Research On Ship Target Imaging Technology Based On Compressive Sensing For Bistatic Or Multistatic ISAR

Bistatic Inverse Synthetic Aperture Radar(Bistatic ISAR)provides diversity of target views due to its unique structure.The imaging structure and the imaging environment together affect the quality of the imaging.The sea surface environment is a special imaging environment.Under the influence of high sea conditions,the ship's target is complex and difficult to accurately estimate.The echo signal of the ship target received by the bistatic ISAR structure is non-stationary,the Doppler phase is time-varying,and the data is incomplete.If we use the traditional linear sampling method based on Range-Doppler imaging,the target image will be distorted.The Compressive Sensing(CS)theory has great advantages when dealing with data with nonlinear properties,sparsity,and other characteristics.Compared with the traditional methods of increasing signal bandwidth,using linear interpolation or all-pole models,we use compressive sensing imaging methods to obtain higher resolution radar images through nonlinear reconstruction.At the same time,the problem of incomplete echo data is solved,and the sampling rate of compressive sampling is far lower than the Nyquist sampling rate,and less measurement data is needed.This thesis applies compressive sensing technology to bistatic ISAR ship target imaging.To solve the problem of low resolution caused by time-varying Doppler and incomplete echo datasets of ship targets,we will focus on sparseness analysis and study from the following aspects:(1)The basic theory of compressive sensing imaging methods.The structure of the bistatic radar,the non-cooperativeness of the imaging target,leads to discontinuities in observations and incompleteness of echoes.The advantages of compressive sensing theory can solve problems such as high sampling rate,large amount of data,and short coherence time,and improve the resolution of radar images in complex environments.(2)Ship target imaging based on compressive sensing.The ship's target movement is influenced by the sea state and has non-stationary and time-varying characteristics.The Doppler shift required for imaging is provided using the swing of the ship target itself.The multi-base structure helps to obtain a two-dimensional view of the various imaging planes of the ship's target.Compressive sensing technology is introduced into the sea ship target imaging problem,and the sparse characteristics of ship target echo are used.(3)Compressive sensing imaging algorithm with missing data.Using a new sparsity analysis method,sparsity is obtained from the spatial distribution characteristics of the target reflection features.The impact of the scene on the transmitted signal is modeled as a generalized linear operator.Using very few pulses to get the target's range and Doppler super-resolution.Solving the problem of missing data in the received dataset.At the same time,the limitation of the two-dimensional resolution by the radar ambiguity function and the time-frequency uncertainty principle has been overcome.