Multiple Moving Targets Tracking For Through-wall-imaging Radar

Through-wall imaging radar can help people to obtain some important information about the detection area,such as the number of targets,targets location.And it provides strong support to related people who are in capture operation,disaster rescue,and anti-terrorism.In this thesis,the imaging method,targets detection and localization algorithms and tracking systems under point target module and extended target module are discussed.The rest of the thesis is organized as follows:1.The echo model of through-wall radar is studied.The relations between fixed background clutter,multipath clutter and the targets on range profile are analyzed.An improved three pulse cascaded canceller and a multipath suppression method based on mask matrix is proposed to restrain the disturbance.And the experiment data testify the effectiveness of the proposed algorithms that it can increase the SCR.The imaging method based on back-projection algorithm is studied.In term of obtaining the targets position,detection and localization algorithm based on imaging processing is proposed and it is validated by measured data that the proposed algorithms can extract targets position effectively.2.Point targets dynamic model is discussed under the through-wall radar framework and the proper dynamic model is given according to the targets properties in actual scene.Aiming to deal with the detection and localization problem caused by wall,the measurement-to-track data association accuracy is improved through integrating NNCJPDA method with amplitude information.In order to track high maneuvering targets in enclosed environment,targets trajectory are updated by interacting multiple model(IMM)estimation algorithms,and the filters of the IMM algorithms are designed by targets properties.In order to track the weak targets,a multiple moving human targets track-before-detect algorithm based on dynamic programming is proposed.The measured data and simulation data testify the proposed its validity.3.The measurement-to-track data association algorithms based on clustering are studied.For the extended characteristics of the targets measurements after imaging,an extended targets tracking algorithm is introduced into the field of through-wall radar tracking,which uses a positive definite symmetric matrix to describe targets shape features.The measured data and simulation data verify that the algorithm has a stable tracking accuracy in case of low loss rate.Under the assumption that a target can generate more than one measurement after detection and localization algorithms,a multiple-detection joint probabilistic data association filter is introduced to solve the through-wall radar extended targets tracking problem.The measured data and simulation data demonstrate that the algorithm has a high tracking accuracy when there are few targets in the detection zone.According to the problems appeared in the practical application,this thesis studies the multiple moving targets tracking algorithms based on a large amount of experiments.The main technology are introduced in this thesis include detection and localization methods,multiple moving targets tracking algorithms under both point target and extended target model.The research result will make benefit for the development of the through-wall imaging radar.