A method for deploying monitoring nodes for high-altitude geological disaster chains based on wireless ad hoc networks

Abstract

This invention discloses a method for deploying monitoring nodes for high-altitude geological disaster chains based on a wireless ad hoc network, relating to the field of geological disaster monitoring and early warning technology. The method includes the following steps: S1, acquiring interference characteristics and establishing a time baseline through a time-frequency observation layer triggered by an earthquake; S2, identifying cross-channel coupling relationships and determining sensitive nodes based on the energy spectrum and drift baseline; S3, reconstructing convergent paths by replacing distorted channels with shadow links; S4, constructing a time stack and suppressing routing oscillations with a hysteresis gate; S5, generating time-varying virtual impedance routes based on the time stack to achieve peak-shifting and stable forwarding; S6, completing loop-breaking control of residual crosstalk through inverse-phase traction and metasurface antennas, ultimately ensuring long-term stable network operation. This invention achieves stable convergence and closed-loop control of the ad hoc network through interference feature extraction, path reconstruction, time stack hysteresis suppression, virtual impedance peak-shifting, and inverse-phase loop-breaking interference control.

Description

Technical Field

[0001] This invention relates to the field of geological disaster monitoring and early warning technology, specifically to a method for deploying high-altitude geological disaster chain monitoring nodes based on a wireless ad hoc network. Background Technology

[0002] "Deployment of Monitoring Nodes for High-Altitude Geological Disaster Chains Based on Wireless Ad Hoc Networks" refers to the use of wireless ad hoc network technology to organically connect multiple dispersed monitoring nodes in high-altitude geological disaster chain areas (such as areas prone to landslides, collapses, and debris flows) according to the spatial distribution of the disaster chain. With an edge gateway as the core, signal interconnection between nodes and between nodes and the gateway is achieved through relaying. In this deployment method, monitoring nodes can actively trigger and upload on-site data in abnormal situations, and can also passively respond to instructions from the edge gateway, thus achieving two-way data interaction and flexible control. Simultaneously, by designing a wireless ad hoc network protocol with a priority scheduling mechanism, monitoring information can be transmitted in different time periods and according to the different locations and risk levels of the disaster chain, ensuring that important data arrives first and improving the real-time performance, stability, and reliability of the overall monitoring. This deployment method not only solves the problems of difficult cabling and signal obstruction in complex high-altitude terrain, but also builds an adaptive and scalable disaster chain monitoring system, providing efficient data support for disaster early warning.

[0003] The existing technology has the following shortcomings:

[0004] In existing technologies, when monitoring nodes are deployed in high-altitude geological disaster chain areas and affected by earthquake aftershocks, the nodes' radio frequency circuits are highly susceptible to electromagnetic coupling crosstalk due to strong vibrations and environmental disturbances. This causes interference between originally independent signal channels, resulting in abnormal distortion of communication signals. In this situation, the ad hoc network protocol automatically triggers topology reconfiguration to maintain link connectivity. However, due to the cumulative effect of interference, routing loops are easily formed during the reconfiguration process. Data is repeatedly forwarded within the loop and cannot reach the edge gateway, ultimately leading to loop lock-up. Once this phenomenon occurs, the entire ad hoc network will remain in a non-convergent state for a long time, and monitoring data cannot be transmitted stably, severely hindering real-time monitoring and early warning of disaster chains.

[0005] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0006] The purpose of this invention is to provide a method for deploying high-altitude geological disaster chain monitoring nodes based on wireless ad hoc networks, so as to solve the problems in the background art mentioned above.

[0007] To achieve the above objectives, the present invention provides the following technical solution: a method for deploying high-altitude geological disaster chain monitoring nodes based on a wireless ad hoc network, comprising the following steps:

[0008] S1, construct a time-frequency observation layer triggered by earthquakes in the high-level geological disaster chain area, deploy dual-path coupled probes and introduce phase calibration beacons, collect dynamic electromagnetic interference field information, and extract crosstalk energy spectrum and time drift baseline as reference for subsequent processing;

[0009] S2, based on crosstalk energy spectrum and time drift baseline, performs causal coherence decomposition, identifies cross-channel coupling kernels and analyzes energy propagation direction, and identifies the set of sensitive nodes that cause routing anomalies;

[0010] S3 constructs a counterfactual replay chain based on the set of sensitive nodes, replaces the signal distortion segments with shadow links, reconstructs a convergent routing trajectory, and restores the time series consistency between nodes;

[0011] S4 deploys dual mirror time stamps around the routing trajectory to build a unified time stack and injects hysteresis gates into it to suppress oscillations caused by loop backflow and topology reconstruction;

[0012] S5 generates time-varying virtual impedance routes based on the time stack, constructs a topological barrier energy landscape, outputs a node forwarding sequence with peak-shaving characteristics, and guides the network into a stable convergence state.

[0013] S6, after the network enters a stable convergence state, performs time-reversal phase traction, drives the programmable metasurface antenna array by injecting inverse phase micropulses, and absorbs residual crosstalk energy in combination with the shadow energy storage structure to complete the loop-breaking control of the coherent topology and realize closed-loop dynamic regulation.

[0014] Preferably, step S1 includes:

[0015] Within the high-altitude geological hazard chain area, select typical areas with risks of landslides, collapses, or debris flows, and determine the layout boundary by combining geological survey results and topographic modeling data;

[0016] Dual-path coupling probes are deployed at equal intervals within the deployment area. Each coupling probe collects disturbance electrical signals from the ground and the ground surface, and connects to a high-sensitivity sampling terminal via an independent wire.

[0017] A set of phase calibration beacons is installed around each probe. After the earthquake is triggered, the beacons actively emit reference pulses with constant amplitude and frequency and consistent phase, and synchronously inject them into the adjacent probes to form a phase reference.

[0018] After the earthquake disturbance occurs, the original disturbance waveforms of each channel are collected, and the amplitude change, phase shift and main peak energy density are extracted to generate crosstalk energy spectrum and time drift baseline.

[0019] Preferably, step S2 includes:

[0020] Based on the crosstalk energy spectrum and time drift baseline, an interference time chain is constructed and a multi-node influence path map is generated;

[0021] Based on the path map, the propagation levels are divided, frequency domain features are extracted, and node pairs with stable phase delay and high coherence amplitude are identified to construct a cross-channel coupled kernel database.

