82 results about "Area coverage" patented technology

The invention discloses a low-orbit communication constellation target area coverage evaluation method and system. The method comprises the following steps: S1, dividing a low-orbit communication constellation target area into quadrilateral grids based on longitude and latitude lines; s2, calculating a single-satellite-to-single-point target coverage time sequence under the condition of considering the earth curvature; s3, counting the coverage time of the constellation to the target area by counting the coverage time of the single satellite to the target; and S4, comprehensively evaluating the coverage performance of the communication constellation on the target area through the coverage index. According to the method and the system, the coverage index of the constellation to the target area can be quickly calculated, the precision of constellation coverage evaluation is improved, the calculation is simple, and the real-time performance is high.

The invention relates to a wide-area coverage area high-precision deformation monitoring method based on an InSAR technology, and the method comprises the steps: obtaining the InSAR monitoring data of a plurality of data sources for a wide-area coverage area, carrying out the registration of the InSAR monitoring data, screening interference pairs according to the coherence, carrying out the interference pair combination of a single-view complex image set obtained through registration, and obtaining a single-view complex image set; performing time sequence analysis according to the interference pair combination result to generate a time sequence interference image; performing phase filtering and phase unwrapping on the time sequence interference image; for the time sequence interference image after phase unwrapping, baseline parameters are corrected based on a nonlinear least square method, and atmospheric delay errors are corrected based on a GACOS atmospheric delay model; according to the processed image, constructing a wide-area surface deformation rate map and a preset application scene surface deformation rate map, and analyzing the spatio-temporal evolution law of the wide-area surface deformation rate map and the preset application scene surface deformation rate map; and finally, visually displaying the wide-area surface deformation rate diagram, the preset application scene surface deformation rate diagram and the spatio-temporal evolution law analysis result.

The invention relates to the technical field of intelligent control of engineering machinery, and provides a tower crane hoisting whole process dynamic mapping and sensing coverage method and system. The method comprises the following steps: respectively mounting two rotary radars on a rotatable bracket of the tower crane; the current hoisting operation stage of the tower crane is obtained in real time; switching a shooting view angle of the double-radar module according to the hoisting operation stage, and controlling the double-radar module to obtain continuous point cloud data of the corresponding operation stage; tower crane operation parameters are collected, and continuous lifting hook tracks are generated in combination with continuous point cloud data obtained by the double-radar module; identifying a dynamic obstacle and a static background contained in the target monitoring space from the continuous point cloud data, and constructing a construction environment point cloud model; performing space-time registration on the construction environment point cloud model and the physical coordinate system, and establishing a global dynamic map; and a dynamic sensing area coverage map is constructed by fusing the continuous lifting hook track and the global dynamic map, so that the real-time sensing of the space environment of the tower crane hoisting operation is realized.

The invention relates to a remote sensing data coverage screening method based on a profit value, relates to the technical field of remote sensing image data processing, and solves the technical problems of insufficient region coverage optimization, serious computing resource waste, lack of flexible screening strategies and the like in the prior art. The method comprises the following steps: step 1, preparing a data set; 2, checking attributes of the data set; and step 3, performing a region coverage algorithm. According to the remote sensing data coverage screening method based on the profit value, by designing a coverage algorithm and introducing an image quality control and consistency guarantee mechanism, the efficiency and accuracy of remote sensing image data selection are remarkably improved. According to the method, the storage and calculation burden of redundant images can be reduced, the efficiency of image coverage is maximized, and the accuracy and consistency of global earth surface coverage are ensured.

The invention provides an SAR satellite scanning mode task planning method and system for the maximum coverage rate of multiple areas, and the method comprises the steps: obtaining the geographic information, satellite load parameters and orbit information of a target area, and enabling the load parameters to comprise a continuous wave position set in a scanning mode; the population of the swarm intelligent optimization algorithm is initialized, individuals represent a task planning scheme, and individual parameters comprise a beam position set and task timing information; iteratively updating the population until a preset iteration termination condition is met, and seeking an optimal task planning scheme; and after iteration is finished, outputting an optimal planning scheme. The method effectively solves the problems that in the prior art, a task planning method for an SAR satellite scanning mode lacks, and an existing method is insufficient in the aspect of multi-target area coverage rate.

