Research On Motion Compensation Algorithm For Inverse Synthetic Aperture Lidar Imaging

The resolution of conventional optical imaging systems is constrained by the diffraction limit,which makes it difficult to achieve centimeter-level resolution imaging of remote targets.Inverse Synthetic Aperture Lidar(ISAL)is a new optoelectronic imaging detection technology,whose resolving power is independent of the imaging distance in principle,and therefore plays an important role in application scenarios such as detecting and identifying targets in the distance.Target motion is a necessary condition for ISAL imaging,but the large amount of phase error introduced by the higher-order motion term can seriously affect the imaging quality.In view of the problem concerning the motion error compensation of ISAL imaging,a series of work has been carried out in this paper.Firstly,to address the problem that motion errors seriously affect the imaging quality,a high-precision ISAL imaging model is established,providing a theoretical basis for the design of subsequent error compensation algorithms.Based on the geometric model and signal model,the types of errors caused by the target motion are analyzed,which mainly include the envelope tilt error and intra-pulse Doppler phase error caused by the high-speed motion of the target,and the phase error introduced by the relative translation and rotation between target and lidar.The differences between optical ISAL and microwave ISAR motion error compensation accuracy are analyzed,and the high-precision envelope tilt correction is emphasized as a necessary prerequisite for accurate phase error estimation and compensation.Secondly,based on the high-precision ISAL imaging model,a motion error compensation method is designed,which mainly includes envelope tilt correction and phase error compensation.Specifically,according to the error compensation model,the problem characteristics to be optimized are clarified.Furthermore,a global joint motion error compensation algorithm for ISAL imaging based on DFP algorithm and bat algorithm is proposed.The algorithm first takes the image contrast as the evaluation index and uses the DFP algorithm to accurately estimate the target motion speed to complete the envelope tilt correction.Then it takes the image entropy as the evaluation index and uses the bat algorithm to globally estimate the target motion parameters,so as to achieve the goal of jointly compensating the rotation error and the translation motion error.The joint compensation can reduce the impact of the residual error on the imaging quality,finally obtaining a well-focused ISAL two-dimensional image.Then,numerical simulations are carried out based on the proposed motion compensation imaging algorithm.In the simulation experiments,the algorithm is verified with a high accuracy in estimating the target motion parameters and has the ability to remove the amplitude and phase noise.In envelope alignment,the velocity estimation error is mainly distributed between 0.2% and 0.6% for targets moving in different directions,and the offset caused by the residual error is less than 1/8 distance unit.In phase error compensation,the error estimation accuracy is further improved by improving the parameter initialization method of the bat algorithm,and the estimation error is mainly distributed between-0.2% and +0.2%,which is close to the real value.In the anti-noise experiment,compared with several other compensation algorithms,the algorithm proposed in this paper has a best compensation performance for amplitude noise and phase noise.Finally,based on the imaging model,an ISAL imaging experimental platform for composite motion targets is built on the basis of the experimental system of the subject group,and a series of imaging experiments are carried out for point targets and extended targets using a rotary table and a translation table.After completing the system debugging,we carried out outdoor 1km distance imaging experiments.In the single-point target experiments,we can achieve centimeter resolution in distance direction as well as millimeter resolution in azimuth direction,respectively,after data processing.The error with the theoretical resolution is only at millimeter and micron levels,and the effect of radial translation on phase distribution is analyzed through the composite motion experiments.In the multi-point target and extended target 2D imaging experiments,different phase error estimation and compensation methods are used to obtain high-resolution 2D images.The simulation and experimental results show that the global joint phase error compensation algorithm based on the bat algorithm proposed in this paper has the superior error compensation performance.