[0022] A propagation path network is constructed based on the coupled kernel database and an energy propagation map is generated. An energy vector field is formed by combining the three-dimensional geographic coordinates.

[0023] In the energy vector field, path aggregation points and disturbance abrupt change points are identified. The path oscillation response of nodes is verified by the disturbance simulation playback test method, and finally the set of sensitive nodes is determined.

[0024] Preferably, step S3 includes:

[0025] Based on the set of sensitive nodes and the list of distorted channel segments, abnormal transmission paths are identified, and corresponding shadow links are constructed to replace the original path segments.

[0026] The shadow link path is determined by hop count control, spatial boundary constraints, signal quality assessment, and return integrity rate screening.

[0027] Node timing reconstruction is performed with the time drift baseline as a reference, and time alignment and error calibration are performed on all nodes in the shadow link.

[0028] By integrating shadow links into the main path architecture through path integration operations and applying signal forwarding suppression mechanisms and routing table redirection control, path convergence and stable operation are achieved.

[0029] Preferably, the selection of the shadow link path should meet the following requirements: the number of hops should not exceed one and a half times the number of hops of the original path, the path space range should be limited to within fifty meters of the original path, the signal-to-noise ratio of all relay nodes should be higher than 25 dB, and the signal return integrity rate should not be lower than 95%.

[0030] Preferably, step S4 includes:

[0031] Dual mirror time stamp devices are deployed at both ends of the reconstructed route trajectory starting node and receiving node to complete time synchronization and direction verification between path jump points;

[0032] Collect time-stamped data of all path nodes, construct a time stack structure, and calibrate the propagation delay and interference sensitivity coefficient to generate a routing time series matrix;

[0033] Identify path segments in the time stack that exhibit non-linear growth characteristics, and inject hysteresis gates with adjustable response delays to form a forwarding buffer and path freezing mechanism.

[0034] Multiple rounds of path transmission tests were conducted to verify the time stamp synchronization, gate delay control, and path topology oscillation suppression effects, ensuring that the time stack is controllable and stable.

[0035] Preferably, the injection position of the hysteresis gate is limited to the position in the time stack where the propagation delay increase exceeds twice that of the previous level and is accompanied by a sudden drop in signal energy and a peak in phase disturbance, so as to ensure that the path oscillation source is accurately constrained.

[0036] Preferably, step S5 includes:

[0037] Extract the average propagation delay of each path node in the time stack, generate a node time impedance lookup table, and construct a multi-period time-varying virtual impedance trajectory.

[0038] By superimposing the impedance trajectories of each node with the historical energy distribution, a topological barrier map with spatial continuity and temporal fluctuation perception is formed, and barrier nodes and low impedance regions are identified.

[0039] Based on impedance differences, the path segments are divided, a segmented staggered forwarding scheduling plan is formulated, and node forwarding is triggered sequentially according to impedance priority to generate a path-level forwarding sequence plan.

[0040] Set a sub-segment convergence verification window, evaluate whether data transmission is completed according to schedule segment by segment, adjust the forwarding frequency and timestamp based on the feedback results, and finally achieve network-wide collaborative convergence.

[0041] Preferably, in the segmented peak-shifting forwarding scheduling plan, the node forwarding triggering time interval of each sub-segment is set to a preset multiple of the maximum propagation delay in that segment to avoid forwarding overlap between nodes. When any sub-segment fails to meet the convergence verification condition for two consecutive rounds, its path is marked as a jitter path segment, and a backup path replacement mechanism is activated to maintain the continuous and stable convergence of the overall network.

[0042] Preferably, step S6 includes:

[0043] Identify nodes in the communication path that exhibit asymmetric phase reversal and delay retraction, extract the backpropagation time period, and establish a list of inversion intervention targets;

[0044] Injecting inverse phase micropulse signals into the intervention target node and propagating them backward in time stack order at the end of the path to detect whether there is a persistent phase reconstruction response in the path;

[0045] A programmable metasurface antenna array is deployed around the detection node, and the loop path is blocked in physical space through the synergistic effect of the phased reflector unit and the shadow energy storage structure.

[0046] Adjust forwarding priorities based on the traction results and block risky directions to ensure that the entire network topology uses positive propagation as the only path, forming a dynamic control structure of closed-loop and closed-loop operation.

[0047] The technical effects and advantages provided by the present invention in the above technical solution are as follows:

[0048] This invention constructs a time-frequency observation layer triggered by earthquake events to collect electromagnetic interference characteristics in real time and extract crosstalk energy spectra and time drift baselines, achieving accurate modeling of physical interference sources. Subsequently, using causal coherence decomposition and counterfactual playback chain techniques, it actively identifies and repairs distorted node links in the communication path, ensuring stable convergence of the routing trajectory. Furthermore, by deploying dual-mirror timescales and hysteresis gates to construct a unified time stack structure, it suppresses loop backflow and signal oscillation in topology reconstruction. Based on this, it generates time-varying virtual impedance routes with segmented peak-shifting characteristics, guiding the network to stable operation segment by segment. Finally, using a programmable metasurface antenna array driven by inverse-phase micropulses and a shadow energy storage structure, it achieves active identification and physical loop-breaking control of residual crosstalk paths, constructing a coherent topology with long-term evolution adaptability and closed-loop control capabilities. This method comprehensively improves the anti-interference, adaptability, and topological stability of wireless ad hoc networks in high-altitude geological disaster chain areas, providing a solid technical guarantee for achieving high-frequency, high-precision disaster monitoring and early warning. Attached Figure Description

[0049] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0050] Figure 1 This is a flowchart of a method for deploying monitoring nodes for high-altitude geological disaster chains based on a wireless ad hoc network, according to the present invention. Detailed Implementation

[0051] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, they are provided so that the description of this disclosure will be more complete and fully convey the concept of the exemplary embodiments to those skilled in the art.

[0052] This invention provides, for example Figure 1 The method for deploying high-altitude geological disaster chain monitoring nodes based on a wireless ad hoc network, as shown, includes the following steps:

[0053] S1, a time-frequency observation layer is constructed in the high-level geological disaster chain area with earthquake events as the triggering condition. Dual-path coupled probes are deployed and phase calibration beacons are introduced to collect dynamic electromagnetic interference field information when earthquake disturbances occur, and to extract crosstalk energy spectrum and time drift baseline to form a reference for subsequent signal processing.