The invention discloses an area coverage method and device for realizing a remote sensing task through satellite group cooperation, and relates to the technical field of satellite remote sensing, and the method comprises the steps: building a first coverage map after a satellite detects a task area, and when an obstacle is detected, releasing pheromones at the position of the obstacle to mark the obstacle, a first pheromone map is then generated based on the location of the obstacle and the release time of the pheromone. The satellite can establish communication with other satellites within the communication range, and the first coverage map and the first pheromone map are updated based on the map obtained through communication to obtain a third coverage map and a third pheromone map. Determining an uncovered area of the satellite cluster by combining the third coverage map and the third pheromone map, and selecting a target area from the uncovered area as a next coverage area of the satellite; the technical problems that the coverage rate is low and the repeated coverage rate is high due to the fact that unknown obstacles and non-coverage areas cannot be efficiently avoided in the current multi-satellite cooperative coverage technology are solved.

The invention relates to the field of urban traffic management and intelligent traffic, and discloses a macroscopic region division method based on urban traffic demands, which comprises the following steps: acquiring traffic node traffic demands of an urban dynamic road network, and constructing a traffic demand adjacency matrix, a degree matrix and a Laplacian matrix, utilizing a spectral decomposition method to extract aggregation degree features among the nodes; a K-means clustering algorithm is adopted to classify the node feature vectors, and a macroscopic region is preliminarily divided; gPS normalized coordinate features are introduced, node space distribution is modeled by using two-dimensional Gaussian distribution, and a comprehensive distance optimization region division result is calculated in combination with a spectral clustering feature distance; and finally, iteratively optimizing category distribution based on the comprehensive distance to obtain a macroscopic region division scheme with the minimum segmentation loss. According to the method, the rationality of traffic area division can be improved, the macroscopic area coverage range is optimized, the scientificity of traffic management is enhanced, and the urban traffic resource allocation efficiency is improved.

The invention relates to the field of area coverage control methods, and discloses a multi-agent system channel type area coverage control method based on arc length, which comprises the following steps: S1, target area division: dividing a channel type target area into a plurality of sequential sub-areas based on an arc length division method; s2, designing a distributed controller of a virtual leader agent, wherein the distributed controller of the virtual leader agent ensures that the arc length of a coverage area of each group of agents is in direct proportion to the number of the group of agents; and S3, designing an individual intelligent agent distributed controller, and enabling the intelligent agent to realize sequential team coverage control on the area S by combining the individual intelligent agent distributed controller with a distributed controller of a virtual leader intelligent agent. The distributed controller designed by the invention enables the intelligent agent to adjust the coverage area of the intelligent agent in real time according to the change of the actual environment.

The invention discloses a convex area coverage path planning method and system for an autonomous sweeper, which are applied to the technical field of path planning of autonomous mobile robots, and the method comprises the steps: generating an area coverage parallel track through a self-adaptive direction track generation algorithm based on a rotary caliper; the method comprises the following steps: constructing a GTSP model based on a region coverage parallel track, and standardizing the GTSP model into an ATSP model by adopting Noon-Bean conversion; and solving the ATSP model by adopting an LKH-VNS hybrid search algorithm to obtain a path planning result. According to the method, efficient and intelligent path planning is realized through adaptive direction orbit generation, standardized modeling from the GTSP to the ATSP and collaborative optimization of the LKH-VNS hybrid search algorithm.

The invention discloses an intelligent maintenance prediction and health management system for high-altitude equipment, and relates to the technical field of high-altitude equipment management, and the key points of the technical scheme comprise the steps: collecting operation parameter values of the high-altitude equipment, and dividing a condition region of the high-altitude equipment into region division sets according to the operation parameter values of the high-altitude equipment; wherein the region division set comprises a target fault region, a first to-be-divided region and a second to-be-divided region; setting an initial steering state of the detection device according to a position relation of the region division set; the initial steering state of the detection device and the condition data in the target fault area are processed and analyzed, and the initial working state of the detection device is set; the area coverage of the target fault area towards the detection device is collected, the parameter change trend of the high-altitude equipment is detected in real time, and the effect is that a fault detection management result is obtained according to the detection work feature set of each area, and intelligent maintenance prediction is achieved.

