30 results about "Arctic" patented technology

The invention discloses a sea ice coverage on-satellite detection and updating method and device for a synthetic aperture radar (SAR) image, and belongs to the technical field of satellite remote sensing marine monitoring, and the method comprises the steps: carrying out the preprocessing of a dual-polarization SAR image on the ground, training a super-resolution model, and carrying out the knowledge distillation and lightweight processing, and deploying the super-resolution model to a spaceborne computer. After a satellite obtains a real-time SAR image in an on-orbit mode, preprocessing can be completed on the satellite, and a sea ice coverage binary image is directly output. In order to adapt to different satellite wave band data, the ground only needs to finely adjust part of parameters of the model and upload and update the parameters in a differential packet form, so that the whole packet is prevented from being retransmitted. According to the method, a closed loop of ground pre-training-on-satellite reasoning-differential updating is realized, the method has the characteristics of fast response, light weight, easy expansion and the like, and the sailing safety of the arctic navigation channel can be remarkably improved.

The application discloses a collaborative scheduling method based on an arctic sea parrot optimization algorithm and peak-valley time-of-use electricity price, belongs to the technical field of micro-grid intelligent scheduling and renewable energy management, and comprises the following steps: step S1, a micro-grid system model is established; step S2, operation constraint conditions are constructed, including the power balance and the upper and lower limit constraints of the power of each component of the micro-grid and the state constraints of the storage battery which need to be satisfied by the wind turbine, the photovoltaic, the gas turbine, the fuel cell, the storage battery and the power exchange with the power grid in the micro-grid; step S3, an objective optimization function of operation cost and pollutant emission is constructed; and step S4, the optimal scheduling scheme is output by applying the objective optimization function. The collaborative scheduling method based on the arctic sea parrot optimization algorithm and the peak-valley time-of-use electricity price can significantly improve the optimization precision and convergence efficiency of the system, meanwhile, the high reliability and robustness of the scheduling process are ensured, and finally, the intelligent collaborative scheduling of the micro-grid energy is realized.

1. The name of the design product: balm round can (Arctic Ocean). 2. The use of the design product: for placing in the car, removing odor, for freshening the air, long-lasting fragrance. 3. The design points of the design product: in the combination of shape, pattern and color. 4. The picture or photo that best indicates the design points: perspective view. 5. The design claimed contains color.

Synthetic aperture radar (SAR) is a type of imaging technology that can be used for a wide range of applications, including Earth observation, mapping, object tracking, change detection (e.g., Arctic ice), natural disaster monitoring, and many other uses. A high-altitude unmanned aerial vehicle for performing synthetic aperture radar (SAR) imaging comprises a fuselage, wings attached to the fuselage to provide lift to the aircraft, one or more electric propellers to provide thrust to the aircraft, a SAR payload for SAR imaging the Earth's surface as the aircraft flies, solar cells to generate power to drive one or more electric propellers and operate the SAR payload, and one or more batteries to store the electrical energy generated by the solar cells.

This invention provides a green and low-carbon intelligent planning method and system for Arctic shipping routes. The method includes: constructing a gridded environmental model of the Arctic sea area; establishing a mapping relationship between ship navigation resistance and propulsion power based on a semi-empirical ice resistance formula to construct an ice resistance-power-carbon emission coupled model, and determining the carbon emissions per unit distance; constructing a multi-objective reward function, including a carbon emission penalty term based on the estimated carbon emissions and a time penalty term based on navigation time; and performing path training and strategy optimization based on the gridded environmental model and the multi-objective reward function to output the optimal route that satisfies the multi-objective constraints. This invention, by constructing an ice resistance-power-carbon emission coupled model and introducing an equivalent turning time mechanism, achieves synergistic optimization of navigation efficiency and carbon emission control in complex ice-covered environments, improving the engineering feasibility and green and low-carbon level of planned routes, and is suitable for intelligent decision-making in Arctic mixed ice and water navigation scenarios.