[0054] In high-altitude geological hazard chains prone to earthquakes, a method based on time-frequency interference characteristics is used to deploy monitoring nodes. The specific process is as follows:

[0055] Within high-altitude geological hazard chains, typical areas with risks of landslides, collapses, or debris flows are selected, and the deployment boundaries are determined based on geological survey reports and 3D terrain modeling results. The deployment area should cover fault slip zones, slope crest fissure zones, gully confluences, and locations where wind erosion has exposed rock and soil. Historical earthquake damage data should be considered, prioritizing fissure-rich zones with high seismic sensitivity. Dual-coupled probes are deployed at equal intervals along these key locations. These probes utilize insulated ceramic shells and platinum electrode contact ends. One end is embedded 10-15 cm into the rock mass, while the other end is exposed within 10 cm of the surface, directly contacting the air, to collect disturbance electrical signals from both the ground and the surface. A shielded connection line is installed at the probe's tail, leading to an independent, highly sensitive sampling terminal. To establish a stable phase reference, a set of phase calibration beacons is installed within a 3-meter radius of each probe. Each beacon comprises a high-frequency resonant cavity, a piezoelectric excitation source, and a vibration initiation pulse generator. Upon receiving a foreshock signal, the beacon automatically activates, emitting a reference pulse train with constant amplitude and frequency, consistent phase, and unique direction. This train is synchronously injected into adjacent probes via a coupling capacitor path, achieving instantaneous waveform alignment and phase reference establishment. The beacon's activation threshold is set to a vertical acceleration greater than 0.78 m / s² (equivalent to approximately 0.08 g), ensuring a response only to vibration events of engineering significance.

[0056] After deploying the coupling probes and phase calibration beacons, the seismic disturbance data acquisition phase commenced. Each probe signal was connected via an independent channel to a 16-bit resolution analog-to-digital converter (ADC) acquisition unit, with a sampling rate set to 5000 times per second. Upon triggering of a seismic event, all channels entered parallel acquisition mode, using the initial reference pulse emitted by the beacon as a unified starting point, continuously recording the raw disturbance waveforms for at least 10 seconds before and after the event. After preliminary processing of the raw data, the amplitude variation, phase shift, and corresponding peak energy density per unit time were extracted based on the differential trajectories of the two channel signals. By registering and analyzing the phase change curves of different probes at the same time, an interference coupling relationship matrix was established, and a preliminary crosstalk energy spectrum was generated based on the coupling strength. To accurately calibrate the response delay of different nodes, the time axis of all signals is further adjusted to the zero point corresponding to the beacon pulse. By performing trend fitting on the small drifts in different time periods, a four-dimensional time drift baseline table is generated, which includes probe number, response delay, phase drift value, and signal similarity. This baseline table is used to identify the dynamic changes in the disturbance propagation link.

[0057] Based on the generated crosstalk energy spectrum and time drift baseline table, the interference signals were cleaned, classified, and their evolution paths reconstructed. First, the high-frequency signals within 3 seconds before and after the earthquake triggering time were compared point-by-point with the background noise frequency band to eliminate non-seismic disturbance signals. Then, based on the concentration of energy distribution in the energy spectrum, the spectrum of each probe was divided into multiple fixed frequency bands, and the energy change rate and phase perturbation of each frequency band in the three stages before, during, and after the earthquake were extracted. These perturbation features were mapped to frequency domain transition trajectories and combined with spatial geographic coordinates to form a complete three-dimensional interference evolution model. By marking phase reversal nodes, peak coupling paths, and their propagation directions in the model, the transfer process of disturbance energy between each probe was gradually revealed, ultimately generating an interference propagation trend table consisting of probe number, initial disturbance time, phase reversal time point, maximum coupling direction, and corresponding energy value. This trend table clearly indicates the possible starting point of signal distortion and its outward radiation path, providing an accurate basis for subsequent fault route identification.

[0058] Based on the energy accumulation area reflected in the interference propagation trend table, and combined with the previously established time drift baseline table, a response synchronization analysis was performed on all affected nodes. Using the first disturbance moment of each node as a reference point, the average response delay between that node and the remaining probes was calculated. If the delay exceeded a set threshold of 0.5 milliseconds, it was identified as a node with inconsistent response. Probes with consistent responses but abrupt changes in phase waveform were further identified as high-risk disturbance sources. The identified nodes were combined to form a highly sensitive disturbance point set, and an interference influence weight matrix was constructed based on their spatial distance and temporal response differences. A two-dimensional projection was then performed on the matrix to form a standard interference map containing three dimensions: time, space, and energy. Finally, using this interference map as input, a "time-frequency disturbance response reference layer" with spatial continuity, temporal progression, and energy visibility was derived. This reference layer possesses both the characteristics of the actual seismic disturbance field and serves as a quantitative benchmark for coupling identification, making it a crucial input data source for subsequent causal coherence decomposition and sensitive node calibration operations.

[0059] S2, based on the extracted crosstalk energy spectrum and time drift baseline, performs causal coherence decomposition, identifies the cross-channel coupling core between monitoring nodes layer by layer, analyzes the energy propagation direction, and identifies the set of sensitive nodes that are prone to inducing routing anomalies;

[0060] After obtaining crosstalk energy spectrum maps and time drift baseline tables with time alignment accuracy and spectral stability, the following operations were performed to identify cross-channel coupling relationships and sensitive node locations among disaster chain monitoring nodes:

[0061] Based on the constructed interference propagation trend table and time drift baseline table, interference initiation nodes with concentrated response times and significant spectral abrupt changes are selected and used as the starting point references for causal paths. Interference time chains are constructed centered on these initiation nodes, extending to all surrounding nodes. Each time chain consists of specific indicators such as signal initiation response time, phase rise slope, spectral jump position, and energy concentration segment. Each chain represents a potential interference transmission relationship between a pair of nodes. The construction of the time chains is based on a sliding window sequence point-by-point comparison method, with a window step size of 0.5 seconds and a time span of 5 seconds before and after the vibration trigger point. Data differences between each group of nodes are standardized using the time drift baseline table to eliminate offsets caused by differences in the accuracy of local clocks at different nodes. All constructed time chains are sorted according to the time sequence from the interference initiation point to the response point and labeled with directional indicators, thus obtaining a multi-node influence path map with preliminary causal relationship judgment capabilities, providing ordered input for subsequent coupling analysis.