The invention provides a multi-agent cooperative detection multi-area coverage task planning method based on an improved discrete grey wolf optimization algorithm, and aims to realize comprehensive coverage detection of a plurality of non-intersecting target areas and remarkably reduce the completion time of a cooperative coverage task at the same time. The method comprises the following steps: firstly, comprehensively considering detection height, view field range and image resolution requirements, and taking minimization of a longest coverage path as a target to construct an accurate mathematical model; furthermore, the invention provides a multi-area coverage path generation method based on an improved rotating caliper method, and the method can accurately position an entrance point and an exit point of each target area, and optimizes a transition path between the target areas and a coverage path in the area. Aiming at the complexity of solving a large-scale problem, a discrete grey wolf optimization algorithm fusing heuristic population initialization, an adaptive iteration updating strategy and a variable neighborhood search operation is designed, so that the task planning efficiency is improved.

The invention provides a fixed-wing unmanned aerial vehicle cooperative area coverage monitoring optimization deployment method. The method comprises the steps of determining an effective coverage area of multi-unmanned aerial vehicle combined area coverage monitoring according to a space detection probability of an unmanned aerial vehicle to a target and a time monitoring probability generated by operation of the unmanned aerial vehicle; determining deployment parameters of an effective coverage area according to two-machine parallel and cooperative area coverage monitoring; and according to the deployment parameters of the effective coverage area, establishing a gridding multi-machine collaborative area coverage monitoring deployment scheme taking a square as a unit. According to the invention, through the space detection probability and the time monitoring probability, the effective coverage area of multi-aircraft joint area coverage monitoring can be determined more comprehensively and accurately, theoretical support is provided for flexible application of the multi-fixed-wing unmanned aerial vehicle in area coverage monitoring scenes such as border patrol and disaster rescue, and a multi-aircraft cooperative area coverage monitoring deployment scheme has the advantages of high efficiency and high reliability. The effective monitoring area is increased, the number of used unmanned aerial vehicles is reduced, and the cooperative efficiency of the unmanned aerial vehicle cluster is effectively improved.

The invention relates to the technical field of ship track area retrieval, in particular to a ship historical track area retrieval method which comprises the following steps: S1, constructing an index; s2, searching a historical track area; the method comprises the following steps: (1) a user gives a geographic space area and a time range as query conditions; (2) adjusting a coding mode of the Google S2; (3) decomposing a geographic space region input by a user by adopting a region coverage algorithm of Google S2 to obtain a group of geographic coding values containing the region; and (4) converting the obtained geocoding value, carrying out quick retrieval by utilizing a MySql database leftmost prefix matching principle and fuzzy query, and giving track data meeting conditions by the database. According to the method, the required query times are reduced, the response speed of the database is accelerated in combination with concurrent query, and the storage pressure of the index is relieved.

The invention discloses a missile-borne communication jammer area coverage optimization distribution simulation method and system, and the method comprises the steps: planning a motion track of a missile-borne communication jammer based on the environment factors of a current area; controlling the jammer to move along the motion trail, and analyzing interference performance data of the jammer to each group of communication radio stations in the current area when the jammer is arranged at different positions of the motion trail based on an OPNET simulation platform; determining corresponding time information and geographical location information when the jammer achieves the optimal interference effect according to interference performance data of the jammer to each group of communication radio stations in the current area when the jammer is arranged at different positions of the motion trail; a commander can be helped to display and master the quality of tasks completed by the missile-borne communication jammer in the movement process in real time and determine corresponding time information and geographic position information when the missile-borne communication jammer achieves the optimal jamming effect, and therefore the commanding and decision-making capacity of the commander is improved.

The invention discloses an SAR satellite strip mode task planning method, and aims to maximize the area coverage rate. According to the method, basic data containing time sequence geometric coverage primitives are obtained, and candidate planning schemes containing mixed parameters are initialized. During iterative optimization, an imaging interval is determined according to planning parameters, corresponding geometric primitives are identified, geometric merging calculation is executed to determine a planned coverage area, the area coverage performance is evaluated in combination with load constraint, and the parameters are updated by using an optimization algorithm. And outputting an optimal scheme after iteration. According to the method, through accurate geometric coverage calculation and constraint processing, the problems of inaccurate coverage estimation, incomplete constraint consideration and low planning efficiency are solved, and a feasible planning result with higher coverage rate and better performance can be quickly generated.

