316 results about "Wireless sensor networking" patented technology

The invention provides a coal mine goaf coal spontaneous combustion risk intelligent monitoring and early warning method and system, and relates to the technical field of coal mine safety management. A dot-matrix wireless sensor network is deployed in a target area, temperature and gas concentration data are collected in real time, and data processing is carried out through edge calculation. A dynamic characteristic matrix is generated based on transfer learning and a space-time diagram convolutional network, a comprehensive risk index is calculated, four early warning levels are divided, efficient and accurate coal spontaneous combustion risk monitoring and early warning are achieved, and an innovative solution is provided for mine safety management.

The invention discloses a traditional Chinese medicinal material standard base intelligent irrigation and fertilization method based on the Internet of Things and a decision making system, and relates to the technical field of agricultural informatization. Through multi-source data acquisition and intelligent analysis, the limitation of an existing irrigation and fertilization method is solved, accurate decision making and resource optimization are realized, comprehensive data are acquired by utilizing a soil moisture content sensor, a meteorological station and plant image acquisition equipment, and by combining principal component analysis, a long-short-term memory neural network and a block chain technology, the intelligent irrigation and fertilization method is realized. According to the system, the water and fertilizer requirements are accurately predicted, an irrigation and fertilization scheme is optimized, data credibility and traceability are ensured, meanwhile, real-time control and collaborative operation of equipment are achieved through edge calculation and a wireless sensor network, the resource utilization efficiency is improved, the production cost is reduced, and scientificity and sustainability of traditional Chinese medicine planting are remarkably improved.

The invention discloses an unmanned aerial vehicle three-dimensional flight path planning method for wireless sensor network data collection and energy supplementation, and belongs to the technical field of Internet of Things. A network is divided into a plurality of clusters through a density peak clustering algorithm, and a dynamic cluster head selection mechanism based on a routing protocol is designed to optimize the positions of cluster heads. The shortest flight path is determined by adopting a self-organizing mapping network introducing a penetration mechanism. Through a depth deterministic strategy gradient algorithm, the flight height of the unmanned aerial vehicle is dynamically adjusted, and meanwhile, the flight route of the unmanned aerial vehicle is planned, so that the unmanned aerial vehicle can efficiently collect data and supplement energy to sensor nodes in a charging range. According to the method, the distance of the unmanned aerial vehicle for charging the sensor and collecting data is obviously optimized, the energy utilization efficiency is improved, the energy supplement and data collection efficiency of the network is improved, and the network survival time is prolonged.

The invention relates to the field of communication transmission, and discloses an anti-interference secure transmission method for a wireless sensor network, which comprises the following steps of: acquiring residual electric quantity, position and communication quality parameters of a sensor node in real time; dynamically selecting a multi-hop routing path based on interference detection, excluding low-electric-quantity nodes, and preferentially selecting high-electric-quantity and low-interference area nodes to form a main path; at least one independent redundant path is generated according to the node electric quantity distribution and the interference intensity, and the relay node electric quantity of the redundant path is higher than a threshold value; monitoring electric quantity change in real time, and triggering a route dynamic reconstruction mechanism; and recovering complete information through a data fusion and verification algorithm. In addition, a charging request protocol is triggered for a low-power key node. According to the invention, by optimizing routing selection, redundancy transmission and energy management strategies, the anti-interference capability and transmission reliability of the wireless sensor network are improved, and the problem of data interruption caused by insufficient electric quantity of nodes is avoided.

The invention discloses a cable defect detection method of a binocular intelligent inspection robot, and relates to the field of image processing, and the method comprises the steps: firstly obtaining the state information of a cable, then carrying out the preprocessing and stereo matching of the image information of the cable, and then constructing a target detection and segmentation model; the target detection and segmentation model is adopted to detect and segment cable defects, and model sample data is updated in real time in an incremental learning mode; fusing the cable state information acquired by the infrared camera, the thermal imager and the wireless sensor network by using a multi-sensor data information fusion model; the cable is maintained and managed based on a detection result; according to the invention, the detection precision and accuracy can be improved, cables of different types and specifications can be handled, the adaptability and stability are ensured, and the real-time performance and accuracy of detection can be improved.