[0062] Based on the path map, the interference propagation process is divided into multiple propagation levels according to time sequence, with each level representing a set of response nodes within a fixed time delay. Points of rapid signal amplitude transitions, sudden phase reversals, and instantaneous spectral collapses occurring in each propagation level are combined and paired to construct a set of suspected coupled node pairs. The frequency domain signal of each pair of nodes is decomposed into four frequency bands: 50–150 Hz, 150–300 Hz, 300–600 Hz, and 600–1000 Hz. The cross-correlation amplitude, phase angle variation trend, and waveform envelope preservation are extracted for each band. If a node pair exhibits a stable phase delay trend and high coherence amplitude (above 60% of the reference beacon amplitude) in three or more frequency bands, it is determined that an actual energy coupling relationship exists and is designated as a cross-channel coupling core. To ensure that the identified coupling kernels possess directional and hierarchical awareness capabilities, the propagation hierarchical number, signal start and end time points, response delay interval, and spectral peak drift rate are recorded for each set of coupling kernels, ultimately forming a cross-channel coupling kernel database. This database comprehensively characterizes the dynamic coupling path distribution characteristics between nodes and serves as a fundamental data source accurately reflecting the laws of interference propagation from the signal evolution perspective.

[0063] After obtaining all cross-channel coupling kernel data, these coupling kernels are used as nodes to construct a propagation path network. The propagation path network is connected by unidirectional edges, with the edge weight defined as the phase perturbation amount when a unit of energy flows through, and the direction pointing from the energy source node to the energy receiver node. Combining the start and end times of all coupling kernels with the propagation path hierarchy number, an energy propagation map containing complete direction vectors is constructed. The map is projected onto a 3D geographic coordinate model to form a 3D energy migration path map. Subsequently, vector aggregation analysis is performed on the path map based on propagation path density and node aggregation degree. Specifically, within a 1-meter radius around each node, the number of paths pointing to that node is counted. If the number exceeds twice the average and the path direction concentration is greater than 0.7 (calculated from the angle between direction vectors), the node is identified as an energy aggregation point; conversely, if a node has large changes in path direction, frequent path breaks, and poor energy continuity, it is marked as a perturbation abrupt change point. The spatial distribution of all aggregation points and mutation points is further mapped into a perturbation energy vector field, from which interference clusters, path turning points, and dense coupling core zones can be identified. These regions often correspond to topological bottlenecks or unstable nodes in network communication.

[0064] By combining the constructed energy vector field, path propagation map, and coupling kernel database, a set of sensitive nodes with high potential for perturbation feedback was identified. To verify their impact on the communication topology, a perturbation simulation playback method was used to conduct path stability tests. This test input an artificial perturbation signal with an amplitude of 0.98 m / s² (approximately 0.1 g) upstream of each candidate sensitive node. The simulated signal was a continuous oscillating waveform over 3 seconds, synthesized from the dominant frequency components of seismic waves collected from the previous real perturbation record. Three indicators were recorded: the actual delay of the perturbation signal on the propagation path, the energy attenuation ratio, and whether it triggered path deformation. The test was repeated with three rounds of independent perturbation input. If a node caused path oscillations, repeated data transmission failures, or overlapping feedback perturbations from adjacent nodes in all three rounds, it was identified as a structurally sensitive node. The final set of sensitive nodes includes all nodes with high coupling strength, high path aggregation degree and high propagation instability. Their location and propagation characteristics will directly serve as the decision basis for the next step—shadow link replacement and route trajectory reconstruction—and will be used to accurately repair the routing loop anomaly caused by the earthquake.

[0065] S3, construct a counterfactual replay chain based on the set of sensitive nodes, replace the identified signal distortion channel segments with shadow links, reconstruct a routing trajectory with stable convergence capability, and simultaneously restore the time series consistency between each monitoring node in the routing trajectory;

[0066] To address the issues of node crosstalk and routing loop instability caused by seismic disturbances, after identifying the set of sensitive nodes, it is necessary to reconstruct a routing trajectory with temporal consistency and stable convergence capability. This is implemented through the following steps:

[0067] Based on the identified set of sensitive nodes and the list of signal distortion channel segments, all distorted path segments are extracted from the original topology, and the communication direction, signal strength variation characteristics, and propagation delay anomaly curves of the preceding and following nodes are identified. The delineation of distorted path segments does not rely on simple transmission failure judgment, but rather uses the number of spectral jumps, the amplitude of phase reversal angle changes, and energy distribution discontinuities that occur during signal transmission along the path as objective evaluation criteria. Channels with a transmission anomaly rate consistently higher than 30%, propagation phase jumps exceeding 45 degrees, and path energy reduction rates greater than 70% are selected. Each distorted channel segment is individually marked in the original topology map, confirming its hop count position in the overall network communication path, distance between nodes, terrain occlusion information, and distance boundaries with neighboring nodes, laying the foundation for subsequent shadow link construction.

[0068] For path segments where distorted fragments have been removed, shadow links are designed to achieve equivalent replacement. The principle of constructing shadow links is to find a feasible connection path with a hop count controlled within 1.5 times that of the original path, and whose geographical location does not exceed 50 meters from the distorted path, without relying on distorted nodes. To ensure the new path has anti-interference capabilities in terms of signal quality, the signal attenuation of each hop is comprehensively judged based on multiple factors such as terrain slope, obstruction structure, and electromagnetic background noise level. In the specific implementation process, a scan is performed outward from the starting node of the original distorted fragment to find candidate relay node groups with a delay of no more than 1 second, an average signal-to-noise ratio of no less than 25 dB, and a spatial distance of no more than 30 meters. Then, hop combinations with stable connection records are selected from these. All candidate nodes must achieve a signal return integrity rate of no less than 95% in three rounds of trial transmission tests before entering the candidate shadow link pool. Based on this, the optimal shadow link path is selected according to the overall path time, node relay frequency, and spatial distribution balance, and the propagation parameters, spectral matching degree, and coupling strength index of each hop are recorded. The final shadow link is bound one-to-one with the original path in a hop-by-hop manner, replacing the corresponding communication interval in the original distorted path segment.

