818 results about "Low earth orbit" patented technology

The invention discloses a multi-beam cooperative scheduling method and a multi-beam cooperative scheduling system for low-orbit satellite communication, which mainly solve the problems of poor beam scheduling flexibility and difficulty in adapting to time-varying requirements in a high-dynamic environment in the prior art, and the implementation scheme of the multi-beam cooperative scheduling method comprises the following steps of: collecting online user information by a low-orbit satellite through a wide beam; a hopping beam position is generated by using adaptive clustering under the constraint of channel resources; a hopping beam scheduling algorithm based on deep reinforcement learning outputs an optimal scheduling strategy according to the real-time environment variable; and optimizing a beam hopping time frame structure in each scheduling period, covering accessed users in a beam position through spot beams, and sending service data and control information to complete efficient service transmission. The method can adapt to changes of user distribution and service requirements in low-orbit satellite communication, the utilization rate of spectrum resources is improved, communication delay is reduced, the overall performance and service quality of the system in a high-dynamic environment can be enhanced, and the method can be used for dynamic beam position division, hopping beam scheduling and hopping beam resource allocation in a multi-beam low-orbit satellite communication scene.

An intention-driven low-orbit satellite network SRv6 routing management and control method comprises the following steps: step 1, receiving and analyzing a user service demand from an application layer, and generating a corresponding intention label according to a service type; step 2, collecting state information of a satellite network in real time, tracking and recording satellite node position change and link state conversion, and establishing a complete network state database; 3, calculating a routing path meeting the service quality requirement by adopting an improved breadth-first search algorithm; 4, monitoring the state change of the inter-satellite link in real time; step 5, continuously monitoring fault events in the network, immediately starting a pre-calculated standby path when a fault is detected, updating a corresponding SRv6SID list, and performing rapid path switching; and step 6, dynamically adjusting the network flow. The method not only can adapt to the dynamic characteristics of the low earth orbit satellite network, but also can effectively meet the differentiated service requirements, and has the rapid fault recovery and load balancing capability.

The invention provides an ocean buoy data real-time acquisition method based on low earth orbit satellite communication, and belongs to the technical field of electrical digital data processing.The ocean buoy data real-time acquisition method comprises the steps that firstly, a low earth orbit satellite network communication link is built, data characteristics are analyzed through a compression conversion gain index model, and a low earth orbit satellite network communication link is established; and establishing a multi-stage compression mechanism. The system adopts an optimization equation set to dynamically adjust compression parameters, the optimization equation set comprises a resource consumption equation, a compression quality equation and a transmission efficiency equation, and self-adaptive compression of data is achieved. And meanwhile, through a hierarchical algorithm selection mechanism and a parameter optimization strategy and in combination with real-time feedback control, continuous optimization of the compression efficiency is ensured. According to the compression scheme based on multi-level optimization, the technical problem of low compression efficiency caused by poor algorithm adaptability in the ocean buoy data compression process in the prior art is effectively solved.

The invention provides a model and data driven low-orbit navigation enhanced satellite clock error forecasting method and equipment, and the method comprises the steps: carrying out the preprocessing of original clock error data of a low-orbit satellite: converting clock error time domain data into frequency domain data through time-frequency conversion, and employing a quartile method to recognize and eliminate frequency domain outliers and corresponding time domain abnormal values; constructing a frequency domain energy model and extracting periodic terms, including performing power spectral density analysis on the preprocessed clock error frequency domain data, and adaptively extracting significant periodic components of the low earth orbit satellite clock error through a threshold value; establishing a polynomial low earth orbit satellite clock error forecasting model considering periodic term correction and forecasting a clock error sequence to obtain a corresponding fitting residual error sequence and a clock error forecasting value; and normalizing the fitting residual error sequence, inputting the fitting residual error sequence into the gating circulation unit neural network, training and forecasting by adopting a window sliding input mode, and outputting a residual error prediction result. According to the method, the interpretability of the forecasting result can be effectively improved while the low earth orbit satellite clock error forecasting precision and stability are improved.

Various approaches for the generation and verification of user equipment (UE) location, using communications and processing capabilities of non-geostationary (NGSO) satellite networks and equipment are discussed. Among other examples, communications between a UE and a low-earth orbit (LEO) satellite may be used to substantiate or corroborate, to a location management function (LMF) of a 5G network, that a UE is located in or at a particular geographical location or area. Additionally, based on this location information and related SV ephemeris data, a satellite coverage area may be determined for a UE at a location at any one moment in time, for coordinating and managing connectivity of the UE with terrestrial and non-terrestrial networks.