The application provides an Arctic sea wave prediction method based on automatic fusion of sea ice density, and belongs to the technical field of weather prediction. The wind field data automatic acquisition system is established to ensure the continuity of the wind field driving data. The sea ice wave interaction optimization model is applied to dynamically adjust the IC4M2 sea ice wave parameterization scheme. The open boundary line is set in the high latitude sea area of the North Atlantic, and the radiation boundary condition algorithm is combined with the sponge layer absorption technology to process the boundary wave propagation. The WAVEWATCH III sea wave numerical model is started, the fourth-order precision finite difference discrete format is combined with the adaptive artificial viscosity control algorithm to calculate the Arctic sea wave field, and the sea wave prediction product business processing system is established, so that the technical problem of low accuracy of the Arctic sea wave prediction caused by the insufficient parameterization precision of the sea ice wave interaction is solved.

The present invention relates to a technology for liquefying natural gas, which is subsequently transported by rivers and oceans and ultimately regasified. Pretreated natural gas is compressed by a compressor 1, the heat of compression is removed in an air or water cooler 2, and multi-stage pre-cooling is subsequently performed by evaporating a heavy refrigerant in an evaporator 3. The light refrigerant vapor and its pre-evaporation cold are recovered in a shell-and-tube heat exchanger 7, where the pressure of the gas to be liquefied is reduced by a pressure reducer 10, unliquefied gas is separated, and liquefied natural gas is discharged. The heavy refrigerant obtained by evaporation is compressed by a compressor 4, condensed in an air or water cooler 5, and reused in the multi-stage pre-cooling of natural gas. A light refrigerant is compressed by at least two compressors 11, the heat of compression is removed in an air or water cooler 12, and then passes through continuous cooling by a low-pressure light refrigerant in a double-flow superheater 12 and an evaporating heavy refrigerant in an evaporator 3. The high-pressure light refrigerant is then split into two streams. The first stream is expanded through an isentropic process in an expander 14. The second stream passes through continuous cooling in a shell-and-tube heat exchanger 7, then expanded through an isenthalpic process in a throttle valve 15, and evaporated by subcooling natural gas in an evaporator 8. The streams are then mixed at equal pressure and used as a single stream of low-pressure light refrigerant to cool the second stream of light refrigerant before expansion and evaporation in the isenthalpic process with natural gas in the shell-and-tube heat exchanger 7, and to cool a single stream of high-pressure light refrigerant in a double-flow superheater 13. The present invention provides stronger cooling of the natural gas, reduces the amount of boil-off gas and the work required for its recompression and recycling, and provides a simpler hardware design for the heat exchanger.

The invention provides a ship target fusion detection method in a polar region channel based on SAR and optical images, and belongs to the field of remote sensing image processing and target detection. In order to solve the problems of difficulty in moving target association and high sea ice false alarm rate in different-time-phase images of the arctic ice region, the technical scheme comprises the following steps: respectively carrying out target initial detection on SAR and optical images, and extracting features to remove sea ice false alarms; secondly, saliency detection is carried out on the image to extract a channel area, and target parameters such as the target main axis angle, the position and the intersection-to-union ratio are calculated; meanwhile, the motion state is judged according to the target parameter difference, and the maximum correlation area is determined by combining the maximum speed constraint; and finally, target matching is completed in the region, and decision-level fusion is carried out by adopting a D-S evidence theory. According to the method, accurate correlation and fusion detection of the SAR and the time-shifting ship target in the optical image are realized, background interference is effectively overcome by comprehensively utilizing bimodal information, and the method has important application value in the fields of polar region navigation safety monitoring and the like.

The application discloses a micro-grid scheduling optimization method and system based on a multi-target arctic sea parrot optimization algorithm, and the method comprises the following steps: establishing a multi-target optimization scheduling model of a micro-grid, wherein at least an operation and maintenance cost target function and an environmental protection cost target function are included in the multi-target optimization scheduling model; solving the multi-target optimization scheduling model by using a multi-strategy fusion multi-target arctic sea parrot optimization algorithm to obtain a Pareto optimal solution set; and determining an optimal output strategy of each distributed power generation unit in the micro-grid according to the Pareto optimal solution set. The algorithm has space exploration ability in the early stage and optimization precision in the later stage, and the optimization effect of micro-grid scheduling is improved.

