A pressure-sensitive cable intrusion detection system

Abstract

The present invention discloses a pressure-sensitive cable intrusion detection system, which relates to the field of intrusion detection technology. The system includes a pressure-sensitive cable network, a signal acquisition and processing module, a positioning algorithm module, a moving path tracking module, and an alarm and display module. The present invention uses the positioning algorithm module to comprehensively consider multiple parameters such as signal strength, propagation time, and cable geometric layout, and accurately calculates the intrusion location through weighted fusion, dynamic calibration, and distributed computing, so as to facilitate security personnel to respond quickly. The moving path tracking module is used to analyze the historical moving path of the intruder, learn its behavior pattern, and thus predict its future direction of action and possible target location, providing valuable early warning information for security personnel, helping to deploy preventive measures in advance, so that the system can accurately point out the intrusion location and even track the moving path of the intruder, greatly improving the effectiveness of security protection.

Description

Technical Field

[0001] The present invention relates to the technical field of intrusion detection, in particular to a pressure-sensitive cable intrusion detection system. Background Art

[0002] With the continuous development of security technology, perimeter security systems have higher and higher requirements for the accuracy and reliability of intrusion detection. Traditional security means such as infrared detectors, microwave detectors, etc. are prone to false alarms or missed alarms in complex environments or under specific conditions. Therefore, it is particularly important to develop a security system that can detect intrusions more accurately and reliably. The pressure-sensitive cable intrusion detection system came into being in this context. It uses the special properties of pressure-sensitive cables to achieve accurate detection of intrusions. The pressure-sensitive cable intrusion detection system can detect intrusions more accurately, reduce false alarms and missed alarms, and improve the overall performance of the security system. The system can adapt to various complex terrains and environmental conditions, such as humidity, dust, electromagnetic interference, etc., to ensure the stability and reliability of the security system. Pressure-sensitive cables can be laid secretly underground or in walls, which are not easily detected by intruders, increasing the concealment and deterrence of the security system. By combining environmental detection devices and intelligent algorithms, the pressure-sensitive cable intrusion detection system can eliminate interference signals caused by environmental factors and reduce the occurrence of false alarms.

[0003] However, the current traditional intrusion detection system still has certain defects in accuracy, positioning accuracy and tracking ability. The traditional pressure-sensitive cable intrusion detection system can often only detect the occurrence of intrusion events or roughly determine the area where the intrusion occurs, but cannot accurately point out the intrusion location and track the intruder's movement path. This makes it difficult for security personnel to predict the intruder's next move and take effective preventive measures. This has brought great inconvenience to security response and subsequent processing in many practical application scenarios. Therefore, it is necessary to propose a pressure-sensitive cable intrusion detection system to solve the problems in the existing technology. Summary of the invention

[0004] The purpose of the present invention is to make up for the deficiencies of the prior art and to provide a pressure-sensitive cable intrusion detection system, which can not only detect the occurrence of intrusion events, but also accurately point out the intrusion location and even track the movement path of the intruder, greatly improving the effectiveness of security protection.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: a pressure-sensitive cable intrusion detection system, the system includes a pressure-sensitive cable network, a signal acquisition and processing module, a positioning algorithm module, a moving path tracking module and an alarm and display module, the pressure-sensitive cable network is composed of multiple sections of pressure-sensitive cables, covering the area that needs to be protected, the signal acquisition and processing module is responsible for real-time acquisition of the signal generated by the pressure-sensitive cable and processing, the positioning algorithm module accurately calculates the intrusion position according to the signal changes at different positions in the pressure-sensitive cable network, the moving path tracking module tracks the moving path of the intruder based on the continuous intrusion position information, and the alarm and display module sends an alarm signal when an intrusion event is detected, and displays the intrusion position and moving path;