[0069] After deploying the physical structure of the shadow link, timing reconstruction needs to be performed on all nodes participating in the link communication to restore the time consistency of the entire path. This step uses the time drift baseline table as a reference to calculate the actual transmission delay of each node in the new path under the shadow link, and synchronously converts the timestamps in the original path to the new path, ensuring a linear and stable relationship between the start trigger time and the receiving processing time of all forwarding nodes. The local clock of each node is recalibrated by the reference beacon signal to achieve millisecond-level alignment. Single-hop round-trip transmission verification is performed on all shadow link nodes, recording the start time, arrival time, and acknowledgment feedback time of the received signal at each node. The error must not exceed 0.1 seconds in three consecutive round trips. If a node exhibits offset fluctuations during this calibration process, its relay priority must be lowered or it must be replaced structurally to prevent it from becoming a potential trigger point for subsequent path non-convergence. Through multiple rounds of timing adjustments, the time sequence consistency among all nodes in the new path is finally achieved, ensuring that the shadow link has coherent, continuous, and predictable communication behavior in the logical topology.

[0070] After structural replacement and timing adjustments are completed, path integration is performed to formally integrate the newly created shadow link into the main network path architecture. To prevent the original distorted path from being selected again during network self-recovery and causing loop recurrence, a signal forwarding suppression mechanism is applied to all replaced nodes. This mechanism is not implemented through physical link disconnection, but rather by introducing hop count suppression and node status masking during path broadcasting to block their participation in route reconstruction calculations. Simultaneously, during routing table updates, the shadow link path is set as the priority forwarding path, and all link requests sent to the original path are automatically redirected to the shadow link ingress node, ensuring that the new path becomes the preferred transmission channel in actual communication. Three rounds of complete data return tests are performed on the entire path. If the average packet latency remains stable below 1 second, the packet loss rate is below 5%, and the number of route reconstructions is zero within the observation period, the path is considered to have stable convergence capability and can operate long-term. Ultimately, the above process achieves a closed-loop processing flow from identification, replacement, reconstruction to confirmation. This not only effectively eliminates transmission links affected by earthquake interference, but also constructs a new communication path structure that is time-consistent, structurally stable, and highly resistant to interference, providing a solid foundation for subsequent time stack construction and topology control.

[0071] S4. Deploy dual mirror time stamps around the reconstructed routing trajectory to map the routing trajectory into a unified time stack structure, and inject a hysteresis gate with response delay characteristics into the time stack to suppress loop backflow and limit the oscillation amplitude during the topology reconstruction process.

[0072] To further suppress path loops and topology reconstruction oscillations caused by earthquake disturbances in the network, the following operations need to be performed based on the reconstructed shadow routing trajectories:

[0073] Around the established shadow routing trajectory, a pair of dual-mirror time-stamping devices are simultaneously deployed at both the starting and receiving nodes of each hop path, forming a strictly symmetrical time boundary. The time-stamping device consists of a high-precision crystal oscillator, a temperature-controlled clock drive circuit, and a phase calibration charge component, capable of maintaining millisecond-level frequency stability and time accuracy at different times. During deployment, using the starting point of the shadow link as the zero-time reference point, corresponding time stamps are configured for all hops sequentially along the communication direction from the starting node. The transmission and reception times at each hop are recorded separately and bidirectionally paired and verified with their mirror nodes, thereby achieving bidirectional correction of the time mapping. The time stamps begin with a unified pulse emitted by the reference beacon, and after path propagation delay compensation, are continuously aligned with all downstream nodes, ensuring the continuity, verifiability, and directionality of the time transmission process between any two adjacent hops, avoiding path reversal misjudgments or link loop errors caused by local node clock drift.

[0074] After completing the dual-mirror time-stamp deployment at all path nodes, time-stamped data from each node is collected to construct a complete time stack structure. Based on the shadow routing trajectory, the time stack structure uses the transmission and reception times of each node as push elements, stacking sequentially from the source node to the destination node according to the path order. During construction, the time difference between the push position of each node and the pop position of its predecessor is calculated and set as the propagation delay record value for that stack layer. To improve the time stack structure's response to micro-disturbances, a set of interference sensitivity coefficients is added to each stack layer to represent the signal stability, signal-to-noise ratio fluctuation amplitude, and coupling strength variation trend of that path segment under historical seismic disturbances. These additional information are bound to the time layers one-to-one through a stack layer index table, enabling the time stack's structural stability assessment function. All time data is uploaded to the central control node, which uniformly aggregates it into a complete "routing time series matrix." This matrix corresponds perfectly to the path structure spatially, exhibits a linear progression characteristic in time, and possesses accurate mapping, complete recording, and full traceability capabilities.

[0075] After identifying sensitive sections in the time stack that may cause path oscillations, a hysteresis gate with response delay adjustment function is injected into the time stack. The hysteresis gate is a physical timing control device composed of a delay crystal array, a signal holding unit, and a current-limiting feedback device, possessing microsecond-level response granularity and adaptive voltage control capabilities. During the injection process, path levels exhibiting "non-linear growth" in the time stack are preferentially selected for gate installation. Non-linear growth refers to a propagation delay increase exceeding twice the delay value of the previous layer between two consecutive stack layers, accompanied by a sudden drop in signal energy or a peak in phase disturbance. After the hysteresis gate is injected, the signal forwarding behavior of nodes is time-limited, requiring them to wait for the time-stamped data fed back by their predecessor nodes to undergo accuracy judgment, stability detection, and transmission legality confirmation before triggering the next level of data transmission. This delay mechanism essentially forms a loop suppression buffer. When loop feedback occurs from an upstream node, the hysteresis gate can create a short-term "freeze" state in the propagation path, effectively blocking the return path of erroneous data and preventing continuous network topology oscillations. All gate activation and release processes can be dynamically determined by time stamp information, without the need for additional manual intervention, thus achieving automated closed-loop control.

