Research On RCS Measurement And Imaging Of Targets In Terahertz Band

The terahertz wave has higher imaging resolution than microwave, and stronger penetrate ability than infrared and light. Thus, the terahertz radar has a vast potential for future development in military, medical and security check. The research on targets' RCS properties and imaging are the technology base for terahertz radar used in both military and civil applications. While, because of the shorter wavelength, phase sensitive and immature generation and detection technology in terahertz band, the calculation, measurement and imaging of targets are faced with big problems needed to be studied. Therefore, this paper carries out research on this problems and the research background mainly include the RCS laboratory measurement and detection in SAR.In order to tackle the problems in RCS calculation and measurement of targets, this paper focus on the RCS simulation based on electromagnetic computing software and RCS measurement based on the experiment system. We at first utilize the software FEKO and CST to calculate the RCS value of perfect sphere, cylinder and rectangular plate in three frequency point including 0.3THz?1THz?2THz, and compare the simulation performance of different software. Secondly, the RCS measurement based on TDS system is implement, and through the comparison of smooth and rough cylinder's measured RCS, we found that the higher frequency the greater impact of rough surface on RCS in terahertz band, and the traditional definition of rough surfaces which roughness more than one eight of the wavelength is not suitable in terahertz band any more. Finally, the RCS measurement of different standard targets and car model based on terahertz radar system utilizing microwave multipliers is fulfilled.To avoid the defocus of range profile caused by phase errors in the terahertz experiment system, we proposed two different phase compensation methods. This paper mainly focus on two types of phase errors: random phase errors and phase errors caused by waveform nonlinearities. Firstly, a method based on the Bayesian compressive sensing is proposed to correct the random phase errors. The method build the echo model contain the random phase errors, use the maximum likelihood estimation method to estimate the phase errors, and compensate the errors through the loop iteration of phase errors estimation and targets reconstruction. On the other hand, to compensate the phase errors caused by waveform nonlinearities, we introduce the azimuth autofocusing in SAR to the autofocusing of nonlinearity errors. The method is based on the phase gradient autofocus algorithm, and it can not only adapt to the change of nonlinearity but also eliminate the error caused by phase periodic discontinuity of the dechirped FMCW signals. More importantly, the autofocusing approach is validated by real data obtained from the THz radar.To realize the simulation of the FMCW SAR in terahertz band, we at first discuss the system simulation parameters of terahertz FMCW radar, and then build the model of targets echo. Consequently, whether the stop-and-go assumption is available in terahertz SAR imaging is analyzed. Finally, we proposes a imaging algorithm for terahertz FMCW SAR based on the Bayesian compressive sensing, and obtain the SAR imaging of T64 tank model. Through the analysis of the imaging results, we found that the tank have different characters in different imaging azimuth and the imaging algorithm we proposed have a preferable performance.