The application discloses an Arctic shipping route navigation safety evaluation method and system based on multi-source data fusion and ship adaptability, and relates to the cross technical field of marine navigation safety guarantee, meteorological and hydrological data analysis and intelligent navigation. The method comprises the following steps: collecting multi-source data of the Arctic shipping route, dynamically fusing weights in combination with real-time reliability calculation of the data source after preprocessing and space-time alignment, completing confidence dynamic weighted fusion to obtain comprehensive environmental data; constructing a coupled physical stress model based on the data and inherent parameters of the target ship, introducing ice type and sea current factors to quantify real-time navigation risk, and generating a voyage full-cycle dynamic risk corridor; planning a route based on the risk corridor by using a hybrid heuristic algorithm, and combining a multi-index judgment mechanism with a self-defined weight to realize navigation safety grade judgment and global optimal route output. The application improves evaluation accuracy and ship adaptability, prolongs the dynamic prediction period, realizes global optimal route planning, and has strong operability in decision support.

This invention discloses an ultra-low temperature zinc-free hydraulic oil for engineering machinery in extremely cold regions and its preparation method. The hydraulic oil comprises the following raw materials by weight percentage: 65-75% base oil, 24-35% viscosity index improver, 0.3-1.0% anti-wear agent, 0.1-1.5% antioxidant, 0.01-0.1% rust inhibitor, 0.005-0.02% demulsifier, and 0.005-0.02% defoamer. The ultra-low temperature hydraulic oil for engineering machinery in extremely cold regions prepared by this invention uses polyalphaolefin and light white oil as the main raw materials, resulting in excellent low-temperature fluidity and viscosity-temperature properties. The oil has a viscosity index greater than 250 and a kinematic viscosity less than 1500 mmHg at -50°C. 2 With a pour point below -60°C, this ultra-low temperature hydraulic oil for engineering machinery in extremely cold regions ensures that the hydraulic system can start at -50°C and achieve rapid start-up at -40°C, making it highly suitable for mobile hydraulic systems in extremely cold regions, especially in Antarctica and the Arctic.

The invention discloses an improved ant colony algorithm-based arctic channel path planning method, which belongs to the technical field of navigation, and comprises the following steps of: (1) calculating a navigable area of an icebreaker in an arctic region by combining ice condition data, meteorological data and the level of the icebreaker; (2) initializing pheromone concentration for effective nodes in the navigable area; (3) finding out a next-step transferable node set naavi of the kth ant starting from the current node i at the moment t, and calculating the probability of the ant starting from the node i to the node j in the naavi according to the pheromone concentration; completing one iteration; and (4) updating the pheromone concentration on the path from the node i to the node j, and entering the next iteration until a termination condition is met. According to the north pole channel path planning method based on the improved ant colony algorithm, the initial pheromone concentration is optimized while the characteristics of the ant colony algorithm are reserved, the early blind search is remarkably reduced, the calculation amount is reduced, and the search efficiency is improved.

The present disclosure relates to methods, apparatuses, and systems for unmanned underwater vehicles capable of operation in the Arctic region. An example unmanned underwater vehicle includes: a hull; one or more guide rails extending from the hull and attached to the hull by one or more legs; a vertically-deployed mast, wherein the vertically-deployed mast is configured to penetrate through an ice sheet; and a communications antenna, wherein the communications antenna is deployed with the vertically-deployed mast and enables communication above the ice sheet. The dorsally-located guide rails of an example define an extended position and a retracted position, wherein the guide rails disposed in the extended position are disposed further from the hull than the guide rails disposed in the retracted position. Embodiments described herein include systems employing air-deployable buoys, water-deployed buoys and small UUVs, and ice-penetrating buoys to support communications in the Arctic region.

The invention discloses a flood storage and detention area start decision-making method, system, equipment and medium based on a swarm intelligent optimization algorithm, and the method comprises the steps: collecting hydrological engineering, spatial geography and historical case data through a multi-source data integration architecture, and forming structured data with a unified time scale after cutting, abnormal value processing and standardization; and the uncertainty scene generation architecture is used for flood scene prejudgment. Outputting a flood routing trend and an uncertainty interval based on an LSTM deep learning model, and automatically generating various disturbance scenes of flood peak flow, peak present time and downstream risk levels; and the swarm intelligence optimization decision-making architecture is used for solving an optimal scheme. All scenes are traversed through an Arctic Halorot optimization algorithm, the total flood diversion cost is minimized under the conditions of hard constraint and soft constraint, and a flood diversion critical point and an optimal starting scheme are output through dynamic iteration. According to the method, the dynamic adaptability and the decision robustness are remarkably improved, the multi-target balance and the business landing are considered, and the flood control risk and the disaster loss are effectively reduced.