The invention relates to an agile imaging satellite narrow strip region splicing planning method and device and a medium, and the method comprises the steps: S1, constructing the visual strip information of a region target at least according to the three dimensions of the region target, the satellite and the time based on the orbit and load view field parameters of a constellation; s2, calculating a candidate strip set of a splicing task of each satellite for each regional target, and completing preliminary planning of regional splicing; and S3, optimizing the preliminarily planned area splicing task according to the satellite attitude maneuver capability and the area coverage index. According to the method, through greedy search, neighborhood search, attitude discretization and other algorithms, optimization calculation is carried out on the regional target splicing task, each satellite attitude maneuver and load imaging strip sequence is generated, the splicing coverage rate of constellations on the regional target can be effectively improved, and the splicing time consumption is reduced.

The invention discloses an unmanned aerial vehicle cluster multifunctional area revisit coverage method and system, and relates to the unmanned aerial vehicle technology, and the method comprises the steps: configuring the area revisit coverage parameters of an unmanned aerial vehicle cluster, and calculating an area convex hull polygon; determining a region coverage direction according to the calculated length direction of the region convex hull polygon; based on the area coverage direction, segmenting the to-be-covered area to obtain a plurality of to-be-covered sub-areas and corresponding coverage directions; determining an initial path point and a termination path point of the to-be-covered sub-region based on each to-be-covered sub-region and the corresponding covering direction; and calculating a cooperative revisit coverage path according to the initial path point and the termination path point of the to-be-covered sub-region. The invention provides a multi-group, multi-angle and multi-region unmanned aerial vehicle cluster revisit coverage route planning scheme based on region segmentation.

A system and method that automatically monitors product use, such as the type and amount of agricultural and / or horticultural product stored in and dispensed from a cartridge over time and / or by geographic location. Monitored data are stored in memory such as a tag on the cartridge and may be transmitted to a server for storage, aggregation, and analysis. The cartridge may be authenticated before being authorized for use for the benefit of a current user in dispensing the product. The cartridge may be refilled after confirmation of authorization codes on the cartridge and refilling equipment tags. The cartridge may be calibrated automatically based on the bulk density or other parameter of the product in the cartridge. Data may be aggregated from a plurality of cartridges automatically. As-applied data from individual cartridges may be used to verify, independent of operator input, treated area coverage and product application rate.

The application relates to the technical field of intelligent control of engineering machinery, and provides a tower crane hoisting whole-process dynamic mapping and perception coverage method and system. The method comprises the following steps: installing two rotating radars on rotatable supports of a tower crane; acquiring a current hoisting operation stage of the tower crane in real time; switching the shooting angles of the two radar modules according to the hoisting operation stage, and controlling the two radar modules to acquire continuous point cloud data of the corresponding operation stage; collecting tower crane operation parameters, combining the continuous point cloud data acquired by the two radar modules to generate a continuous hook trajectory; identifying dynamic obstacles and static backgrounds contained in a target monitoring space from the continuous point cloud data, and constructing a construction environment point cloud model; performing space-time registration on the construction environment point cloud model and a physical coordinate system, and establishing a global dynamic map; fusing the continuous hook trajectory and the global dynamic map to construct a dynamic perception area coverage map, and realizing real-time perception of the space environment of the tower crane hoisting operation.

The present disclosure is directed to methods and systems for tuning a wireless network propagation model. A propagation model system can generate a nominal propagation model of a coverage area using collected geographical data and network equipment information. The nominal propagation model can provide a representation of the wireless network and coverage areas. The propagation model system can continuously calibrate the generated propagation models with continuous wave data and crowdsourced data from user devices. The crowdsourced data can provide a real-time representation of the coverage capability in an area as the terrain and clutter in an area can change.

The invention provides a deep space star catalogue multi-detector air-ground collaborative deployment method based on reinforcement learning, and belongs to the technical field of planet surface detection. According to the method, a leap device and a patroller serve as detectors to cooperatively detect an unknown area of a deep space star catalogue, three types of communication channels are established between the detectors, and the communication radius between the different detectors is calculated; the method comprises the following steps: establishing constraints in the aspects of communication range, sensing range, coverage mode and energy, and setting an optimization target to keep communication connection between detectors under limited energy and maximize the total coverage area of the detectors; a leap device and a patroller are used as two agents, and an optimal deployment strategy is determined based on a multi-agent near-end strategy optimization algorithm. According to the invention, the method optimizes the regional coverage strategy, achieves the efficient distribution of resources, improves the detection efficiency and accuracy of a leap device and a detector in extreme terrains and complex environments, reduces the energy consumption while guaranteeing the coverage efficiency, and improves the overall energy utilization efficiency of the system.

