On-line Channel Equalization Methods For Bistatic SAR

Bistatic Synthetic Aperture Radar(Bi SAR)is gradually evolving from a single receiving channel to multiple receiving channels,and it uses the method of increasing the degree of freedom in the airspace to improve the system's suppression performance of the main lobe clutter,so as to realize the detection of slow moving targets.Compared with the traditional single-base single-channel radar,the bistatic multi-channel SAR has many technical characteristics,such as flexible configuration,strong anti-interference ability,good concealment,anti-reconnaissance,etc,which make it have important application value in the military field.However,in actual application scenarios,the channel mismatch problem would seriously affect the results of clutter cancellation and moving target detection.Therefore,the problem of amplitude and phase error correction between channels has become an urgent issue.The key to the research of adaptive channel equalization lies in echo modeling,channel mismatch analysis,equalization algorithm research,migration curve extraction of strong point targets,separation of direct waves and echoes,etc.For the above questions,the main works of thesis are as follows:1.The geometric observation model of bistatic multi-channel SAR is built.The author analyzes the distance migration,Doppler and other characteristics of stationary targets.The multi-channel mismatch model of the receiving station is established to study the reasons for the inconsistency of the amplitude and phase between the receiving channels,and the necessity of online channel equalization technology for the bistatic multi-channel SAR system is explained.2.From the perspective of time domain and frequency domain,four channel equalization methods are studied.The author analyzes the advantages and disadvantages of current adaptive equalization algorithms,and proposes a least squares equalization method based on diagonal loading and an inverse Fourier equalization method that uses the average in-band frequency response to replace the out-of-band frequency response,in order to solve the problem of insufficient calculation accuracy of the adaptive filtering algorithm.Through point target and area target simulation,the effectiveness of each adaptive equalization algorithm is verified,which lays the foundation for the later development of online adaptive channel equalization methods.3.The author proposes two online adaptive channel equalization methods based on strong echo signals and direct wave signals,which realizes the extraction of strong point target echoes and the separation of strong direct wave signals and ground echoes.The problem that the error of the receiving channel changes with time is solved.4.Aiming at the channel equalization work of measured data,a new idea of combining particle swarm optimization(PSO)with online adaptive channel equalization method is proposed to achieve the selection of equalization filter parameters and the consistency calibration of the measured data.The effectiveness of the above methods has been verified by theoretical derivation,simulation experiments and measured data.The results prove that both methods of using echo strong point information and direct wave signals can achieve online adaptive channel equalization,and the channel equalization algorithm combined with PSO can correct the errors between channels more accurately and efficiently.