An intelligent grain storage control system based on a wireless sensor network comprises a grain storage environment monitoring subsystem which comprises a plurality of sensor arrays used for monitoring at least one grain storage environment parameter; the grain condition early warning subsystem is used for processing all the grain storage environment parameters by using a deep belief network and a long-short term memory network to obtain a real-time grain condition state; the intelligent control subsystem is used for generating an equipment control instruction according to the real-time grain condition state; and the overrun execution subsystem comprises a plurality of environment control devices, and the environment control devices are used for operating according to the device control instructions to change the environment of the grain depot. According to the invention, the grain storage environment parameters in the grain depot can be more flexibly collected, and the real-time grain condition state is predicted through the grain condition early warning model comprising the deep belief network and the long-short term memory network based on the grain storage environment parameters, so that the grain depot environment can be controlled with high precision, and full protection of grains is realized.

The invention discloses a wireless sensor network node fault diagnosis system based on a multi-scale Bayesian network, and relates to the technical field of wireless sensor networks. The system comprises the following components: a data acquisition and preprocessing module which adopts sensor nodes distributed in a monitoring area to acquire environmental parameters according to a preset frequency, wirelessly transmits the environmental parameters to a data processing unit, performs preprocessing in a self-adaptive mode, and stores the processed data into a database; according to the method, a micro-scale Bayesian network model, a node-scale Bayesian network model and a sub-network three-scale Bayesian network model are constructed, so that cross-scale fault analysis from a component level to a network level is realized, the micro-scale captures fault association of internal components, the node scale evaluates the overall sensor performance, and the sub-network scale analyzes a cooperation state between nodes. The multilevel information interaction and fusion mechanism can comprehensively consider node internal fault propagation, external communication interference and subnet topology influence, and significantly improves the integrity and accuracy of fault diagnosis.

The invention relates to the technical field of wireless communication and intelligent optimization, and particularly discloses a path planning method and system for data collection of a wireless sensor network, and the method comprises the steps: dividing a sensor working process, and defining a time window constraint condition, so as to build an energy consumption model; taking maximization of data collection amount, minimization of energy consumption and minimization of path length as optimization objectives, and constructing a path planning model based on multi-objective Pareto optimization; carrying out global exploration by adopting an improved ant colony algorithm, carrying out local optimization by taking an exploration result as an initial solution of a particle swarm algorithm, and dynamically adjusting pheromone distribution and algorithm parameters through a bidirectional feedback mechanism; and generating an optimal path of the mobile node according to an optimization result, and controlling the mobile node to execute a data collection task.

The invention relates to a hybrid ad hoc network and a safe and efficient communication method in a large-scale wireless sensor network. The method comprises the steps that a network topology construction module is used for designing a heterogeneous communication protocol with high adaptability based on the distribution condition of large-scale sensor nodes, and seamless cooperative work of multiple communication technologies is ensured; the ad-hoc network optimization module adopts a dynamic ad-hoc mechanism to realize autonomous discovery and network connection between nodes and improve the expansibility and flexibility of the network; the safety communication module is combined with an advanced encryption algorithm and an authentication mechanism to ensure the safety and the reliability in a data transmission process; and the efficient communication protocol module improves the data transmission efficiency and the overall performance of the network through the technical means of signal transmission optimization, interference management and the like. Through cooperative work of the modules, efficient, safe and reliable heterogeneous wireless communication can be realized in the large-scale wireless sensor network, and the requirements of the large-scale wireless sensor network in practical application are met.

The invention discloses a dynamic topology ad hoc network method based on environmental perception and adaptive optimization, and relates to the field of wireless sensor networks. Parameters (such as temperature, obstacle distribution and node energy consumption) of nodes are collected in real time; a multi-dimensional quantization parameter matrix including an obstacle coverage matrix, an energy consumption distribution matrix and a signal attenuation coefficient matrix is constructed, and path loss, communication delay and node energy consumption are fused and calculated to generate a node weight value by adopting an adaptive weight calculation mechanism, so that the priority of a communication link is dynamically adjusted. Compared with the prior art, the method has the advantages that the self-healing capability and the real-time performance of the network in a complex environment are remarkably improved, the global calculation overhead is reduced, the real-time performance and the expansibility of the system are improved, the node layout and the dynamic optimization of a communication path are realized, and the network load and the stability are balanced.

