Study On ISAR Imaging Of Maneuvering Target And Feature Extraction Of Space Targets

Radar,as a kind of sensor that can detect,locate and identify targets in all-weather,has always been the focus of global research.High resolution synthetic aperture radar(SAR)and inverse synthetic aperture radar(ISAR)imaging technology,as an important branch in the history of radar development,can more intuitively and accurately depict the structural information of the target,and has been highly valued by military and civil.ISAR imaging,as a technology that can acquire the image of non-cooperative target from a long distance,plays an important role in target classification and recognition in the military field.The key condition of ISAR imaging is the rotation of target relative to radar.But for non-cooperative targets at long-distance,their motion is often very complex.In the case of low resolution radar,the rotation of the target in a short period of time can be regarded as uniform rotation,and a good image can be obtained by traditional phase compensation technology,such as phase gradient autofocus(PGA).However,when the resolution of radar is high,the radar echo of non-cooperative target can be represented by multi-component polynomial phase signal after motion compensation.How to compensate the multi-component polynomial signal by signal processing method becomes the key to obtain high-quality and high-resolution ISAR image.On the other hand,ISAR image contains abundant information of target structure,attitude and size,how to extract these information from ISAR image is one of the important research directions to provide strong technical support for target classification,recognition and cataloguing.Now ISAR imaging technology has developed to a higher level,but there are still many problems to be solved for ISAR imaging and ISAR image feature extraction technology of maneuvering targets.In this dissertation,the above two aspects are divided into three parts:In the first part,the problem of time selection for ISAR imaging of maneuvering target is studied.In the third chapter of this dissertation,a method of target attitude angle estimation based on aircraft tracking information and optimal selection of ISAR imaging time period is proposed.According to the aerodynamic model,the relationship between the change of aircraft attitude(yaw,pitch,and roll)and the change of velocity is established.Through the analysis of Doppler in radar echo,it can be found that the change of Doppler is directly related to the change of aircraft attitude: the change of attitude is stable,and the Doppler is approximately constant.The change of Doppler determines the imaging quality of ISAR: the smaller the Doppler change,the higher the imaging quality.This shows that the attitude angle change of target can be evaluated,and the time period when the attitude change is stable is the time period with high ISAR imaging quality.Based on the above conclusions,the proposed algorithm estimates the target attitude through extended Kalman filter based on radar tracking data,and introduces the concept of attitude angle linearity to evaluate the linearity of attitude angle in different time periods to realize the optimal selection of ISAR imaging time period.Compared with the traditional methods based on image analysis and Doppler analysis,the proposed method does not rely on the radar echo of the target,only needs the tracking information of the target,so it has certain noise robustness.Experimental results based on Simulation and experimental data show that the proposed algorithm has a more robust ability to select the imaging time period at low SNR.In the second part,the phase compensation of ISAR imaging for maneuvering target is studied.The nonuniform three-dimensional rotation of the target will cause the image projection plane(IPP)of ISAR to change continuously,thus resulting in two-dimensional space variant phase error.In this case,the traditional compensation method will make the ISAR image seriously blurred.On the other hand,the influence of strong noise on the traditional methods of motion parameter estimation and phase error compensation can not be ignored.In Chapter 4,a two-dimensional space variant phase error method based on parametric minimum entropy optimization is proposed.In the proposed method,the target attitude(yaw,pitch,and roll)changes are approximated to the second-order form,and the specific expressions of the two-dimensional air-varying phase error parameters of the aircraft target are derived.On this basis,the minimum entropy optimization function of the two-dimensional air-varying phase error is established.The phase error parameters are roughly estimated by using the aircraft target attitude estimation method proposed in Chapter 3 as the initial iteration Value improves the speed and precision of iterative search.Compared with the traditional space variant phase error compensation method,the proposed algorithm only needs to estimate two phase error parameters considering the integrity of the target motion,which significantly reduces the computational complexity.In addition,the proposed coarse phase error estimation method improves the speed and accuracy of the minimum entropy optimization search,and makes the proposed algorithm have stronger noise robustness.Experimental results based on Simulation and experimental data show that compared with the traditional methods,the proposed algorithm has low computational complexity,has good phase compensation ability when the signal-to-noise ratio is not less than-15 d B,and the obtained focused image has lower entropy value than the traditional method,and the quality of ISAR image is higher.In the third part,the method of space object physical feature extraction based on ISAR image is studied.The attitude and geometric characteristics of satellite target are important information for satellite activity analysis.In the fifth chapter of this dissertation,an estimation method of satellite target absolute attitude and size parameters based on ISAR image sequence is proposed.The proposed method takes the satellite subject as the research object,and proposes an ISAR image segmentation method based on pix2 pix generic adversarial network(pix2pixgan)to segment the satellite subject from the sequence of ISAR images.Furthermore,based on the projection theory of ISAR imaging,the optimization function of satellite attitude and size is established.The principal component analysis(PCA)method is used to extract the two-dimensional characteristics of the main body of the satellite.The traditional three-dimensional reconstruction method based on factor decomposition obtains the unknown rotation between the three-dimensional point distribution and the real three-dimensional point distribution,so it can only estimate the absolute size of the target,but not the attitude.The proposed method can estimate the attitude and size of the target at the same time.In the experiment,the satellite tool kits(STK)are used to simulate the actual orbit movement and radar observation angle of Tiangong and keyhole satellite targets,and the radar echo of the two satellites is simulated by using the electromagnetic simulation software FEKO under the corresponding perspective according to the computer aided design(CAD)model of the two satellites.Experimental results based on simulation data show that the proposed algorithm can not only estimate the satellite attitude and size simultaneously,but also estimate the satellite size more accurately than the factor decomposition method.