DESIGN AND REALIZATION OF SOFTWARE FOR IDENTIFICATION AIRCRAFT TYPE BASED ON SPEED AND RADAR CROSS SECTION USING NEURAL NETWORK TYPE BACKPROPAGATION

• Main Author: DARUSMAN (NIM: 13202182), MAMAN
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/12352
• Institution: Institut Teknologi Bandung

Radar used in military to detect aircrafts that operating on the air. Radar can measure speed and radar cross section (RCS) of the aircraft. Because every type of aircraft has different speed and radar cross section, so by knowing speed and radar cross section will be known type of the aircraft. Benefit of knowing type of aircraft that detected by radar namely military can overcome threats caused by the aircraft because military can know it's strong and weakness.<p>In this final project research, it is designed and made a software for identification of aircraft type based on speed and RCS uses algorithm neural network type backpropagation. Software is made use Matlab version 7.0 by using neural network toolbox. As study case, it is collected eight data about aircraft type, it’s speed and it's radar cross section.<p>After performed experiment, derived condition of neural networks that have most optimal performance that is be able to achieve mean square error (MSE) in less epoch number. Then made software uses network on this condition. The software is simulated. The result is software can identified aircraft type from speed and RCS data that input. Data that have value near to data on database will result aircraft type that equal with resulted by data on database.