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- W2187148935 abstract "Inthepaperanewapproach forestimating the radarsignal multivariate probability density issuggested. Itis basedontheuseofaprojection ofarandomprocess tothesetof randomvariables, withtheprobability density defined asa productoftwo-dimensional densities. Theestimates oftwo- dimensional probability densities areobtained withthehelpof filtering thetwo-dimensional characteristic function. Soweare suggesting a nonparametric estimate ofthecharacteristic function. On thebasisoftheseestimates nonparametric algorithms ofsignal detection areconstructed. Examplesfor remotesensing ofatmosphere aresuggested. IndexTerms Probability, estimation, radardata processing. I.INTRODUCTION Itisveryimportant forremote sensing ofatmosphere to describe thereflected radar signal using themostprecise and accurate method. Ifweconsider that thereflected signal can bedefined assomestochastic process, thefullest description canbeobtained intheformofamultivariate density function. Usingthisapproach we cansolvedifferent problems. Measurement ofamultivariate probability density hasalways beenaverydifficult problem anduptorecent times ithasnot beenusedforradar exploration ofatmosphere because ofthe complexity of itspractical application. Moreoverin mathematical statistics goodnonparametric methodsof estimating multivariate probability densities havenotbeen developed. Themethod ofmultivariate histogram calculation israther roughandinexact. Theappearance offastand compact signal processors, fitforprocessing radar signals, andkernel methods ofestimating probability density allows ustofindacomprehensible solution ofthis tasknow.But evennowthis problem israther difficult. Thatiswhyitis veryinteresting tosuggest newsignal models whichsimplify this task. We suggest using aprojection ofarandom process tosomesimplified modelofamultivariate probability density function whichallows ustopresent themultivariate density function asaproduct oftwodimensional densities. Forestimating twodimensional densities themethodof building thekernel estimate ofa characteristic function is suggested. Theuseoftheestimate ofacharacteristic function, whichiscalculated withthehelpofthefastFourier algorithm, allows ustoincrease thespeed ofcalculations in comparison withcalculating estimates ofaprobability density function intimearea. Theresults oftheworkarenonparametric estimates of multidimensional probability density and characteristic function. Theseestimates canbeusedforthesynthesis of nonparametric signal detection andrecognition algorithms." @default.
- W2187148935 created "2016-06-24" @default.
- W2187148935 creator A5069970312 @default.
- W2187148935 date "2006-01-01" @default.
- W2187148935 modified "2023-09-27" @default.
- W2187148935 title "Projection Approach forEstimating RadarSignal Multivariate Probability Density" @default.
- W2187148935 hasPublicationYear "2006" @default.
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