This invention discloses an Arctic submersible transport system adaptable to both nuclear and conventional diesel power, belonging to the field of Arctic transport equipment technology. The system includes a dual-power mode compatible submersible transport platform module, a piston-type self-cleaning storage and transport module, a multimodal three-dimensional collaborative operation module, an under-ice communication and navigation module, an intelligent ballast control module, and a safety assurance module. The core platform adopts a modular power compartment design, adaptable to either nuclear or conventional diesel power, and can stably submerge at a depth of 5 meters under 2 meters of Arctic ice, with a rated crude oil carrying capacity of 460,000 tons. It is equipped with multiple unmanned surface vessels, ice-surface hovercraft, and aerial resupply and protection mechanisms to form a three-dimensional collaborative system. The storage and transport module uses a partitioned piston-type oil tank structure, enabling crude oil loading and unloading, self-cleaning, and dynamic control of ballast water. This system enables year-round, all-weather navigation along Arctic routes, mitigating geopolitical risks, balancing long-range economics with construction approval flexibility, and significantly improving the efficiency, safety, and adaptability of polar energy and bulk commodity transportation.

This invention belongs to the field of computer vision technology and provides a weakly supervised pixel-level annotation method for shipborne sea ice images: The method involves acquiring the original image of Arctic shipborne sea ice, cropping the sky and visually blurred areas, removing ship pixels using a ship region mask, and obtaining an effective observation image containing only sea ice and seawater. The image is then partitioned from far to near, converted to the LAB color space, and pixel feature vectors are extracted. These feature vectors are input into an SPGMM model, and pixel categories are determined based on the posterior probability of sea ice and seawater. The partitioned annotation results are then stitched together and post-processed to obtain a pixel-level binary mask for sea ice. This invention addresses the problems of high manual annotation costs for shipborne sea ice images and the poor adaptation of traditional global segmentation models to image spatial heterogeneity, leading to low segmentation accuracy, blurred boundaries, and misclassification.

This invention discloses a method and system for predicting Arctic ship navigation risks based on a GA-BP neural network model, belonging to the field of risk prediction technology. Step 1: Identify key risk factors affecting Arctic ship navigation, determine the input and output of the GA-BP neural network model, and construct a dataset; Step 2: Normalize the dataset obtained in Step 1; Step 3: Establish a BP neural network model and determine its structure; Step 4: Optimize the weights and thresholds of the BP neural network using a genetic algorithm (GA) to obtain a GA-BP prediction model; Step 5: Train and test the GA-BP prediction model obtained in Step 4 on the normalized dataset from Step 2 to predict the risks of ice entrapment and ship-ice collision. This invention addresses the problem of cumbersome and inefficient steps in existing technologies for assessing and analyzing navigation risks in the Arctic.

The invention relates to a north pole inter-ice water channel extraction method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining FY-3D satellite MERS-II sensor data; performing brightness temperature conversion on the thermal infrared band data to obtain brightness temperature data; removing the bow tie effect of the brightness temperature data to obtain processed data; cutting the processed data to obtain model input data, inputting the model input data into a deep learning pre-training model, and extracting an inter-ice water channel of a north pole region; the land area in the inter-ice water channel is filtered out through mask data in the sensor data, and an actual inter-ice water channel is obtained; and enabling the actual inter-ice water channel to correspond to the pixel longitude and latitude information data in the sensor data to obtain an inter-ice water channel distribution diagram of the north pole region. Therefore, the technical problem that the precision of the extracted inter-ice water channel is poor due to the fact that an inter-ice water channel extraction method based on a thermal infrared image easily generates identification errors due to factors such as cloud interference, background complexity and water channel scale diversity in the related technology is solved.

1. Name of the product in this design: Pencil (ZF7709 Arctic Ocean). 2. Purpose of this design: For writing. 3. The key design feature of this product is its shape. 4. The picture or photo that best illustrates the key design points: Design 1 front view. 5. Design 1 (bottom view) is omitted as it is already shown in other views; Design 2 (bottom view) is omitted as it is already shown in other views; Design 3 (bottom view) is omitted as it is already shown in other views. 6. Design 1 is designated as the basic design.