The invention relates to an air route planning method for multi-machine area coverage search based on an improved K-Means algorithm. The method comprises the following steps: using an improved mixed K-Means clustering division strategy; the method comprises the following steps: dividing a target area into a plurality of sub-areas, taking projection points of a starting point and an ending point of multi-unmanned aerial vehicle cooperation at the boundary of the target area as fixed clustering centers, automatically selecting initial values of other clustering centers, and determining a polygonal boundary of the sub-area corresponding to each clustering center based on all the clustering centers; on the basis of preset unmanned aerial vehicle path parameters and polygon boundary information, generating a broken line type coverage path with the minimum total cost for each sub-region, and obtaining a path point sequence of each sub-region; and for the path point sequence of each sub-region, according to a minimum turning radius constraint condition, obtaining a smooth airway path satisfying kinematics constraint. According to the method, the technical problem that the adaptability is insufficient due to the fact that the coverage integrity cannot be guaranteed and path flight cannot be considered in the existing scheme is solved.

The application provides a full-area coverage path planning method and device for a mowing robot, a terminal and a medium. The method comprises the following steps: abstracting an environment map by setting a virtual boundary line of one or more target mowing areas; determining a long-axis direction of a bow shape for each target mowing area and rotating each target mowing area; dividing the one or more target mowing areas into one or more sub-areas based on the boundary points of the rotated target mowing areas; performing path planning for each target mowing area based on the long-axis direction of the bow shape of the target mowing area; and connecting the bow-shaped paths of the target mowing areas based on a navfn algorithm to obtain a full-area coverage path corresponding to the environment map. The application can realize full-area coverage path planning, has a high coverage rate even for a complex mowing area, has a low repetition rate, and greatly increases the path planning efficiency of the mowing robot.

This invention relates to a multi-satellite joint regional coverage planning method based on an improved multi-objective evolutionary algorithm, comprising the following steps: decomposing the area to be covered into discrete strip sets of all remote sensing satellites based on the imaging conditions of each satellite; binary encoding the strips in the discrete strip sets, using all encoded individuals as input to the improved multi-objective evolutionary algorithm, which employs a combination of the NSGA-III and S-CDAS algorithms to achieve an extreme solution preservation mechanism; constructing a multi-objective optimization model composed of multiple objective functions, and solving the multi-objective optimization model using the improved multi-objective evolutionary algorithm to obtain the regional coverage result. The improved multi-objective evolutionary algorithm in this invention can preserve extreme solutions, thus achieving satisfactory regional coverage results, and can also optimize the rationality of the regional coverage scheme from other objective dimensions.

The invention provides a message relay forwarding method based on vehicle-road cooperation, and aims to solve the problem that RSU (road side unit) or OBU (on-board unit) cannot effectively receive target information due to shielding, signal interference and other factors. The method comprises the following steps: firstly, comprehensively evaluating the communication quality of peripheral communication equipment to obtain key indexes including signal strength (RSSI), signal-to-noise ratio (SNR), bit error rate (BER) and the like; and screening out a reliable vehicle list of which the communication quality meets the requirement based on an evaluation result. And then, a K-means clustering algorithm is adopted to perform clustering processing on surrounding reliable vehicles, and a clustering number range (such as 1-K) is limited, so that the effectiveness and coverage rationality of a clustering result are ensured, and over-scattered vehicle distribution is avoided. In each cluster, a vehicle located or closest to the cluster center is selected as a relay node, and the relay node broadcasts target information, so that message diffusion in each cluster coverage area is efficiently realized. According to the mechanism, the area coverage capability and the service reliability of the target information are remarkably improved.