[0076] To verify the effectiveness of the deployed dual-mirror timescale and hysteresis gate in suppressing oscillations, multiple rounds of transmission experiments and path disturbance response tests were conducted on the shadow routing trajectory. Test data was randomly injected into the source nodes of the path using a vibration simulator. Data packets were delivered bidirectionally, propagating forward to the destination and then back to the source node to verify the synchronization of the timescale and the controllability of the gate delay response. During the experiments, the stack entry time, stack exit time, hysteresis gate delay time, data forwarding success rate, and retransmission count were recorded for each hop node, and compared with a control path without a hysteresis gate. If, in three consecutive rounds of testing, no reverse path was mistakenly established at any node in the path, the number of communication cycle oscillations was less than one, the average propagation delay remained stable within ±0.5 seconds, and the data integrity transmission rate was not less than 98%, then the path was deemed to have achieved the topology stability control objective. Ultimately, this structure binds time and path behavior together, creating a dynamically adjustable, controllable response lag, and breakable path loop anti-loop structure. This provides a highly controllable time framework for the next stage of topological energy constraint modeling and delay-shifting forwarding mechanism.

[0077] S5 generates time-varying virtual impedance routes based on the time stack, constructs an energy landscape structure with topological barriers, and outputs a node forwarding sequence with segmented peak-shifting characteristics, thereby driving the wireless ad hoc network to enter a stable convergence state segment by segment.

[0078] After completing the time stack construction, hysteresis gate deployment, and path oscillation control, in order to achieve a stable transition of the entire network communication, a dynamic forwarding mechanism with timing adjustment and topology guidance capabilities needs to be constructed. This is accomplished through the following steps:

[0079] Continuous communication records of each hop node in the time stack are extracted, and the transmission and reception time intervals of each node in different time periods are statistically analyzed to calculate its average propagation delay within the current communication cycle. The time delay value of each node is used as a quantitative index of its temporal impedance in the current path segment, forming a node-time impedance lookup table. To improve the temporal controllability of path behavior, a sliding segment analysis is performed on the impedance data, with each 5-second time window capturing the impedance change curves of all nodes within the window to construct a multi-cycle time-varying virtual impedance trajectory. The gradient value of the trajectory on the time axis reflects the state change of the path communication load over time. If the impedance change amplitude of a node exceeds a set stability threshold (e.g., the growth rate of the preceding and following cycles is greater than 25%), it is marked as a fluctuation point and serves as an important reference node for subsequent adjustment and control. The above steps enable the extraction of the dynamic change trend of node delays based on the original time stack, and use this as the starting point for constructing a stable path.

[0080] Based on the extracted time-varying virtual impedance trajectory, an energy landscape structure with spatial continuity and temporal fluctuation perception capabilities is constructed for the entire path segment. The construction method involves mapping the impedance value of each node to a three-dimensional height using time as the horizontal axis and the spatial location of the nodes as the vertical axis, forming an impedance topographic map of the path segment. To enhance the physical interpretation capability of this topographic map, historical energy distribution parameters of the nodes are introduced as vertical correction factors. This involves superimposing the signal energy density changes of a unit node within the past 20 seconds onto the impedance height using an equal-amplitude correction method, generating a dynamic topological barrier map. In this map, nodes where impedance spikes and energy drops overlap are considered barrier nodes, and their communication timing and energy conduction direction require delayed intervention. Simultaneously, energy depressions—node regions with stable impedance and saturated signal strength—are identified as activation sources for priority forwarding paths. Through this map, impedance highlands, energy channels, and boundary shift locations in the spatial-temporal dimensions can be obtained, providing accurate references for subsequent path peak shifting.

[0081] The "low impedance region" is defined by the time impedance value calculated from the average propagation delay of each node in the time stack. The lower the time impedance value of a node, the smaller its propagation delay in the current communication cycle, the higher the signal transmission smoothness, and the more stable its historical energy density and weaker coupling disturbances, making it a preferred path segment for forwarding. Therefore, an impedance topography map is formed by mapping the time impedance values ​​of nodes to their spatial locations. On this map, nodes with impedance values ​​within a preset low range are considered low impedance nodes.

[0082] The specific calibration method is as follows: Statistically analyze the time impedance distribution of all nodes along the entire path, calculate its mean μ and standard deviation σ, and express μ as the time impedance distribution. k·σ (where k is an empirical coefficient ranging from 0.5 to 1.0) is used as the low impedance threshold. When the temporal impedance of a node is lower than this threshold, it is identified as a low impedance node. Further aggregation of spatially adjacent low impedance nodes forms a low impedance region. This region represents a path segment in the topology that possesses high forwarding stability and low propagation delay, and is the data transmission segment that is prioritized for activation in subsequent peak-shifting scheduling plans.

[0083] Based on the topological barrier map, the entire path is divided into multiple continuous segments with significant differences in temporal behavior, constructing a segmented, staggered forwarding scheduling structure. The specific division criteria are as follows: if the temporal impedance difference between three consecutive hop nodes does not exceed 10%, and the energy density remains within a set range (e.g., -65dBm to -55dBm), it is classified as a stable sub-segment; if the impedance of any node suddenly increases or the energy drops sharply beyond a threshold, it becomes a segment boundary. Within each stable sub-segment, nodes are sorted according to their impedance values, and forwarding priorities are assigned. The smaller the impedance value, the closer it is to the segment's start time, and data forwarding is initiated first. The node forwarding trigger interval is set to 1.2 times the maximum propagation delay of the segment to eliminate data stacking effects and avoid loop path contention. The forwarding scheduling tables of all sub-segments are integrated into a path-level forwarding sequence plan. Different segments are activated within each time window, ensuring spatial node parallelism, temporal hop point staggering, and structural network non-interlacing, forming a staggered, segmented, and predictable forwarding temporal scheduling network.

[0084] After the node segmented forwarding plan is completed, to achieve a segment-by-segment convergence mechanism, a convergence verification window is set for each sub-segment to observe whether the forwarding is successfully completed within the predetermined time window. The convergence window starts at the time the first node initiates the forwarding and ends at the time the last node receives the data and sends back confirmation. If any node in the path fails to complete the data relay or fails to send back confirmation within the window, it sends a synchronization correction signal to the preceding node, instructing it to reduce the forwarding frequency or extend the waiting period, and recalibrate the local timestamp and time stack reference. Segments that successfully converge are marked as stable path segments and no longer participate in scheduling adjustments; segments that fail to converge for more than two rounds are marked as jittery path segments and undergo secondary path replacement candidate evaluation. The entire process continues until all path segments are marked as stable, completing the global coverage of the distributed forwarding plan. On this basis, all routing nodes in the network will enter a collaborative convergence state according to the segment-based initiation, staggered forwarding, and segment-by-segment verification method, completely eliminating the problems of frequent loop reconstruction, path oscillation, and data loss under topology disturbances in the original ad hoc network.