The invention relates to the technical field of component quality control, and discloses a remote component quality control system based on digital twin and wireless communication. A component data acquisition module of the system obtains multi-dimensional data of a to-be-monitored component through a wireless sensor network, and a component identification code is associated to generate a quality basic data set; the regional association analysis module establishes association mapping of adjacent components according to a spatial topological relation to form a quality association partition map; the environmental response evaluation module analyzes the influence degree of environmental factors on the performance of the component and generates an environmental response analysis report; the defect positioning module identifies problem points and constructs a defect distribution map; and the quality early warning module integrates the problem points and the associated parameters, marks the position of the potential safety hazard, and outputs a quality evaluation and risk early warning report. The system realizes remote and comprehensive control of component quality, and assists in timely finding and dealing with quality problems.

The invention discloses a wireless sensor network (WSN) target coverage method and device based on a chaos adaptive bat algorithm, and belongs to the technical field of wireless sensor network coverage. Aiming at the problems of limited communication range, poor adaptive capability and the like of the existing WSN, the method comprises the following steps of: initializing parameters, constructing a monitoring relation matrix to determine a fitness value, designing an adaptive inertia weight strategy, updating various parameters of a bat individual, and carrying out operations such as local search, adaptive adjustment of loudness and pulse emissivity and the like. And judging a termination condition to obtain an optimal solution in combination with an elitist strategy and chaos updating. The device comprises a network model construction module and the like and is used for executing the method. According to the method, the adaptive bat algorithm is adopted to establish the target coverage model, the elite strategy and chaos updating are combined, the algorithm is prevented from falling into local optimum, the stability is improved, the sensor node coverage area is effectively increased, the convergence speed is higher, the optimization capacity is stable, and the method is suitable for a WSN target coverage scene.

The invention discloses an evacuation path dynamic planning method and system based on an HPSO-IGWO algorithm, and relates to the technical field of fire safety and emergency evacuation. The system mainly comprises a fire information acquisition module, a data processing coordination module, a path planning module and an evacuation indication module. The fire information acquisition module acquires information such as the position, smoke concentration and temperature of a fire through a sensor, and transmits the acquired data to the data processing coordination module; the data processing coordination module sends the data to the path planning module, so that the evacuation path is planned and optimized by using an HPSO-IGWO algorithm, the path is dynamically adjusted according to the real-time condition of the fire, and the safety and optimality of the evacuation path are ensured; and finally, the path planning module sends the planned evacuation path information to each LED evacuation indicator through the wireless sensor network, and the indicators display the evacuation direction in real time according to the information sent by the server to guide people to evacuate along the planned path.

The invention discloses a 360-degree camera wireless sensor network coverage method for three-dimensional curved surface monitoring, and belongs to the technical field of three-dimensional curved surface monitoring. The method comprises the following steps: S1, acquiring a three-dimensional curved surface scene to be monitored, and constructing a 360-degree camera wireless sensor network coverage model; and S2, optimizing the 360-degree camera wireless sensor network coverage model by adopting an improved hummingbird swarm optimization algorithm, and obtaining a non-dominated coverage scheme based on an optimization result. The coverage scheme of the 360-degree camera wireless sensor network is optimized through guiding foraging, regional foraging and migration foraging of the hummingbird group. And obtaining a non-dominated coverage scheme of the 360-degree camera wireless sensor network through a non-dominated sorting method of the multi-target hummingbird group. The coverage effect of the 360-degree camera wireless sensor network is effectively improved, the coverage rate and the network connectivity are effectively improved, and the energy consumption of the 360-degree camera wireless sensor node is reduced.

The invention relates to the technical field of high-pressure gas filling, in particular to a high-pressure gas filling equipment temperature anomaly detection method based on wireless sensing. Comprising the steps of constructing a state transition equation and an observation equation; collecting temperature data of a key area in the high-pressure gas filling equipment; the acquired temperature data is preprocessed by using an improved robust adaptive unscented Kalman filter; carrying out local fusion on the preprocessed temperature data based on a serialization fast covariance overlapping algorithm; global fusion is carried out on the temperature data after local fusion based on an improved zebra optimization algorithm; and comparing the global fusion result with a preset threshold value, and outputting a temperature detection result in the high-pressure filling equipment. The method can cope with the extreme environment in the high-pressure gas filling equipment, and ensures the accuracy and reliability of temperature monitoring. Based on the design of the wireless sensor network, the system has the characteristics of flexible deployment, low cost and strong expansibility, and can be widely applied to multi-point temperature monitoring in the fields of energy and chemical industry.

