Study On Imaging Algorithm And Autofocus Algorithm For Multi-rotor UAV SAR

The traditional Synthetic Aperture Radar(SAR)system is usually installed on the aircraft or satellite platform,but the high cost and complex operation limit the application.Multi-rotor UAV SAR has attracted much attention due to its economy,portability,easy operation and wide application fields and becomes increasingly a popular research hotspot in the field of SAR.However,low flying height and the poor self stability of multi-rotor UAV result to its unstable flight speed and complicated flight trajectory.High efficient and accurate imaging processing needs the complex motion compensation processing.Moreover,since the limitation of volume and weight,multi-rotor UAV SAR is usually unable to install high-precision motion sensors(such as GPS and IMU),which makes the motion parameter estimation and compensation inevitable.This thesis probes into some key problems faced by imaging processing of multi-rotor UAV SAR,and proposes effective imaging processing scheme.The main work of this thesis is arranged as follows:Chapter 1 briefly introduces the research background and significance,reviews the origin and development history of SAR technology,describes key problems with multi-rotor UAV SAR imaging,finally introduces the main work and structure of this thesis.Chapter 2 introduces the principle and advantages of Dechirp technology as well as the imaging principle of polar format algorithm(PFA)and back projection algorithm(BP).Chapter 3 proposes an autofocus algorithm based on improved MD technology.By this method we can estimate real-time velocity and compensate the motion error of multi-rotor UAV SAR effectively,simulation and measured data experiment verify the effectiveness of the proposed method.Chapter 4 firstly introduces the PGA algorithm.Aiming at the PFA algorithm,we analyse the phase error model of PFA image and introduce the two dimension autofocus technology.According to the BP algorithm,we research the spectrum form of BP image,and propose a spectrum alignment correction method,and PGA is applied to the corrected BP image.Chapter 5 makes a brief summary of the research contents of the full thesis,points out the existing problems and shortcomings,gives valuable suggestions and makes a prospect for the future research.