainlobeoverlapswiththeotherones’sidelobes.ThispaperprovesthatthefrontpartofSPCMBSARsystemscanbeconsideredtobeahybridfilterbank.Therefore,theazimuthsignalcanbereconstructedandtheinterbeamam-biguitiescanbeeffectivelysuppressedbyawell-designedhybridfilterbank.

简介：

简介：Toaimattheproblemthatthehorizontaldirectivityindexofthevectorhydrophoneverticalarrayisnothigherthanthatofavectorhydrophone,thehigh-resolutionazimuthestimationalgorithmbasedonthedatafusionmethodwaspresented.TheproposedalgorithmfirstemploysMUSICalgorithmtoestimatetheazimuthofeachdividedsub-bandsignal,andthentheestimatedazimuthsofmultiplehydrophonesareprocessedbyusingthedatafusiontechnique.Thehigh-resolutionestimatedresultisachievedfinallybyadoptingtheweightedhistogramstatisticsmethod.TheresultsofthesimulationandseatrialsindicatedthattheproposedalgorithmhasbetterazimuthestimationperformancethanMUSICalgorithmofasinglevectorhydrophoneandthedatafusiontechniquebasedontheacousticenergyfluxmethod.Thebetterperformanceisreflectedintheaspectsoftheestimationprecision,theprobabilityofcorrectestimation,thecapabilitytodistinguishmulti-objectsandtheinhibitionofthenoisesub-bands.

简介：TheDirectionsofArrivals(DOAs),speedsanddistancesoftargetsareallrequiredforarraysignalprocessing.Basedontheperiodicphaseshiftofcoherentpulsesequencewaveform,anewestimationofmulti-targets'2-Dimentional(2-D)DOAangle,Dopplerfrequencyshiftandrelativetime-delayisproposed.Basedonavirtualsensorarrayconstructedbypulsecumulating,theestimationsofazimuth,elevation,Doppierfrequencyshiftandtime-delaycanbeobtainedsimultaneously,andtheleastnumberofpulsescouldbetwo.Thismethodiscomputationallyefficienteveninheaviernoisedenvironment,andallestimationsareautomaticallypairedincalculationprocesswithnospectrumsearching.Furthermore,thisalgorithmcanbeusedtoanyplanesensorarrayanddealwithmanytargetsatthesametimeonlybyfewsensors.Thetargetsnumberthatcandealwithsimultaneouslyisseveraltimestothesensornumber,whichistheupperlimitfornormalalgorithmssuchasESPRITandMUSIC.Thesecharacteristicswouldbeveryuseful,especially,foraerialsystems.Simulationsdemonstratethecapabilitiesofthismethodefficiently.