The invention discloses a satellite switching method and system for an NTN high and low orbit fusion network, and the method comprises the steps: S1, UE obtains the position of the UE through a GNSS, reports the position to a source satellite, and obtains a candidate satellite list which is allowed to be accessed and measurement configuration from the source satellite; s2, the UE starts measurement after receiving the candidate satellite list, and updates the candidate satellite list according to a measurement result; s3, the UE measures all satellites in the updated candidate satellite list; and sorting the low earth orbit satellites and the geostationary orbit satellites meeting the conditions according to the measurement result and the candidate satellite information, and switching the satellites according to the sorting result. The method has the characteristics that the success rate and the communication continuity of UE conditional switching are improved, the switching decision delay and the signaling interaction load are dynamically reduced, and the cooperative advantages of LEO low time delay and GEO wide coverage are fully exerted.

A satellite constellation system includes a plurality of satellites, wherein each satellite is configured to orbit in one of a plurality of orbital planes of the satellite constellation system at an altitude range corresponding to low earth orbit (LEO), wherein each of the plurality of orbital planes includes a corresponding one of a plurality of satellite subsets of a plurality of satellites, wherein a first orbital plane of the plurality of orbital planes corresponds to a first coverage area facilitated by a plurality of navigation signals transmitted by ones of the plurality of satellites in the first orbital plane, wherein the plurality of navigation signals transmitted by the ones of the plurality of satellites in the first orbital plane each have a first primary pseudo-random noise (PRN) code; and wherein a second orbital plane of the plurality of orbital planes corresponds to a second coverage area facilitated by a plurality of navigation signals transmitted by ones of the plurality of satellites in the second orbital plane, wherein the plurality of navigation signals transmitted by the ones of the plurality of satellites in the second orbital plane each have a second primary PRN code.

The invention belongs to the technical field of satellite orbit prediction, and provides a low-orbit satellite orbit state prediction method based on artificial intelligence, which comprises the following steps of: dividing step lengths of a predicted orbit according to a time window, calculating a resultant acceleration of each step length, performing stress input on an initial position and speed, and obtaining a nominal orbit state sequence; forming an augmented state vector with aerodynamic synthesis parameters; inputting a time sequence neural network model, and performing rolling updating on the augmented state according to the output; obtaining an original standard deviation through mapping by using uncertainty measurement, calculating a standardized residual error, solving a right side weighted quantile according to a normalized time weight, comparing the right side weighted quantile with a preset threshold value, and carrying out adaptive deviation adjustment; and calculating risk measurement by using the acquired data, comparing the risk measurement with a set threshold value and a priority rule, automatically executing a judgment action on the risk measurement, recording a trigger reason and the judgment action, and updating parameters in the time sequence neural network model.

The invention provides a low-orbit satellite communication terminal network performance dynamic tuning method and system, and relates to the technical field of low-orbit satellite communication. Comprehensive data such as relative movement of a satellite and a terminal and signal transmission loss are acquired; preprocessing the integrated data, inputting the preprocessed integrated data into a time sequence prediction model containing LSTM and Transform, generating a signal quality and intensity index sequence and a link stability level in a future preset time window, and carrying out dynamic optimization based on the generated indexes, including adjusting a terminal modulation mode according to the signal quality; combining the link stability and the signal strength to aggregate the link, and optimizing the switching opportunity and path; allocating resources according to the signal strength and the service characteristics; and optimizing the energy consumption according to the relative motion and the business characteristics. Through accurate prediction and multi-dimensional adjustment and optimization, the communication efficiency and reliability of the low-orbit satellite communication terminal network are improved, energy consumption and delay are reduced, and good communication quality is guaranteed.

The invention provides a low-orbit satellite internet heterogeneous federated learning method based on dynamic aggregation, and relates to the technical field of federated learning, and the method comprises the following steps: S1, a central server distributes a local training task for each low-orbit remote sensing satellite through a data set sharing method; s2, the satellite participating in local training receives the shared data and the parameters of the current global model, and uploads the updated local model parameters to a central server; s3, the central server calculates a weighted value according to the frequency at which each satellite participates in aggregation and the time at which the model participates in aggregation last time; judging whether convergence occurs based on the weighted value; s4, outputting a current global model; and S5, replacing the initial global model in the step S1 with the current global model, executing the steps S1 to S3 again until convergence, and outputting the current global model. According to the method, the efficiency, precision and stability of model training can be improved, and the generalization ability of a global model is enhanced, so that cooperative work between different satellites and efficient convergence of the model are ensured.

