Mission Planning Of Earth Observation Satellite For Emergency Management Information Support

The mission planning of Earth observation satellite(EOS)can fully exploit its remote sensing information acquisition capability of "barrier-free observation",to achieve high timeliness and diversity of remote sensing information acquisition,to meet the timeliness and diversity requirements of emergency management information support,and to effectively support and assist emergency management in making timely and accurate action decisions.In particular,the new generation of Earth observation satellites have the super remote sensing information acquisition capability,that is "Visibility is Observation".The aim is to fully exploit this super remote sensing information acquisition capability to achieve "more","faster","better" and " more economical" remote sensing information acquisition,and finally meet the increasingly rich information support requirements of emergency management.On the one hand,focusing on three new types of observation capabilities of EOSs,including task clustering,non-tracking imaging and variable image duration,this paper conquered observation scheduling for the new generation of EOSs,and fully stimulated the application effectiveness of the above three new observation capabilities of EOSs.On the other hand,facing the contradiction between s the superb remote sensing information acquisition capability and the sluggish development of data reception capability,this paper analyzed and summarized the characteristics of image data downlink of the new generation of EOSs,such as the huge amount of data formed by each observation,the huge demand for image data transmission and the relatively backward data transmission/reception capability,and then overcame image data downlink scheduling technology for the new generation of EOSs,which has to a certain extent alleviated the bottleneck of satellite imaging data playback caused by the delayed development of data reception capability.The main research contents and innovative results of this paper can be summarized as follows.Firstly,taking into account the advantages("faster,more accurate,more stable" attitude maneuverability)and disadvantages("narrower" field of view)of(semi-)agile earth observation satellites((S-)AEOSs),this paper proposed a new task clustering:comprehensive task clustering(CTC),and defined a computational model of satellite energy consumption for task clustering.To optimize the loss rate of image quality and energy consumption simultaneously,the observation scheduling problem for agile earth observation satellite with comprehensive task clustering(OSWCTC)was constructed as a discrete bi-objective optimization models.In addition,combining an adaptive large neighborhood search algorithm(ALNS)and a nondominated sorting genetic algorithm II(NSGA-II),an adaptive multi-objective memetic algorithm,named as ALNS+NSGA-II,with strong scalability was designed for the first time.The rich and diverse simulation experimental analysis results demonstrated that CTC can effectively improve the comprehensive gain of(semi-)agile imaging satellites in acquiring remote sensing information.Secondly,in order to overcome the problem of infinite number of non-tracking imaging directions of complete agile earth observation satellites(CAEOSs),Envelope partition set was proposed.In addition,combined with the characteristics of active imaging(or non-tracking imaging),this paper defined the cumulative imaging quality of CAEOSs for the first time,which portrayed the imaging quality change during the whole observation,and then defined the energy consumption calculation model for multi-strip imaging.To optimize both the cumulative imaging quality of CAEOSs and the energy consumption of multi-strip imaging,the multi-strip observation scheduling problem for an agile earth observation satellite(MOSP)was constructed as a discrete bi-objective optimization model.The rich and diverse results of simulation experiments and analysis confirmed that Envelope partition set effectively balances the quality and time consumption for solving MOSP and ensured the timeliness of observing ground targets by CAEOSs.In addition,a systematic test case generation method for observation scheduling problem of CAEOSs(OSPFAEOS)was proposed in this paper.Thirdly,another new feature,variable image duration,of CAEOSs was investigated.This paper enriched the energy consumption calculation model of CAEOSs,and for the first time,the observation scheduling problem for CAEOSs with variable image duration(OSWVID)was constructed as a discrete bi-objective optimization model.In addition,ALNS+NSGA-II was extended,and two other multiobjective algorithms,PD+NSGA-II and LA+NSGA-II,were proposed.Based on the test case generation method for OSPFAEOS,a rich variety of test scenarios were generated,and the performance of three types of multi-objective algorithms for solving OSWVID was analyzed in multiple measures.The results showed that ALNS+NSGAII was more suitable for solving OSWVID because it can search for better and more diverse elite solutions in less algorithm running time and more stably.Fourthly,toward "Segmentation" and "Rearrange",this paper presented a dynamic satellite image data downlink scheduling(D-SIDSP)for the first time in this paper,and then proved D-SIDSP was NP-Hard in theory.In order to optimize both the image data transmission failure rate and the service-balance degree of EOSs,D-SIDSP was constructed as a discrete bi-objective optimization model.The rich and diverse simulation experimental analysis results confirmed that "Segment & Rearrange" not only facilitated transmitting more and higher priority imaging data,but also enabled the full and balanced use of the transmission window.In addition,this paper extended ALNS+NSGA-II,and then designed three other multi-objective modal algorithms:GRASP+NSGA-II,EC+NSGA-II and SA+NSGA-II.The results of the simulation experiments revealed that ALNS+NSGA-II was more suitable for solving D-SIDSP.Note that,this paper also proposed a systematic test case generation method for image data downlink problem for the new generation of EOSs.Finally,facing the contradiction between s the superb remote sensing information acquisition capability and the sluggish development of data reception capability,in order to transmit the rich and diverse remote sensing information acquired by EOSs to the ground stations as much and fast as possible,this paper deeply investigated the integrated scheduling problem for earth observation satellites(ISPFEOS).The problem components of ISPFEOS were systematically sorted out and modeled in a normalized manner,and three integrated scheduling frameworks were proposed: Separated scheduling framework(SSF),Compromised scheduling framework(CSF)and Coordinated integrated scheduling framework(CISF).In addition,the loss rate of data capturing and the energy consumption were also optimized to construct ISPFEOS as a discrete bi-objective optimization model.The results of a large number of simulations showed that CISF not only helped EOSs observed more ground targets with higher priority and provided more information support with higher benefit,but also was good for saving the energy consumption.Moreover,this paper proposed a c systematic test case generation method for ISPFEOS.