The invention discloses an arctic ice region dynamic route planning method with a stagnation strategy, which belongs to the field of ice region route planning and comprises the following steps: firstly, constructing a dynamic sea ice environment field containing multiple time layer environment data; a space-time A search algorithm is adopted, and path optimization is carried out in the state space fusing the space coordinates and the arrival time index; in the node expansion step, two types of candidate subsequent nodes are synchronously generated: nodes generated based on a spatial movement rule and stagnation nodes allowing the ship to stay at the same position for different time lengths, and the movement cost is calculated according to dynamic environment data. According to the method, dynamic environment perception, space-time path search and a stagnation strategy are deeply fused, so that the adaptability and reliability of path planning in a dynamic change ice area environment are remarkably improved, and integrated optimization of a navigational speed elastic regulation and control process and a path search process is realized.

This invention relates to a method for assessing the efficiency of Arctic marine biological carbon pumps and providing early warning of carbon sink depletion, falling under the field of data processing and analysis technology, including acquiring target data sources. The invention improves the resolution of estuaries and erosion hotspots by employing adaptive grid refinement, enhancing the characterization accuracy of terrestrial material diffusion processes while reducing computational resource consumption. It establishes a multi-level degradation parameterization of organic matter, distinguishing between active, semi-active, and inert organic matter. The invention introduces excitation effects and ultraviolet light degradation modules, reducing the systematic bias in remineralization rate estimation and increasing the additional degradation contribution from excitation effects in the shelf region. Furthermore, it employs a nonlinear depth-adaptive remineralization parameterization, using a hyperbolic tangent threshold function and an exponential saturation function to respond to temperature and organic matter quality, capturing the nonlinear jump in remineralization rate after Arctic temperatures cross the freezing point threshold, thus reducing the prediction error of deep carbon sequestration efficiency.

The application provides a polar route planning method and system based on meteorological big data and artificial intelligence, relates to the field of navigation technology, and comprises the following steps: obtaining polar multi-source meteorological data and sailing constraint information, performing multi-scale space-time decoupling analysis, constructing a risk field data structure, generating a candidate route by using an identification-correction iteration mechanism, calculating a risk feature sequence of the route and accumulating the time sequence, and finally evaluating and selecting an optimal polar route. The application can effectively avoid sailing risks, improve the safety and economy of polar route planning, and adapt to complex and changeable polar meteorological environments.

The invention discloses a parrot-shaped north pole optimization algorithm and peak-valley time-of-use electricity price-based collaborative scheduling method, and belongs to the technical field of micro-grid intelligent scheduling and renewable energy management, and the method comprises the following steps: S1, building a micro-grid system model; s2, operation constraint conditions are constructed, wherein the operation constraint conditions comprise power balance which needs to be met by a fan, a photovoltaic system, a gas turbine, a fuel cell, a storage battery and power exchange power with the power grid in the micro-grid, upper and lower limit constraints of power of each component of the micro-grid and state constraints of the storage battery; s3, constructing a target optimization function of the operation cost and pollutant discharge; and S4, applying the target optimization function, and outputting an optimal scheduling scheme. By the adoption of the collaborative scheduling method based on the parrot optimization algorithm and the peak-valley time-of-use electricity price, the optimization precision and convergence efficiency of the system can be remarkably improved, meanwhile, high reliability and robustness of the scheduling process are ensured, and finally intelligent collaborative scheduling of micro-grid energy is achieved.

The application discloses a method and system for predicting arctic sea ice concentration and ice edge, and relates to the field of intelligent marine prediction. When the prediction time span of the sea ice concentration is less than or equal to half a year, a first sea ice concentration prediction model is used to obtain the monthly sea ice concentration of each spatial grid within the prediction time span; or a second sea ice concentration prediction model is used to obtain the monthly sea ice concentration of each spatial grid within the prediction time span; when the prediction time span of the sea ice concentration is greater than half a year, a third sea ice concentration prediction model is used to obtain the monthly sea ice concentration of each spatial grid within the prediction time span, so as to determine the monthly sea ice range and ice edge position of the Arctic within the prediction time span. The first sea ice concentration prediction model comprises an ice edge perception module, the second sea ice concentration prediction model comprises an edge perception modulation module, and the third sea ice concentration prediction model comprises an adaptive physics information gate expert hybrid mechanism. The application can improve the prediction accuracy of the sea ice concentration and the ice edge.