The invention relates to the technical field of satellite internet, and discloses a low-orbit satellite phased array multi-beam interference modeling and suppression method and system, and the method comprises the steps: selecting a Kaiser window as a core filtering method, and achieving the optimization of beam characteristics through the dynamic adjustment of a shape parameter beta; generating an initial beam directional diagram based on a digital phase matching method, and multiplying the Kaiser window function coefficient by the excitation weight of the 64-array-element linear array element by element to realize spatial domain weighted filtering; the method comprises the following steps: constructing a training data set containing multi-scene interference characteristics, calculating a corresponding covariance matrix and an accurate inverse matrix thereof to form a sample pair, designing a deep neural network architecture, inputting a flattened covariance matrix vector, and learning a complex nonlinear mapping relation from the covariance matrix to the inverse matrix through a multi-layer full-connection structure; a mean square error is used as a loss function to constrain network output precision, and a multi-beam interference system model is constructed; according to the invention, stable and efficient communication of the low-orbit satellite system in a complex electromagnetic environment and under rapid channel change is ensured.

The embodiment of the invention discloses a precision positioning acceleration method and device based on a low earth orbit satellite / LSTM neural network. The method comprises the steps that a terminal obtains a wide lane phase decimal deviation product, a narrow lane phase decimal deviation product and a first GNSS combination observation value which are generated by a server based on an LSTM method and are subjected to coding processing; determining a first GNSS wide lane real number ambiguity according to the first GNSS wide lane real number Based on a precise point positioning algorithm, determining initial GNSS ionosphere elimination combination real ambiguity and other parameters; performing inter-satellite single difference on the first GNSS wide-lane real number ambiguity, and obtaining the integer ambiguity by combining wide-lane phase decimal deviation product fixation; performing inter-satellite single difference on the initial GNSS ionosphere-free combination real ambiguity, determining a first GNSS narrow-lane real ambiguity by combining the wide-lane integer ambiguity, and fixing the first GNSS narrow-lane real ambiguity by using a narrow-lane phase decimal deviation product through a partial ambiguity fixing method to obtain the integer ambiguity of the narrow-lane phase decimal deviation product; and calculating a user coordinate fixed solution in combination with related parameters.

The invention discloses a forecasting method and device for an atmospheric resistance coefficient of a low-orbit satellite in the technical field of satellite navigation. The forecasting method comprises the following steps: acquiring satellite orbit determination data and a space environment index in a preset time period before forecasting; according to the satellite orbit determination data, performing simplified dynamic precise orbit determination on a low-orbit satellite, and fitting an atmospheric resistance coefficient in the simplified dynamic precise orbit determination process; performing data preprocessing on the space environment index and the atmospheric resistance coefficient and generating a sample set; constructing an LSTM prediction model, and training, adjusting and evaluating the LSTM prediction model through the sample set; predicting an atmospheric resistance coefficient in a future preset time period according to the finally obtained LSTM prediction model; and applying the atmospheric resistance coefficient in the future preset time period to the atmospheric resistance perturbation model of the low-orbit satellite for orbit forecasting. According to the method, the atmospheric resistance coefficient in the LEO satellite orbit prediction process is predicted in a high-precision manner through the LSTM prediction model, so that the orbit prediction precision is effectively improved.

The invention discloses a method and a system for capturing an ultra-wideband navigation signal of a low-orbit satellite, which are used for solving the technical problem that the existing method for capturing the ultra-wideband navigation signal of the low-orbit satellite is easy to cause that the signal cannot be locked, and finally the capturing success rate is low. The method comprises the following steps: acquiring ka-band low-orbit satellite signals and low-orbit satellite pseudo-random noise codes corresponding to a plurality of low-orbit satellite ultra-wideband navigation signals; generating a complex signal and an original intermediate-frequency signal according to a preset sampling rate, preset skipping time and the ka-band low-orbit satellite signal; constructing a pseudo-code spectrum library based on the pseudo-random noise codes of the low-orbit satellites, and outputting the pseudo-code spectrum library; determining a discrete frequency search sequence based on known intermediate frequency parameters of the original intermediate frequency signal, performing matrix construction in combination with the complex signal and the pseudo code spectrum library, and outputting a three-dimensional result matrix; and capturing and judging the ultra-wideband navigation signals of the low-orbit satellites by adopting the three-dimensional result matrix, and determining a plurality of successfully captured ultra-wideband navigation signals of the low-orbit satellites.