The invention relates to the technical field of wireless sensor networks, and discloses a transformer substation ground deformation sensor monitoring signal collecting and monitoring method, system and device and a medium, and the method comprises the steps: dividing monitoring areas and selecting corresponding types of sensors according to ground deformation risks of different functional areas of a transformer substation; constructing a multi-channel synchronous signal acquisition system, synchronously acquiring sensor signals through a clock synchronization technology, and dynamically adjusting the sampling frequency; a wireless communication network is adopted to transmit the collected data, and data transmission is carried out; processing and analyzing the data transmitted to the monitoring center, and establishing a ground deformation prediction system comprising a finite element model, a neural network model and a time sequence model; and setting an early warning threshold based on the real-time analysis result, triggering a corresponding early warning signal, and displaying the monitoring data and the early warning state through a visual interface. According to the method, a data transmission and processing mechanism is improved, rapid and stable data transmission is ensured, the ground deformation trend is analyzed in time through an efficient algorithm, a reliable basis is provided for safe operation of a transformer substation, and potential risks are early warned in advance.

The invention provides a timestamp-free clock synchronization method and system based on an EKF, and belongs to the technical field of wireless sensor networks, and the method comprises the steps: obtaining the data packet sending time of an active node and the ACK returning time of the reference node based on the data packet interaction of the active node and the reference node, and obtaining the dynamic response time and the dynamic time difference; constructing an EKF observation model based on the dynamic response time and the dynamic time difference; receiving a silent node and reference node clock skew obtained by monitoring interaction between a plurality of active nodes and corresponding reference node data packets by the silent node; constructing an independent EKF channel based on the EKF observation model and the clock skew between the silent node and the reference node; and synchronizing an active node clock, a reference node clock and a silent node clock based on the independent EKF channel. According to the invention, multi-node collaborative clock synchronization without timestamp exchange is realized, and the accuracy of clock synchronization is improved.

The invention discloses an environmental pollution detection method and system based on a wireless sensor network, and relates to the technical field of environmental pollution monitoring, and the method comprises the steps: deploying a sensing node set in a to-be-monitored region, collecting and establishing node collection data, and analyzing and establishing self-calibration observation data through an edge calculation unit; configuring adjacent node communication to construct a wireless sensor network and form a temporary cluster; and according to the cluster reconstruction communication topology and the sampling frequency, executing data reconstruction acquisition, inputting a result and self-calibration observation data into a causal backtracking channel for verification, and outputting an environmental pollution detection result. The technical problems that a traditional air pollution detection method is difficult to adapt to a dynamically changing monitoring environment, monitoring coverage is incomplete, data collection precision is insufficient, and pollution sources cannot be traced are solved, air pollution detection coverage is more comprehensive, data are more reliable, the pollution sources can be traced, a complete process from detection to management is formed, and the detection efficiency is improved. And the technical effects of accurate evaluation and effective management and control are achieved.

The invention relates to the technical field of data communication, and particularly discloses a communication anti-interference parameter cooperative regulation and control method and system, and the method comprises the steps: obtaining energy state information; adjusting the frequency and fineness of environment perception activities, and perceiving and collecting environment perception information; determining a report format and a sending frequency according to the energy state information and the communication parameter set, and generating cooperative information according to the energy state information and the environment perception information based on the report format; the cooperative information is uploaded to the sink node based on the sending frequency, so that the sink node generates a parameter adjustment instruction according to the cooperative information and issues the parameter adjustment instruction to the corresponding sensor node; receiving a parameter adjustment instruction, and updating the communication parameter set based on the parameter adjustment instruction; according to the method, an energy sensing type self-adaptive closed-loop control mechanism is formed, and the problems of energy waste and response lag caused by a traditional fixed or non-energy sensing regulation and control mode when the energy of the wireless sensor network is limited and the environment is dynamically changed are effectively solved.

The invention discloses a soil moisture content real-time remote monitoring method and system for precise irrigation, and the method comprises the steps: dividing unit planting fields according to the terrain, and arranging a soil detection device in each unit planting field; a network transmission device, an irrigation pipe network and an irrigation control system are laid; starting from extraction of soil moisture content information, an open-circuit automatic control system for starting and stopping an irrigation system according to preset time and a closed-circuit automatic control system for determining starting and stopping time of the irrigation system through sensor data feedback and software analysis are respectively established through wired control and wireless sensor network technologies; irrigation is implemented through fixed sprinkling irrigation, drip irrigation and infiltrating irrigation, so that an intelligent precise irrigation control network system is formed.

