简介：SurfacePenetratingRadar(SPR)isarecentlydevelopedtechnologyfornon-destructivetesting.Itcanbeusedtoimageandinterprettheinnerstructureofthereinforcedconcrete.ThispapergivesthedetailsaboutacompactandhandheldSPRdevelopedrecentlyforreinforcedconcretestructuredetection.Thecenteroperationfrequencyoftheradaris1.6GHz.Notonlyithasfastacquisitionability,butalsoitcandisplaythetestingresultontheLCDscreeninreal-time.Thetestingresultsshowthattheradarhasapenetratingrangeofmorethan30cm,andalateralresolutionbetterthan5cm.Theperformancevalidatesthattheradarcanmeettheapplicationrequirementsforreinforcedconcretestructuredetection.

简介：Opportunisticarrayradar(OAR)isanewgenerationradarsystembasedonthestealthoftheplatform,whichcanimprovethemodernradarperformanceeffectively.Designingtheorthogonalcodesetswithlowautocorrelationandcross-correlationisakeyissueforOAR.Thispaperproposesanovelhybridgeneticalgorithm(HGA)anddesignsthepolyphaseorthogonalcodesetswithlowautocorrelationandcross-correlationproperties,whichcanbeusedintheOARsystem.Thenovelalgorithmcombineswithsimulatedannealing(SA)andgeneticalgorithm(GA),addsinkeepingbestindividualsandcompetitioninsmallscope,andintroducesgreycorrelationevaluationtoevaluatefitnessfunction.TheseavoidtheprematureconvergenceproblemexistedinGAandenhancetheglobalsearchingcapability.Atlast,thegeneticresultsareoptimizedtoobtainthebestsolutionbyusinggreedyalgorithm.ThesimulationresultsshowthattheproposedalgorithmiseffectiveforthedesignoforthogonalphasesignalsusedinOARsystems.

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简介：Thispaperdiscussestheproblemofdirectionofdeparture(DOD)anddirectionofarrival(DOA)estimationforabistaticmultipleinputmultipleoutput(MIMO)radar,andproposesanimprovedreduced-dimensionCaponalgorithmtherein.Comparedwiththereduced-dimensionCaponalgorithmwhichrequirespairmatchingbetweenthetwo-dimensionalangleestimation,theproposedalgorithmcanobtainautomaticallypairedDODandDOAestimationwithoutdebasingtheperformanceofangleestimationinbistaticMIMOradar.Furthermore,theproposedalgorithmhasalowercomplexitythanthereduced-dimensionCaponalgorithm,anditissuitablefornon-uniformlineararrays.ThecomplexityoftheproposedalgorithmisanalyzedandtheCramer-Raobound(CRB)isalsoderived.Simulationresultsverifytheusefulnessoftheproposedalgorithm.

简介：追踪作为多尺度知道的算法追踪雷达的新雷达回响回应由跨关联(MTREC)在这研究被开发在不同空间规模分析雷达回响的运动。雷达回响的运动，特别地与对流暴风雪联系了，在导致对流暴风雪的形成的气象学的系统之中由于复杂相互作用在各种各样的空间规模展出不同特征。为空回响区域，平常的关联技术生产零或运动向量的很小的大小。减轻这些限制，MTREC由关联(TREC)使用追踪的雷达回响有一个大盒子的技术驾驶风驾驶的系统的运动，和MTREC与一个小盒子使用TREC技术决定估计小规模的内部运动向量。最后，MTREC向量被综合获得系统的运动和小规模的内部运动。MTREC技术的性能与用案例研究的TREC技术相比：Wenzhou雷达和一个嚎啕线系统在2005年9月11日在2011年6月23日观察的Khanun台风由北京雷达检测了。结果证明那更空间地变光滑，连续向量领域能被MTREC技术产生，它在追踪全部雷达反射率模式导致改进。新多尺度的追踪计划被使用在量的降水nowcasting的表演上学习它的影响。在一1-h铅时间的重降水的地点和紧张与使用雷达和雨计量器的量的降水估计更一致。

