Research On Distributed Routing And Autonomy Levels For Space-Based Network

Recently,it is common that the volume of satellite data is rapidly increasing,the space-based network is constantly being built,and the demand for intelligent information integration is expanding.A evaluation model of autonomy needs to be rationally established to help analyze,evaluate,and facilitate technological advances in the autonomy of satellite networks.Moreover,with the continuous emergence of LEO communication mega-constellations and the increasing requirements for on-orbit autonomy,it is necessary to use distributed routing algorithms to help the selforganization and management of satellite networks,and to cope with sudden traffic fluctuations in the mobile communication market,as well as the local congestion caused by a highly uneven population distribution.However,the traditional distributed constellation routing algorithms have limited congestion control capability.And they are difficult to adapt to random network failures,to deploy in a multi-layer interconnected LEO satellite networks structure.Firstly,when applied to LEO mega-constellations,traditional distributed routing algorithms have limited congestion control capabilities and are not suitable for on-orbit autonomous network management.Therefore,a distributed routing algorithm was proposed based on local flooding optimization to improve performance.This algorithm collects ISL congestion status by the mechanism of local flooding.In this way,it can deal with the common congestion caused by the intensive local communication demand.Meanwhile,local path optimization is used to achieve traffic dredging and network load balancing with low computational overhead.In terms of characteristics,this proposed algorithm ensures that routing loops are avoided,can be applied to the multi-layer LEO satellite network,and has wide adaptability to satellite random failures.It is considerably beneficial to data transmission of common on-orbit tasks such as multisatellite collaborative observation and tracking.In addition,a routing simulation environment has been built for LEO mega-constellations,to simulates data packet transmission which is a type of multi-source concurrent and mutually influencing events.Simulation results indicate that this algorithm can reduce the packet loss rate by2%～10% in the case of high network load with uneven distribution of communication demand,and has robust performance against random network failures.Subsequently,for the autonomy modeling and evaluation of space-based networks,this dissertation proposes a novel hierarchical model based on the OODA loop and six corresponding levels that show a progressive relationship.Using the loop of "observation-adjustment-decision-action",multiple dimensions of the space-based intelligent network are modeled separately,such as the progressive relationship of "positioning → tracking → multi-target → fusion perception" for data processing,the progressive level of "local central structure → local distribution → global distribution→ space-earth integration" of network structure,and the scale level of "single satellite→ satellite cluster → local constellation → global constellation" of the intelligent agents,etc.The closed-loop degree of OODA loop is taken as the basis for classification.And for space-based intelligent networks at various levels,our model can reveal the differences in on-orbit task load capacity,behavioral autonomy,and application scenario limitations,showing the trend of satellite on-orbit intelligence technology with clear layers and key points.It is expected to facilitate understanding and evaluation of the technical levels of space-based intelligence,and provide a systematic overall outlook of demand and research.