The invention relates to the technical field of wireless sensor networks, in particular to a heterogeneous wireless sensor network coverage method for a mountain new energy construction site, which comprises the following steps of: constructing a three-dimensional mountain monitoring area, inputting related parameters and establishing a multi-target optimization model taking the non-coverage rate, the reciprocal of the connectivity rate and the minimum total energy consumption as targets; initializing a dung beetle population, dividing the dung beetle population into four classes, obtaining an initial coverage scheme, and screening a non-dominated coverage scheme solution set for storage; iteratively updating the positions of various types of dung beetles based on a multi-target dung beetle optimization algorithm; the current coverage scheme and the archive set are combined, the archive set is updated after non-dominated sorting, and dense solutions are discarded to guarantee diversity when the scale is over-scale; and outputting a solution set after the maximum number of iterations is reached, and selecting a target scheme to complete node deployment. The method is adaptive to complex mountain scenes, network coverage and communication quality are improved, energy consumption is reduced, local optimum is avoided, and mountain monitoring effects of high coverage, low energy consumption and strong adaptation are achieved.

The invention discloses a WSN (Wireless Sensor Network) efficient target coverage method and device based on an improved tuna algorithm, relates to the field of wireless sensors, and solves the problem of high complexity of large-scale node rotation scheduling in a wireless sensor network. Comprising the following steps: S1, initializing parameters: determining the size of a target area, the number of sensors, the number of rounds of the maximum service life of the sensors, the coverage radius, the initial variation rate and the final variation rate, and randomly initializing sensor nodes and the positions of a target; s2, constructing a coverage relation matrix R; s3, initializing a three-dimensional population matrix pop, wherein the dimension is the number of sensor working rounds * the number of sensors * the number of populations; s4, population fitness is calculated; S5, an improved tuna algorithm main loop is executed; and S6, current iteration information is output, and a fitness change curve is drawn. The technology has a good application prospect in the fields of industrial Internet of Things and the like.

The invention discloses a coal mine methane leakage early warning method and system based on a wireless sensor network, and relates to the technical field of leakage early warning. The method comprises the following steps: deploying a sparse sensor network in a coal mine area, and constructing a coal mine cloud picture; real-time data of a coal mine area are collected and transmitted back to the central control processor; if the real-time data represents that no leakage exists, but the real-time data is in a metastable critical state, carrying out directional sensing management by calling a mobile sensing component in the sparse sensing network; if the real-time data represents that leakage exists, a leakage verification assembly is triggered, the data are synchronized to a coal mine cloud picture, cloud picture network screening and superposition state definition based on leakage events are carried out, and leakage data are determined and leakage early warning management is carried out based on superposition state collapse of candidate leakage paths by introducing a walking operator. The technical problem that in the prior art, coal mine methane leakage monitoring depends on a fixed sensing point, and the leakage state cannot be dynamically tracked is solved, and the technical effect of coal mine methane leakage dynamic positioning is achieved.

This invention provides an energy-saving clustering routing method for wireless sensor networks based on improved multi-target ant colony optimization, comprising: Step 1, initialization; Step 2, determining the set of active sensor nodes in the current round; Step 3, completing network clustering; Step 4, maintaining the Pareto optimal path solution set; Step 5, repeating steps 2 to 4 until the maximum number of iterations is reached or the solution set converges, outputting the Pareto optimal path solution set as the routing scheme for network data transmission. This invention improves network energy efficiency and extends network lifetime by constructing a globally collaborative energy management framework that integrates sleep scheduling, cluster head election, and routing optimization, while ensuring the real-time performance and reliability of data transmission.

Ambient Internet-of-Things (AIoT) refers to an ecosystem of a large number of objects in which every item is connected into a wireless sensor network using low-cost self-powered sensor nodes. The described embodiments enable the configuration and management of an intermediate node for improved communication in AIoT systems. An example wireless communication method includes receiving, by a wireless device from a network node, data and / or signaling, and transmitting, to one or more AIoT devices, the data and / or signaling. In this example, the network node is configured to receive the data and / or signaling via a core network, and the wireless device is configured to perform as a dedicated intermediate node between the network node and the one or more AIoT devices.

