The Study On Measuring And High-Resolution Imaging Techniques With Wideband Radar

With the development of aerospace technology,aerospace vehicles have the properties of high speed,high maneuverability,and small size,which significantly threaten our county’s air and space security.So it is necessary to develop the technology of information perception and acquisition for air and space targets,realizing accurate status monitoring,image acquisition,and situational awareness.Wideband radar can detect a target with long distance in conditions of all-weather and all-time,and it can realize high-resolution imaging using synthesis aperture.Therefore,wideband radar is becoming the critical sensor to realize information perception and acquisition for air and space targets.Thus,digging wideband radar signals and optimizing signal processing ability to increase the abilities of measuring,tracking and imaging are very important.However,in the wideband radar’s measuring,tracking,and imaging processes,traditional methods always use the open-loop and separation processing mode to decrease processing difficulty and increase computational efficiency.In this way,only part of the target information is applied during processing,which has significant information loss and results in the problems of limitation of measuring accuracy,insufficient noise robustness,and low imaging efficiency.Therefore,it is crucial to fully exploit the wideband radar echo information to realize the measurement,tracking,and imaging technology without information loss,high time efficiency,and high precision.In addition,wideband radar imaging performance and transmitting waveform are tightly coupled,and traditional wideband radar waveform has the problem of superficial form.In this way,optimizing wideband waveform makes it crucial to realize high-resolution ISAR imaging with small resource usage in a complex electromagnetic environment for information perception and information acquisition.This dissertation utilizes the properties of wideband frequency,high resolution,and abundant target information to realize target measuring,tracking,and imaging of wideband radar.Four critical problems are researched: integrating tracking and measuring,tracking and imaging,ISAR imaging with sparse frequency waveform optimization,and ISAR imaging in a complex electromagnetic environment.Therefore,the research contents can be summarized as follows:In the first part,we study the integration of measuring and tracking methods with signal domain filter to decrease information loss in tracking and measuring;we introduce the complex-valued reference HRRP using coherent integration to preserve the target’s complete envelope,phase,and scattering properties.To realize integration processing mode,we construct the relationship between signal and data domains using the Bayesian inference model.The convex optimization method is used to estimate innovation and realize motion state updating.In addition,the method is also extended to tracking and measuring with multiple dimensional applications,realizing high accuracy,noise robustness,and multidimensional integration of tracking and measuring.In the second part,we studied the integration of measuring,tracking,and imaging.Traditional ISAR imaging uses the mode of "imaging after data collection," which has the problem of low efficiency.So we construct the Bayesian model to describe the relationships among the data domain,signal domain,and image domain to realize sequential measuring tracking and imaging for space and air vehicles.Aiming at the influence of the rotational phase on translational estimation,we propose the sub-aperture measuring and tracking method.We also introduce the decentralized filtering method to realize motion state fusion to decrease motion error in every sub-aperture.The motion state after fusion filtering can be directly used in motion compensation to realize real-time ISAR imaging.In the third part,we studied the sparse frequency waveform optimization for high-resolution ISAR imaging.We derive the range auto-correlation ambiguity function,analyze the reason for high grating lobes,and propose the waveform optimization method based on frequency steps and phase codes.Based on the proposed waveform,we proposed the method of motion compensation and sparse ISAR imaging method based on the Bayesian conjugate gradient method.We can realize ISAR imaging with high quality in low sparse degrees using the waveform optimization and sparse imaging method.In the fourth part,we studied the frequency and pulse repetition frequency(PRF)agility optimization for high-resolution ISAR imaging.Aiming at the complex electromagnetic environment,we proposed the frequency and PRF agility waveform to increase the antijamming and anti-interception ability.Aiming at the problem of choosing a frequency support set,we use the range autocorrelation function to select the frequency.To increase the performance of the Doppler estimation and imaging,we propose the agile frequency and PRF optimization method based on minimizing Doppler ambiguity side lobes.In addition,we also proposed a velocity estimation method based on agile frequency using maximum likelihood moving target detection(ML-MTD)and cognizing transmitting.Moreover,we also proposed the joint autofocusing and imaging method based on two-dimensional sparse reconstruction,and this kind of method has high efficiency compared with the traditional imaging method.