This invention provides a method for optimizing unmanned surface vessel (USV) area coverage paths based on constrained reinforcement learning, belonging to the technical field of autonomous navigation and path planning for marine unmanned systems. Each USV acts as an intelligent agent, and the USV area coverage path optimization problem is modeled as a constrained Markov decision process. The constraint condition is that the difference between the optimized path and the planned path is within a preset area. The reinforcement learning framework consists of: a policy network outputting an action probability distribution based on the current environmental state; a reward evaluation network evaluating the expected rewards of states and actions; and a cost evaluation network evaluating the expected cumulative cost of state-action pairs. With the goal of maximizing policy entropy and expected rewards, the penalty strength of the cost constraint is dynamically adjusted using Lagrange multipliers, jointly optimizing the policy network, reward evaluation network, and cost evaluation network. The minimum coverage requirement is modeled as a hard constraint condition for policy optimization, ensuring navigation safety and the integrity of the mission area coverage.

This invention relates to a method, device, and medium for multi-agent coverage search and task allocation path optimization. The specific method includes: scenario construction and problem description, which describes the characteristics of the task area, the attributes of agents and targets, and clarifies the area coverage search problem and the target task allocation problem; area coverage model design, which establishes a minimum task time model objective function and constraints, and then solves the area coverage model; and task allocation strategy and path planning algorithm, which, considering agent speed and target attributes, combines a greedy strategy and a genetic algorithm to allocate target exploration tasks to agents, optimize target exploration paths, and reduce total task time. Compared with existing technologies, this invention improves the efficiency of marine area search and target exploration through multi-agent cooperation, achieving full area coverage search and accurate target exploration.

The invention provides a high-precision troposphere delay modeling method, device and equipment under a sparse GNSS (Global Navigation Satellite System) site, and belongs to the technical field of spatial scientificity, and the method comprises the steps: calculating an initial ZTD (Zero Time Division) value of a real GNSS site through a first preset empirical model, constructing a ZTD residual time sequence by combining a GNSS actually measured ZTD value, analyzing a periodic signal, constructing a residual model to obtain a ZTD residual, and calculating the ZTD residual according to the ZTD residual. Further obtaining a ZTD improved value of the GNSS real station; based on a second preset empirical model in which an error correction term is introduced, virtual sites are arranged in the sparse region, and ZTD values of the virtual sites are generated; performing weighted fusion on the real and virtual ZTD values through a variance component estimation method to obtain a unified ZTD observation data set; and adopting spherical crown harmonic analysis to solve the adaptation coefficient, constructing a continuous ZTD model, outputting full-region data, and generating a high-resolution and high-precision ZTD map. According to the method, the defect that sparse GNSS station data coverage is insufficient is effectively overcome, and troposphere delay modeling precision, space continuity and area coverage integrity are remarkably improved.

The invention discloses a visual marking method and equipment based on fusion positioning, and a medium, belongs to the technical field of airport scene monitoring and management, and aims to solve the problems that the recognition accuracy is reduced, the high computing power requirement is needed, the real-time monitoring adaptability is poor, and the recognition efficiency is high due to the fact that existing airport scene monitoring is easily shielded by vision. And accurate geographical location information is difficult to obtain. The method comprises the following steps: performing coverage calculation of a maximum monitoring area on a visible area on an airport map to obtain a polygonal visible area; acquiring positioning terminal signals of key equipment and workers in an airport range; carrying out conversion processing of related camera point locations on a real-time geographic coordinate system in the real-time position information to obtain a camera coordinate system; performing conversion processing on the camera coordinate system to obtain a two-dimensional image coordinate system; mapping the two-dimensional image coordinate system into a polygonal visible area; and performing shielding labeling display on part of shielding targets in the initial labeling display information to obtain fused labeling display information.

The invention belongs to the technical field of collaborative interception guidance, and particularly relates to a bias differential game collaborative interception method based on region coverage. The method comprises the steps of establishing a probability distribution model of a target in an interception plane, performing Monte Carlo sampling, and converting a coverage strategy design into an optimal coverage problem of a finite center point in the interception plane; segmenting, iteratively solving the standard maneuver of each interceptor through a Voronoi diagram method to obtain the standard maneuver aTsi of each interceptor; and based on the standard maneuvering aTsi of each interceptor, deploying to a corresponding optimal array position and carrying out offset item design of a differential game guidance law to jointly realize the offset of the coverage range of each interceptor, and finally completing the optimal coverage and interception of the target. According to the method provided by the invention, the defects that an existing disc coverage model has limitation on maneuvering distribution simplification and only a fixed solution can be applied mechanically are overcome; the miss distance and the overload demand of the interceptor are obviously reduced, and the interception efficiency is improved.