The invention discloses a double-layer ionosphere modeling method fusing low-orbit satellite data, which comprises the following steps of: preprocessing ground-based GNSS (Global Navigation Satellite System) data to obtain an STEC expression of a ground-based GNSS; preprocessing the precise orbit determination data of the low-orbit satellite to obtain a VTEC expression of the precise orbit determination data; obtaining an electron density profile product of the radio occultation of the low-orbit satellite, and obtaining VTEC of the radio occultation through profile integration; using two groups of spherical harmonic coefficients to express global VTEC distribution, and constructing an observation equation; and determining weights of different types of data by using Helmert variance component estimation, and finally solving to obtain two groups of spherical harmonic coefficients to generate an ionized layer grid product. Projection errors caused by vertical layering in a traditional single-layer model are weakened, meanwhile, precise orbit determination data and radio occultation data of a low-orbit satellite are combined, the problem that ionosphere TEC cannot be correctly layered in a double-layer model is solved, data of areas where GNSS tracking stations are sparsely distributed are supplemented, and the reliability of the GNSS tracking stations is improved. Therefore, a global ionosphere model with higher precision is obtained.

The invention relates to the technical field of satellite network communication, in particular to an ST-DSQN-based low earth orbit satellite network task unloading method and system, and the method comprises the steps: introducing a time flow module, a spatial flow module and a space-time attention mechanism into a deep Q network, and constructing a space-time double-flow Q network; the method comprises the following steps: extracting time characteristics of arrival of a satellite unloading task through a time flow module, extracting spatial characteristics of inter-satellite topology through a spatial flow module, and carrying out weighted summation on the time characteristics and the spatial characteristics based on a space-time attention mechanism to obtain space-time fusion characteristics; and inputting the space-time fusion features into the deep Q network, and training the deep Q network in combination with a priority experience playback mechanism and a multi-target reward function until an optimal task unloading strategy is learned. According to the method, space and time characteristics can be better combined, efficient decision-making of task unloading in the satellite network environment is achieved, the average time delay and energy consumption are remarkably reduced, and the task success rate is improved.

Proposed is a topology generation device for generating topology for a low earth orbit satellite constellation system including a plurality of low earth orbit satellites to be operated in a plurality of orbits. The topology generation device may include a memory storing one or more instructions and a processor executing the one or more instructions. The processor may collect orbit information for the plurality of orbits from a ground station, collect status information including status of links between the plurality of low earth orbit satellites, and generate location information for a first low earth orbit satellite by predicting a location of the first low earth orbit satellite based on the orbit information. The processor may also generate a network topology for the low earth orbit satellite constellation system based on the location information for the first low earth orbit satellite and the status information.

The invention discloses a mobility management optimization method and system in a low earth orbit satellite system. The system comprises two core mechanisms of idle state position registration and connected state Xn switching. Aiming at idle state management, registering through periodic position change, integrating registration requests of a plurality of UE (User Equipment) by adopting a batch message merging technology, and sending the integrated registration requests to a ground core network; in the aspect of connection state management, a multi-UE collaborative switching process based on an Xn interface is designed. According to the method, the problem of signaling storm in a low-orbit satellite high-speed moving scene is effectively solved, the switching time delay is greatly reduced, the data stream continuity retention rate is remarkably improved, and the method is suitable for mobility management optimization of a large-scale satellite communication system.

The invention provides a communication resource scheduling method and system for a low-orbit satellite, and the method comprises the steps: transmitting a spot beam to a target region by the low-orbit satellite through a directional antenna, and starting to provide communication services for all target terminals in the coverage range of the spot beam; when the preset switching period is ended, the satellite resource control center determines a new low earth orbit satellite taking over the target area according to the real-time motion information of the low earth orbit satellite; controlling the new low-orbit satellite to adjust the pointing angle of the directional antenna so as to enable the spot beam emitted by the new low-orbit satellite to cover the target area; meanwhile, beam switching instructions are generated and sent to all target terminals in batches; and all the target terminals execute a beam switching action so as to continuously provide communication services for all the target terminals through the spot beams emitted by the new low-orbit satellites. According to the invention, unified beam switching of all user terminals in the target area is realized, the situation of high concurrency of switching instructions of a satellite resource control center when the number of users is large is avoided, and the communication response speed of the users is improved.