[0006] The positioning algorithm module comprehensively considers multiple parameters to perform positioning calculations, and specifically includes a data preprocessing unit, a positioning calculation unit, a dynamic calibration unit and a distributed computing coordination unit. The data preprocessing unit receives the pressure-sensitive cable network signals transmitted by the signal acquisition and processing module, preprocesses these signals, and transmits the processed signals and feature information to the positioning calculation unit. The positioning calculation unit combines the signal propagation time and the geometric layout of the cable to perform multi-parameter fusion positioning. The distributed computing coordination unit assigns the positioning calculation task to multiple nodes, and each node uploads the result after performing local calculations. The dynamic calibration unit monitors environmental changes and cable performance changes in real time. When environmental factors change, the positioning parameters are adjusted according to the new signal propagation speed, and the signal propagation time is recalculated.

[0007] The specific calculation process of the positioning calculation unit in the positioning algorithm module to perform multi-parameter fusion positioning by combining the signal propagation time and the geometric layout of the cable is as follows:

[0008] Multi-parameter fusion positioning: Define the intrusion location coordinates as , the signal strength is , the signal propagation time is , the cable geometry layout function is , the signal strength weight is , the signal propagation time weight is , the cable geometry weight is ,but ,in , , They represent the location information based on signal strength, signal propagation time, and cable geometry respectively;

[0009] Positioning calculation: The coordinates of the three cable nodes are known to be , , , and the corresponding distances are , , , according to the geometric relationship, we get the equation system: , by solving the equations, we can get the intrusion location coordinates ;

[0010] Distributed computing: Defining The local positioning result of the nodes is , the weight is , a total of nodes, the comprehensive positioning result is ;

[0011] The mobile path tracking module includes a data acquisition and preprocessing unit, a trajectory analysis unit, a trajectory prediction unit and a multi-source information fusion unit. The data acquisition and preprocessing unit receives the intrusion position information output by the positioning algorithm module and preprocesses the information. After receiving the preprocessed data, the trajectory analysis unit starts to calculate the movement parameters of the intruder, and based on these parameters, identifies the action mode of the intruder. At the same time, it analyzes the movement path rules of the intruder in different time periods. The trajectory prediction unit uses a neural network to predict the trajectory according to the result of the trajectory analysis unit, and uses the trained model to predict the future action direction and possible target position of the intruder in real time according to the current state. The multi-source information fusion unit receives data from other sensors and fuses it with the position information of the pressure-sensitive cable to improve the accuracy and reliability of mobile path tracking.

[0012] Furthermore, the dynamic calibration unit monitors environmental changes and cable performance changes in real time. When environmental factors change, the specific calculation process of adjusting the positioning parameters is as follows:

[0013] Environmental Monitoring: Defining Signal Propagation Speed With temperature ,humidity , air pressure The relationship is The specific function form adopts the linear model ,in , , , is the coefficient to be determined;

[0014] Parameter adjustment: When environmental factors change, the adjusted signal propagation time is , the original propagation time is , the adjusted propagation speed is ,but ,in is the distance between the intrusion location and the cable node;

[0015] Regular calibration and verification: Define the actual position as The positioning result is , the positioning error is , by comparing the test with a standard signal source with a known position, the positioning parameters can be adjusted to reduce the error.

[0016] Furthermore, the specific process of the distributed computing coordination unit allocating the positioning computing task to multiple nodes is as follows:

[0017] Task allocation: Define the overall positioning calculation task as , a total of nodes, and assign tasks to each node so that the amount of tasks undertaken by each node is ;

[0018] Data Synchronization: Defining The data of the nodes is , the synchronized data is , ;

[0019] Monitor the computation process: define the The calculation progress of each node is The total progress is , , monitor the calculation progress of each node in real time.

[0020] Furthermore, the specific process of the trajectory analysis unit calculating the movement parameters of the intruder and identifying the action mode of the intruder is as follows:

[0021] Calculate the movement parameters: define two consecutive moments , The locations are and , the time interval is , then the moving speed , define the previous moment Location information , then the direction changes , residence time It is determined by the duration of the position change being less than a certain threshold, and the threshold is defined as ,but , the residence time starts to be accumulated until the position change is greater than the threshold;

[0022] Identify the action mode: Define the speed range of uniform linear motion as , the direction change range is ,when and When , it is judged to be uniform linear motion;

[0023] Analyze the path rules: The set of location points is , in an area The number of locations within is , the area is , the density of the location points in this area is .