[0085] S6, after the network enters a stable convergence state, performs a time-reversal phase traction operation, drives the programmable metasurface antenna array by injecting inverse phase micropulses, and absorbs residual crosstalk energy in combination with the shadow energy storage structure, completes the loop-breaking control of the coherent topology, and forms a sustainable closed-loop dynamic control mechanism.

[0086] Even after completing node forwarding peak control and achieving segment-by-segment network convergence, there may still be hidden closed-loop paths formed by remnants of early interference. To completely eliminate this type of structure, the following steps are taken:

[0087] Based on the stable path sequence, phase residual records, round-trip delay variation trajectories, and abnormal communication feedback information from historical transmission data between nodes are retrieved to identify path segments that may exhibit signal loopback trends. In this stage, the focus is on analyzing locations within path nodes exhibiting asymmetric phase reversal (deviating from the uplink signal by 180 degrees) and average delay shrinkage (more than 20% lower than the previous cycle's delay value), identifying potential loop closure points. Combining the time stack data from the previous stage, time window analysis is performed on these regions to extract the time periods when reverse energy propagation occurs. Subsequently, multi-point time-series cross-sampling is performed on these nodes to capture phase transition boundaries and power fluctuation peaks in their received signals, comparing them with the communication time sequences of adjacent nodes to confirm the existence of unauthorized reverse paths. If the detected anti-phase echo signal exhibits periodic bounce phenomena within three consecutive time windows, the node is added to the inversion intervention target list and considered a candidate injection node for subsequent phase traction.

[0088] Starting from the identified inversion intervention node, reverse-phase micropulses are injected into its communication path as driving signals for time-reversal traction. Each injected pulse maintains the same frequency as the forward propagation data in terms of signal parameters, with a waveform amplitude no less than 90% of the forward signal, a phase set to be the reverse of the standard uplink signal (i.e., 180-degree phase misalignment), and a pulse width limited to no more than 200 nanoseconds to ensure a short signal with instantaneous energy release characteristics. The injection of all micropulses strictly follows the path start and end flags set in the time stack, executing at the end of the communication cycle to avoid interference with the main path signal. After the pulse is emitted by the target node, it propagates in reverse along the path, triggering phase response recording in the nodes along the way. If a node in the path detects a reverse phase reconstruction phenomenon (i.e., the detected waveform is phase-synchronized with the reverse-phase pulse), and this phenomenon persists for two communication cycles, it is determined that there is an unresolved loop channel in the path. This process can accurately identify closed-loop segments that are surface-stable but whose structure has not yet been broken, avoiding potential topological risks caused by path micro-coupling.

[0089] To detect the closed-loop path, a programmable metasurface antenna array with active reverse energy manipulation capability is deployed. This array consists of multiple phased-array reflectors, each with independent phase adjustment capabilities, continuously controlling the direction and phase of the reflected wave within a 0-360 degree range. The inversion intervention node is set as the center point, and at least six reflector points are deployed around it with a radius of 10 meters, forming a closed-loop interferometric control structure. Each reflector adjusts its reflection angle according to the time, phase, and direction of the received inverse-phase signal, ensuring its output waveform constitutes a region of maximum interference field strength, suppressing the loop propagation trend of the signal along the path. Simultaneously, a shadow energy storage structure is deployed in the core region of the antenna array. This structure consists of an energy-absorbing shell made of low-temperature ceramic material, a carbon nanotube charge trap layer, and a multi-coil coupling buffer. It is specifically designed to absorb high-frequency crosstalk pulses with frequencies between 8kHz and 20kHz, phase misalignment exceeding 90 degrees, and duration less than 10 milliseconds, converting them into non-propagating heat dissipation. By combining antenna interference direction and shadow energy storage, the signal that originally propagated along the loop path is effectively dissipated or phase-cancelled in physical space, thereby blocking the possible loop closure path.

[0090] Combining the inversion results with energy absorption efficiency assessment, the closed-loop structure of the entire network topology is confirmed and dynamically updated. After the inversion traction operation is completed, it is observed whether there is still anti-phase response feedback in the path during three consecutive communication cycles; if not, the path segment is marked as "coordination completed"; if there is still residual response, pulses are repeatedly injected and antenna reflection parameters are adjusted point by point until the echo is completely eliminated. Subsequently, based on the successful loop breaking status of each node, the forwarding priority is adjusted, the loop breaking point is moved forward to the preferred path of the main route relay, and the original connection directions with loop risk are blocked. Through this mechanism, the entire network finally forms a stable topology structure with forward propagation as the only path, no secondary bounce, and controllable energy closed loop.

[0091] This invention constructs a time-frequency observation layer triggered by earthquake events to collect electromagnetic interference characteristics in real time and extract crosstalk energy spectra and time drift baselines, achieving accurate modeling of physical interference sources. Subsequently, using causal coherence decomposition and counterfactual playback chain techniques, it actively identifies and repairs distorted node links in the communication path, ensuring stable convergence of the routing trajectory. Furthermore, by deploying dual-mirror timescales and hysteresis gates to construct a unified time stack structure, it suppresses loop backflow and signal oscillation in topology reconstruction. Based on this, it generates time-varying virtual impedance routes with segmented peak-shifting characteristics, guiding the network to stable operation segment by segment. Finally, using a programmable metasurface antenna array driven by inverse-phase micropulses and a shadow energy storage structure, it achieves active identification and physical loop-breaking control of residual crosstalk paths, constructing a coherent topology with long-term evolution adaptability and closed-loop control capabilities. This method comprehensively improves the anti-interference, adaptability, and topological stability of wireless ad hoc networks in high-altitude geological disaster chain areas, providing a solid technical guarantee for achieving high-frequency, high-precision disaster monitoring and early warning.