The application discloses a wireless sensor network distributed guaranteed probability estimation method under a deception attack, and specifically comprises the following steps: a nonlinear system mathematical model under the condition that innovation is deceived is established; a neural network-based distributed state estimator structure model is established according to the nonlinear system mathematical model under the condition that innovation is deceived; a neural network weight matrix adaptive updating strategy is designed; a distributed guaranteed probability state estimator gain is designed; and estimator parameters are optimized to achieve local optimal estimation performance; the application comprehensively considers the nonlinear characteristics and the influence of malicious attacks existing in actual engineering, can be widely applied to military monitoring systems and environmental monitoring systems, estimates the state of a monitoring or monitoring object, is more in line with engineering application, and is high in practicality.

The application relates to a wireless sensor network hierarchical routing optimization method and system based on a quantum mound beetle mechanism, relates to the technical field of wireless communication, and aims to solve the technical problems of unbalanced energy consumption and short network life of a wireless sensor network in a traditional method. The technical points of the application include the following steps: establishing a wireless sensor network system model; determining the number of clusters and dynamically clustering, and simultaneously establishing a network node dynamic clustering cost function; initializing quantum mound beetle groups and setting parameters, and calculating the organic matter decomposition degree of all quantum mound beetles to determine the global optimal quantum position of the quantum mound beetle groups; quantum position evolution of the quantum mound beetles and obtaining the global optimal quantum position by using a selection mechanism; quantum mound beetle mechanism evolution termination judgment, outputting the current wireless sensor network cluster center; wireless sensor network dynamic cluster head election; and the wireless sensor network performing stable data transmission while updating the network state. The application effectively improves the energy consumption efficiency of the wireless sensor network and effectively prolongs the network life.

The invention discloses a multi-field coupling intelligent inclination angle plane physical similar simulation experiment system and method. The system comprises an experiment platform with a controllable inclination angle, a stress monitoring module, an optical deformation monitoring module and an acoustic emission monitoring module. The experiment platform realizes high-precision adjustment and stable maintenance of an inclination angle of + / -0.1 degree through cooperation of hydraulic drive and a mechanical lock. The stress module adopts a wireless sensor network to monitor a stress field; the optical module is used for measuring full-field displacement strain based on a CCD camera and a digital image related technology; and the acoustic emission module positions a rock stratum fracture signal through the probe array. The method comprises the steps of platform deployment, inclination angle adjustment, system debugging, synchronous mining monitoring and the like. According to the invention, inclination angle accurate control and multi-physical field information synchronous integrated acquisition are realized, and the system is suitable for inclined coal seam mining rock stratum movement and disaster mechanism research.

The application relates to the technical field of Internet of Things data processing, and discloses a local reasoning and abnormality detection method for a wireless sensor network, which comprises the following steps: constructing a hypergraph model according to a sensor node set in the sensor network and corresponding association relations, and defining an energy function; applying a sensitivity constraint to the potential function, so that the potential function satisfies a bounded difference condition; determining a constraint range of coupling strength and a truncation order m; performing local deterministic approximate reasoning to obtain a conditional edge probability of a target sensor node; calculating an abnormality score of the target sensor node, and performing abnormality detection. In the wireless sensor network, a hypergraph Gibbs model with a sensitivity constraint is constructed, and based on strong spatial mixing ensured by theory, the application realizes the probability reasoning of a deterministic error bound only by relying on a limited-step local communication, so that the explainable abnormality detection and positioning are completed on a resource-limited edge device.

The application discloses a robot attack-resistant positioning method based on geometric consistency voting and adaptive M estimation, and belongs to the field of wireless sensor network positioning. The method comprises the following steps: obtaining anchor node coordinates and ranging, and initializing a global positioning solution; enumerating three-anchor combinations to generate a sub-positioning solution, performing geometric consistency voting according to the deviation of the sub-positioning solution from the global positioning solution, assigning a credibility weight to the anchor node, and eliminating low-score nodes; calculating a residual error, adaptively determining an M estimation threshold value by using a median absolute deviation, and generating a robust weight by using a Tukey double weight function; fusing the two weights to obtain a comprehensive weight; constructing a weighted least square problem to update the global solution; and iterating until convergence. The application does not explicitly estimate attack values, and malicious nodes are inhibited by a double mechanism of geometric constraint and residual error statistics, is robust to different attack modes, is adaptive in parameters, and is convenient to implement in engineering.