15262

13717

كارشناسي ارشد

برق

اصفهان : دانشگاه صنعتي اصفهان

1398

يازده، 88ص. : مصور، جدول، نمودار

احسان يزديان

محمود مدرس هاشمي، محمدرضا تابان

1398/08/13

كتابنامه

مهندسي برق

مهندسي برق و كامپيوتر

1398/08/13

2572772

Using microdoppler of radar return signal to extract the characteristics of helicopter Fatemeh HamedaniGolshan f hamedani@ec iut ac ir September 18 2019 Department of Electrical Engineering Isfahan University of Technology Isfahan 84156 83111 IranDegree Master of Science Language FarsiSupervisor Ehsan Yazdian Assist Prof yazdian@cc iut ac ir AbstractMicrodoppler is a new subject in radar signal processing with a research history of about twenty years Radialvelocity of targets relative to radar position causes doppler frequency shift of return signal to radar In additionto radial velocity of target fuselage many targets consist of components which have small scale motions whichresults in frequency modulation around the main doppler frequency shift Vibrations of the motor componentsand fuselage of airplanes and blade rotation of helicopters are some examples of these types of small scalemotions which produce periodic doppler shifts known as microdoppler Extraction of microdoppler shift andits properties is very important in target classifications and estimating many parameters of the target In thisstudy we focus on microdoppler properties of return signal of radar from helicopter Estimation of helicopterparameters such as number of blades their length and velocity of angular rotation and finally identification ofhelicopter type are aims of this research For this purpose the previous methods for estimating the helicopterparameters are reviewed and classified and especially compressive sensing approach is studied as an innovativemethod In previous researches on applications of compressive sensing in microdoppler estimation atomsof dictionary matrix are constructed based on the received signal from one rotating object In this researchemploying these methods to solve the problem of estimating the parameters of helicopter we improve theperformance by defining the atoms of dictionary based on model of entire return signal including all components We employ Orthogonal Matching Pursuit OMP algorithm to solve the problem In order to encounter problemof mismatching parameters to the predefined atoms dictionary learning method is employed The obtainedresults show that accuracy of estimation increases in the case of using dictionary learning in the case of rotorblade length Finally advantage of method based on compressive sensing is showed in comparison with IRadontransform as one of the well known time frequency domain methods is presented which confirms the superiorityof the proposed CS method KeywordsMicroDoppler Helicopter Radar parameter estimation compressive sensing

احسان يزديان

محمود مدرس هاشمي، محمدرضا تابان