The invention discloses an energy scheduling method, system and device for a low-earth-orbit satellite and a medium. The method comprises the steps that the energy storage level is calculated according to the current generation power of the low-earth-orbit satellite, the current remaining electric quantity of an energy storage unit and the health degree of a battery; generating a future illumination time sequence according to the orbit parameters of the low-orbit satellite and the satellite attitude control data; according to the current operation state data of each device loaded on the low earth orbit satellite and a preset task list, generating corresponding task prediction energy consumption data arranged in a descending order according to the importance level through a historical energy consumption model; according to the energy storage level, the future illumination time sequence and the task prediction energy consumption data, calculating the dominant power supply amount, matching the energy consumption demand in the task prediction energy consumption data, and carrying out the preferential power supply of the equipment of the task item with the high importance level. And carrying out power supply adjustment on the other equipment by adopting at least one strategy of delaying to the illumination period, reducing the operation power and shortening the operation duration so as to realize efficient scheduling on the energy of the low-orbit satellite.

The invention provides a low earth orbit satellite network task unloading and route planning combined scheduling method based on a time expansion graph and a related device, and belongs to the technical field of wireless communication. According to the method, a dynamic time-varying low earth orbit satellite network is constructed; expressing the constructed dynamic time-varying low earth orbit satellite network as a directed network topological graph based on a time sequence by using a time expansion graph; constructing a joint scheduling model by using the directed network topological graph based on the time sequence; setting constraint conditions of the combined scheduling model; based on the set constraint condition of the joint scheduling model, solving the objective function of the constructed joint scheduling model to obtain an optimal result; and performing task unloading and route planning combined scheduling on the low-orbit satellite network according to the obtained optimal result to obtain a task unloading and route planning combined scheduling result. The problem that the overall performance optimization effect is poor due to the fact that the coupling relation between task unloading and routing planning in the dynamic time-varying network scene is not comprehensively considered is solved.

The invention discloses a random access preamble and detection algorithm design based on low earth orbit satellite communication. Specifically, firstly, a novel lead code with a plurality of subsequences is provided, in order to enlarge the number of available lead codes in a wave beam, a ZCM sequence is introduced to form the subsequences, and orthogonal frequency division multiplexing is adopted for modulation and is sent to a channel. Subsequently, a timing advance (TA) detection algorithm is proposed. The first sub-sequence is used for decimal time delay detection, and the other sub-sequences are used for integer time delay detection. In addition, the peak detection ingeniously utilizes the variance of the power delay spectrum, so that the detection performance is improved. Finally, a simulation result shows that the lead code provided by the invention is almost not influenced by frequency offset, does not need pre-compensation, and is suitable for being applied to low-orbit satellite communication with relatively large frequency offset.

The invention provides a low-earth-orbit satellite global beam position distribution and scheduling system based on deep reinforcement learning, and the system comprises a low-earth-orbit satellite scene modeling beam position distribution module which is used for constructing a low-earth-orbit satellite communication scene and completing the global beam position division. A satellite constellation configuration and orbit parameters are set, global beam positions are divided based on a spherical network, a beam ground projection model and a user system model are established, and a scene basis and a beam position division basis are provided for beam resource scheduling; the deep reinforcement learning beam resource scheduling module is used for realizing intelligent allocation scheduling of beam resources, establishing a decision system based on a Markov decision process by constructing a beam resource allocation model, extracting features through a state space model, performing time sequence modeling, and optimizing a scheduling strategy based on deep reinforcement learning. And dynamically matching the user demand and the beam resource. Therefore, dynamic optimization of low-orbit satellite beam resources is realized, the resource utilization rate is improved, and the communication requirements of users are efficiently met.

The invention provides a low earth orbit satellite network dynamic routing optimization method and system based on domain division routing, and the method comprises the steps: dividing a satellite network into a plurality of regions, and distributing a unique IP address for each satellite node; in each region, synchronizing intra-domain topology information through a Hello data packet and a link state notification, and generating an intra-domain routing table; announcing and synchronizing inter-domain topology information through a boundary gateway and a summarized link state, and generating an inter-domain routing table; and forwarding the data packet according to the intra-domain and inter-domain routing tables. According to the invention, the signaling overhead can be reduced, the routing calculation efficiency is improved, the network stability is enhanced, and the network resource utilization is optimized.

A multi-static synthetic aperture radar using beamformed illumination beams and multiple collection satellites is described. An illumination satellite may be in first orbit and multiple collection satellites may be in a second orbit. The illumination satellite may transmit beam signals (e.g., communication signals carrying modulated data to user terminals) from an antenna array to different beam coverage areas according to a beamforming matrix. Each of the collection satellites may receive reflections of the beam signals. The reflected signals received at the collection satellites may be processed according to the beam signals and beamforming matrix used to transmit the beam signals to obtain an image of a geographical area. In some cases, the collection satellites may relay the received signals for processing via the illumination satellite.