The invention relates to a method for calculating the electron density of plasma cloud blocks of an ionized layer in the arctic region. The method comprises the following steps: step 1, determining calculation time and parameters of the plasma cloud blocks; step 2, acquiring solar activity data and geomagnetic activity indexes; 3, calculating background ionized layer electron density distribution when the ionized layer plasma cloud block structure is not considered; and step 4, determining an ionized layer plasma cloud block distribution area. According to the method provided by the invention, the influence of solar geomagnetic activity on the plasma cloud block of the ionized layer is fully considered, the spatial-temporal change rule of the structure is obtained according to early-stage data statistical analysis, the defect of an existing ionized layer model in plasma cloud block description is overcome, and an electron density distribution model considering the plasma cloud block is constructed; the precision of the ionosphere model is improved, the performance of a communication and navigation system is optimized, and the application effect of the ionosphere model in related fields is improved.

The invention discloses a robot path planning method based on an improved parrot-shaped optimization algorithm, belongs to the technical field of robot path planning, solves the problems of low convergence efficiency and easy falling into local optimum in solving the path planning problem of a traditional parrot-shaped optimization algorithm, and comprises the following steps: constructing a grid map to simulate the working environment of a robot; in the initial stage, a Bernoulli chaotic mapping and refraction reverse learning strategy is fused to initialize a population so as to enhance the diversity of the population; in the air flight stage, a nonlinear weight factor is introduced to optimize position updating, and an enhanced behavior conversion factor is designed, so that the algorithm is prevented from falling into local optimum, and dynamic balance of global exploration and local development is realized; and finally, accelerating population convergence by using an adaptive Cauchy variation strategy, and improving the global optimization capability of the algorithm. Simulation results show that the improved algorithm of the invention can find an optimal path and has good convergence speed and precision.

The application provides a kind of polar route ship target fusion detection method based on SAR and optical image, belongs to remote sensing image processing and target detection field.Aiming at the problem that the moving target is difficult to associate in the different phase images of arctic ice area, the false alarm rate of sea ice is high, the technical scheme includes: respectively to SAR and optical image are initially detected, and the features are extracted to eliminate sea ice false alarm;Then the saliency detection is carried out to extract the channel area, and the target parameters such as the main shaft angle, position and intersection ratio are calculated;At the same time, the motion state is distinguished according to the difference of target parameters, and the maximum correlation area is determined by combining the maximum speed constraint;Finally, the target matching is completed in the area, and the D-S evidence theory is used for decision level fusion.The application realizes the accurate correlation and fusion detection of time shift ship targets in SAR and optical image, effectively overcomes the background interference by comprehensively utilizing the double modal information, and has important application value in the field of polar navigation safety monitoring.

This invention discloses a brightness temperature simulation method for ice and snow environment observation, belonging to the field of image processing technology. The method includes: Step 1, constructing a physical model of ice and snow layers using the SMRT model, and setting the electromagnetic theory model and ice and snow microstructure of the SMRT model; Step 2, calculating the surface emissivity ε corresponding to the uplink radiation; Step 3, acquiring mixed pixels, correcting the surface emissivity of the mixed pixels to obtain the emissivity of the mixed pixels; Step 4, using the RTTOV model combined with ERA5 atmospheric profile data and near-surface parameters to generate the simulated brightness temperature for Arctic ice and snow environment observation. This ice and snow environment observation brightness temperature simulation method utilizes the SMRT model to simulate the transmission process of microwave radiation in multiple layers of snow, sea ice, and other media, allowing for a better understanding of the physical characteristics of snow and its impact on microwave signals. By effectively coupling the SMRT and RTTOV models, more accurate model support can be provided for remote sensing inversion of Arctic ice and snow environment parameters.

The application discloses a sparse array optimization method and system based on an improved arctic tern optimization algorithm, and the method comprises the following steps: according to an array element switch state matrix and an excitation amplitude matrix, an array antenna pattern optimization model is constructed under a preset constraint condition, and minimization of a peak sidelobe level is taken as an objective function; and the array antenna pattern optimization model is solved according to the improved arctic tern optimization algorithm, so that the lowest peak sidelobe level and the array element distribution are obtained. In view of the characteristics of a large number of optimization variables and strong nonlinearity of a traditional sparse array optimization, the algorithm adopts a sparse matrix strategy of joint coding of switches and excitation, and the array element switch matrix and the excitation amplitude matrix are optimized cooperatively, so that the solution space dimension is compressed significantly, and the solving efficiency is improved.