[0092] The foregoing has only described certain exemplary embodiments of the present invention by way of illustration. Undoubtedly, those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the foregoing drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

Claims

1. A high-position geological disaster chain monitoring node deployment method based on a wireless ad hoc network, characterized in that, Comprise the following steps: S1, in the high geological disaster chain area constructs the time-frequency observation layer triggered by earthquake, lays out the double-way coupling probe and introduces the phase calibration beacon, collects the dynamic electromagnetic interference field information, extracts the crosstalk energy spectrum and time drift baseline; S2, based on the crosstalk energy spectrum and time drift baseline, execute causal coherence decomposition, identify cross-channel coupling kernel and analyze energy propagation direction, mark the sensitive node set that triggers routing anomaly; Step S2 includes: According to the crosstalk energy spectrum and time drift baseline, interference time chain is constructed and multi-node influence path atlas is generated; On the basis of path atlas, propagation level is divided, frequency domain feature is extracted and node pair with stable phase delay and high coherent amplitude is identified, cross-channel coupling kernel database is constructed; Based on the coupling kernel database, the propagation path network is constructed and the energy propagation atlas is generated, and the energy vector field is formed combined with the three-dimensional geographic coordinates; In the energy vector field, identify the path aggregation point and the disturbance mutation point, use the disturbance simulation playback test method to verify the path shock response of the node, and finally determine the sensitive node set; S3, based on the sensitive node set, construct the counterfactual playback chain, replace the signal distortion segment with shadow link, reconstruct the convergent routing track, and restore the time sequence consistency between nodes; S4, deploy double-mirror time markers around the routing track, construct a unified time stack, and inject a hysteresis gate in it to suppress oscillation caused by loop backflow and topology reconstruction; Step S4 includes: Deploy double-mirror time marker devices at both ends of the starting node and the receiving node of the reconstructed routing track, complete the time synchronization and direction verification between path hop points; Collect time marker data of all path nodes, construct time stack structure and mark propagation delay and interference sensitivity coefficient, generate routing time sequence matrix; Identify the path segment with nonlinear growth characteristics in the time stack, and inject a response delay adjustable hysteresis gate to form a forwarding buffer and path freezing mechanism; Perform multiple rounds of path transmission tests to verify the time marker synchronization, gate delay control, and path topology oscillation suppression effect; S5, generate time-varying virtual impedance routing based on the time stack, construct topology barrier energy landscape, output node forwarding sequence with peak-shifting characteristics, and guide the network into a stable convergence state; Step S5 includes: Extract the average propagation delay of each hop path node in the time stack, generate a node time impedance reference table, and construct a multi-cycle time-varying virtual impedance track; Superimpose each node impedance track and historical energy distribution to form a topology barrier atlas with spatial continuity and time fluctuation perception ability, and mark the barrier nodes and low impedance areas; Divide the path section according to the impedance difference, develop a segmented peak-shifting forwarding scheduling plan, trigger node forwarding in order of impedance priority, and generate a path-level forwarding sequence plan; Set a sub-section convergence verification window to evaluate whether data transmission is completed according to the schedule, and adjust the forwarding frequency and timestamp according to the feedback result; S6, after the network enters a stable convergence state, execute time reversal phase traction, drive programmable metasurface antenna array by injecting inverse phase micro-pulse, and combine shadow energy storage structure to absorb residual crosstalk energy; Step S6 includes: Identify the nodes in the communication path that exhibit asymmetric phase inversion and delay contraction phenomena, extract the reverse propagation time period, and establish a list of inversion intervention targets; Inject reverse-phase micro-pulse signals into the intervention target nodes, and propagate them in reverse order in the time stack at the tail of the path to detect whether there is a persistent phase reconstruction response in the path; Deploy programmable metasurface antenna arrays around the detection nodes, and use the phased reflection units and shadow energy storage structures to block the loopback path in the physical space; Adjust the forwarding priority and shield the risk direction based on the traction results to ensure that the global network topology has only one path for forward propagation, forming a dynamic regulation structure for closed-loop breakage. 2.The method of claim 1, wherein, Step S1 includes: Select a typical site with landslide, collapse or debris flow induced risk in the high geological disaster chain area, and determine the layout boundary based on geological exploration results and terrain modeling data; Place double-coupling probes at equal intervals in the layout area, each coupling probe collects disturbance electric signals from the ground and the surface, and connects to a high-sensitivity sampling terminal through independent wires; Install a set of phase calibration beacons around each probe, which actively emit reference pulses with constant amplitude and frequency and consistent phase after an earthquake, and inject them into adjacent probes to form a phase reference; After the occurrence of seismic disturbance, collect the original disturbance waveforms of each channel, extract the amplitude variation, phase shift and main peak energy density, and generate the crosstalk energy spectrum and time drift baseline. 3.The method of claim 1, wherein, Step S3 includes: Identify the transmission abnormal path according to the sensitive node set and the list of distorted channel segments, and build a corresponding shadow link to replace the original path segment; Determine the shadow link path by jump number control, spatial boundary restriction, signal quality evaluation and backhaul integrity rate screening; Perform node timing reconstruction with the time drift baseline as a reference, and align the time and correct the errors of all nodes in the shadow link; Integrate the shadow link into the main path architecture through path integration operation, and apply signal forwarding suppression mechanism and routing table redirection control.

4. The method of claim 3, wherein the method further comprises: The selection of the shadow link path must meet the following conditions: the number of hops does not exceed one and a half times the number of original path hops, the path space range is limited within fifty meters of the original path, the signal-to-noise ratio of all relay nodes is higher than twenty-five decibels, and the signal backhaul integrity rate is not less than 95%.

5. The method of claim 1, wherein the method further comprises: The injection position of the hysteresis gate is limited to the position where the propagation time delay increases by more than twice the previous level, accompanied by a sudden drop in signal energy or a phase disturbance peak, to ensure that the path oscillation source is accurately constrained.

6. The method of claim 1, wherein the method further comprises: In the segmented staggered forwarding scheduling plan, the node forwarding trigger time interval of each sub-section is set to a preset multiple of the maximum propagation time delay in that section to avoid node forwarding overlap, and when any sub-section does not meet the convergence verification condition for two consecutive rounds, its path is marked as a jitter path segment, and a backup path replacement mechanism is started to maintain the continuous and stable convergence of the overall network.

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