简介：Abi-caponbeamforming(BCB)algorithmformulti-inputmulti-output(MIMO)radarisdevelopedonthebasisofcorrelationdomain.Byvectorizingtheechomatrixanditstranspose,theconventionalcaponcostfunctionistransformedintobi-caponquadraticfunctions.Bycalculatingtwolowerdimensionalweightvectorswithsub-matricesofthecorrelationmatrix,BCBcansignificantlydecreasethecomputationalcomplexityandtherequirementoftrainingsamples.Inthepresenceofshortdatarecords,BCBcanachievebetterinterferencesuppressionperformancethanfullyadaptivecaponalgorithm.Simulationresultsarepresentedtodemonstratetheeffectivenessoftheproposedmethod.

简介：Usingultrashort-pulseradarwithcompactvivaldiantennas,thesimulationexperimentofbreastcancerdetectionhasbeenperformedinasyntheticbreastphantom.Twometallicballswith9mmand6mmindiameterareusedastumorsinourexperiment.Theimagereconstructionsofthebreastmodelswithtumorsusingreflectiondatahavebeenpresentedbyaconfocalmicrowaveimagingtechnique.Themethodcanbeusedforapulsecompressiontechniquetoreflectedwavesforclearimageformation.

简介：Duetothedemandofdataprocessingforpolariceradarinourlaboratory,aCurveletThresholdingNeuralNetwork(TNN)noisereductionmethodisproposed,andanewthresholdfunctionwithinfinite-ordercontinuousderivativeisconstructed.ThemethodisbasedonTNNmodel.InthelearningprocessofTNN,thegradientdescentmethodisadoptedtosolvetheadaptiveoptimalthresholdsofdifferentscalesanddirectionsinCurveletdomain,andtoachieveanoptimalmeansquareerrorperformance.Inthispaper,thespecificimplementationstepsarepresented,andthesuperiorityofthismethodisverifiedbysimulation.Finally,theproposedmethodisusedtoprocesstheiceradardataobtainedduringthe28thChineseNationalAntarcticResearchExpeditionintheregionofZhongshanStation,Antarctica.Experimentalresultsshowthattheproposedmethodcanreducethenoiseeffectively,whilepreservingtheedgeoftheicelayers.

简介：TheHongKongObservatory(HKO)provideslow-levelturbulencealertingservicefortheHongKongInternationalAirport(HKIA)throughthewindshearandturbulencewarningsystem(WTWS).IntheWTWS,turbulenceintensitiesalongtheflightpathsoftheairportareestimatedbaseduponcorrelationequationsestablishedbetweenthesurfaceanemometerdataandtheturbulencedatafromresearchaircraftbeforetheopeningoftheairport.Theresearchaircraftdataarenotavailableonday-to-daybasis.Theremotesensingmeteorologicalinstruments,suchastheDopplerlightdetectionandranging(LIDAR)andradar,maybeusedtoprovidedirectmeasurementsofturbulenceintensitiesovertherunwaycorridors.TheperformancesofLIDAR-andradar-basedturbulenceintensitydataarestudiedinthispaperbasedonactualturbulenceintensitymeasurementsmadeon423commercialjetsforatypicalcaseofterrain-inducedturbulenceinassociationwithatyphoon.Itturnsoutthat,withthetuningoftherelativeoperatingcharacteristic(ROC)curvebetweenhitrateandfalsealarmrate,theLIDAR-basedturbulenceintensitymeasurementperformsbetterthantheanemometer-basedestimationofWTWSforturbulenceintensityatmoderatelevelorabove.Ontheotherhand,theradar-basedmeasurementdoesnotperformaswellwhencomparedwithWTWS.BycombiningLIDAR-andradar-basedmeasurements,theperformanceisslightlybetterthanWTWS,mainlyasaresultofcontributionfromLIDAR-basedmeasurement.Asaresult,theLIDAR-basedturbulenceintensitymeasurementcouldbeusedtoreplaceanemometer-basedestimatefornon-rainyweatherconditions.Furtherenhancementsofradar-basedturbulenceintensitymeasurementinrainwouldbenecessary.