The Aircraft Partial Stealth Characteristic Analysis Algorithm Study

Stealth aircrafts adopt contour design and coating system to achieve ‘invisible'.RCS(Radar cross section)is the indicator which is used to evaluate performance of stealth aircrafts.RCS detection is mainly conducted through indoor near field scanning and outdoor far field scanning.Indoor scanning can provide high accurate and confidential test.Further more,near field to far field transform(NFFFT)is applicable to transform the near filed data into far field in order to conduct RCS testing.During stealth aircrafts' serving lives,the stealth aircrafts are deployed in various environments.Obviously,coating system failure will enlarge stealth aircrafts' RCS which make them more detectable by surveillance radars.It is reasonable to conduct a RCS test target at the places where coating system failure easily occurs.Since partial RCS test can only be operated in the near field,then NFFFT has to be used to calculate far field distribution.The basic theory of NFFFT is studied,a new algorithm based on traditional sphere wave scanning algorithm through circular scanning(CNFFFT)is advanced.The CNFFFT algorithm involves the special functions(Bessel function and Hankel function),which is difficult to be applied into practical engineer applications.Therefore,it is necessary to improve the programming ability of CNFFFT algorithm.In this paper,we present an improved CNFFFT algorithm,which can be adopted in practical engineer applications.The algorithm uses asymptotic function to simplify Bessel function and Hankel function.HFSS is used to calculate the near field distribution of objects.MATLAB is used to process near field data.A half wave dipole antenna is used to verify the practicability of algorithm,an angle reflector is used to verify the accuracy of algorithm and a microstrip antenna is used to analyze coating failure.The result of the comparisons between theory far field distribution and far field distribution is processed by improved CNFFFT algorithm.The results show that improved CNFFFT algorithm is reliable and able to be used in real engineer application.And the improved CNFFFT algorithm can be used in RCS analysis.