The invention discloses a low earth orbit satellite edge computing service optimization method and system based on double time scales, and relates to the technical field of satellite networks and edge computing, and the method comprises the steps: obtaining a plurality of time frames and time slots, the plurality of time frames and time slots are divided based on time, and the time scales of the time frames are larger than the time scales of the time slots; dynamically adjusting satellite selection and request scheduling based on the visibility and resource state of the current satellite in each time slot; according to the method, a service deployment and migration strategy is dynamically adjusted based on long-term service requirements and resource states in each time frame, and the dynamic adjustment method is an optimization algorithm based on double time scales, so that the service quality can be improved, and the system cost can be reduced.

The invention belongs to the technical field of satellite navigation, provides a real-time positioning processing method based on low-orbit satellite opportunity signal Doppler, and is used for solving the problem of how to adopt low-orbit satellite opportunity signals to carry out real-time high-precision positioning under the condition of GNSS satellite signal rejection. The method comprises the following steps: firstly, obtaining a Doppler frequency shift measurement value of a low-orbit satellite, and then determining an initial value of a receiver based on the low-orbit satellite and two rows of element orbit data; performing iterative calculation according to the initial value of the receiver and the satellite position information of the low-orbit satellite at the receiving moment to obtain satellite position information and speed information of the low-orbit satellite at the transmitting moment; and finally, constructing a positioning error equation according to the Doppler positioning model, carrying out iterative calculation by adopting a least square method, and judging and outputting a positioning result according to a preset convergence condition. According to the method, real-time positioning can be carried out based on low-orbit satellite opportunity signals under the GNSS denial condition, and the real-time positioning requirements of static and mobile receivers can be met.

The invention belongs to the technical field of satellite communication, and provides a distributed low earth orbit satellite inter-satellite routing method and device based on a minimum hop count path. The method comprises the following steps of: 1, constructing a low earth orbit satellite inter-satellite network with a topological structure, mapping the dynamically changed low earth orbit satellite inter-satellite network into a logic static network by utilizing a virtual node method, and determining the positions of a source satellite node and a target satellite node of a data packet to be forwarded in the logic static network; 2, determining a minimum hop count path and a path selection domain based on the positions of the source satellite node and the target satellite node; and step 3, starting from the source satellite node, gradually selecting a next-hop routing node of the data packet to be forwarded in the path selection domain according to the load state and survival probability of adjacent routing nodes until the next-hop routing node coincides with the target satellite node. According to the method and the device provided by the invention, the data transmission efficiency and reliability can be improved.

The application discloses a low-orbit satellite congestion control method based on an artificial immune algorithm, which comprises the following steps: a satellite node periodically monitors the occupancy rate of an output queue in each direction, when congestion is detected, the satellite generates a congestion warning packet as an antigen and sends it to a directly adjacent node; the adjacent node receiving the congestion warning packet finds a matching item of an affected destination node in a historical memory cell library through the similarity between the current scene and the historical record, as the routing strategy of the destination node; when no match is found, the optimal bypass strategy is determined based on the direction of the congestion link and the position information of the satellite; the satellite comprehensively evaluates the generated control strategy within a time window; when the affinity continues to fail to reach a threshold, the satellite continuously monitors the queue occupancy rate change trend, and when it is found that a continuous multiple periods show an upward trend, the shunt proportion is increased; the application improves the response speed of the congestion control, network performance and service quality.

We present a ground-based laser system for searching, ranging, and tracking that actively illuminates small resident space objects (RSOs) in low Earth orbit (LEO) and observes position and transit-time of reflections, enabling orbital custody of most one-to-few centimeter-sized objects. A diode-pumped alkali laser (DPAL) augmented with mode-locking and Q-switching serves as an illuminator and offers exceptionally high spectral brightness due to its output beam's sub-nanosecond pulse duration and picometer-level spectral linewidth. Kilohertz fast-rastering enables interrogations of distinct few-meter-sized sky-patches at megahertz rates. Paired on the observation side with one or more telescopes outfitted with Faraday anomalous dispersion optical filters (FADOFs), image intensifiers, multi-pixel arrays, and nanosecond timing, the combined system could offer nearly background-free discoveries of RSOs every hour, even during daytime. Periodically re-flashing previously discovered objects to maintain orbit custody expends only a small fraction of total observing time.