[0024] Furthermore, the trajectory prediction unit uses a neural network to perform trajectory prediction according to the result of the trajectory analysis unit. The specific steps are as follows:

[0025] Use neural network for prediction, input is current position And the movement parameters , the output is the position at the future time ;

[0026] Define the training data set as , the goal is to find a function Make , the model parameters are continuously adjusted through the optimization algorithm to minimize the prediction error;

[0027] Define the current state as , then the predicted future position is .

[0028] Furthermore, the specific steps of the multi-source information fusion unit receiving data from other sensors and fusing the data with the position information of the pressure-sensitive cable include:

[0029] Receive multi-source data: define other sensor data as , and the position information of the pressure-sensitive cable to integrate;

[0030] Data fusion processing: weighted fusion method is used to define the weight of pressure-sensitive cable data as , the weights of other sensor data are ,and , the fused position is ;

[0031] Cross validation: Define the error between the fused position and the actual position as , the error is reduced by adjusting weights and fusion methods.

[0032] Furthermore, the signal acquisition and processing module is a bridge between the pressure-sensitive cable network and the positioning algorithm module. The pressure-sensitive cable network senses changes in external pressure and converts them into electrical signal outputs. The signal acquisition and processing module is responsible for receiving these original signals from the pressure-sensitive cables. After preliminary processing, the sorted signal data is accurately transmitted to the positioning algorithm module. The signal acquisition and processing module analyzes the collected signals and extracts characteristic information related to intrusion, including signal strength, frequency and duration.

[0033] Furthermore, the alarm and display module has various alarm modes, including sound and light alarm, SMS alarm and email alarm;

[0034] Sound and light alarm: When an intrusion event is detected, a strong sound and light signal is issued. The sound part uses a high-decibel alarm sound, and the light signal uses a high-brightness flash light. Different flashing frequencies and colors are used to distinguish different levels of intrusion events.

[0035] SMS alarm: The alarm and display module sends the alarm information to the mobile phones of relevant personnel in the form of SMS. The content of the SMS should include the time, location and severity of the intrusion event;

[0036] Email alarm: The alarm and display module sends alarm information to the specified email address. Email alarm provides more detailed information, including intrusion event screenshots, video clips and data analysis reports.

[0037] Compared with the existing technology, the pressure-sensitive cable intrusion detection system has the following beneficial effects:

[0038] The present invention uses a positioning algorithm module to comprehensively consider multiple parameters such as signal strength, propagation time and cable geometric layout, and accurately calculates the intrusion location through weighted fusion, dynamic calibration and distributed computing, which is convenient for security personnel to respond quickly. The mobile path tracking module is used to analyze the historical movement path of the intruder and learn its behavior pattern, so as to predict its future direction of action and possible target location, providing valuable early warning information for security personnel and helping to deploy preventive measures in advance, so that the system can accurately point out the intrusion location and even track the movement path of the intruder, greatly improving the effectiveness of security protection.

[0039] Other advantages, objectives and features of the present invention will be set forth in part in the following description and, in part, will be apparent to those skilled in the art based on an examination of the following or may be taught from the practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. Obviously, the drawings described below are only some embodiments of the present invention, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0041] Figure 1 The figure is a schematic diagram of the structure of a pressure-sensitive cable intrusion detection system. DETAILED DESCRIPTION

[0042] The technical solutions in the embodiments of the present invention are described clearly and completely below. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0043] Embodiment 1

[0044] In a modern smart factory, there are a large number of high-value equipment and important production areas that require strict security protection. The factory covers a large area, including multiple workshops, warehouses and outdoor areas. The surrounding environment is complex and there may be various interference factors. The specific implementation of using this system to provide security protection for the smart factory is as follows:

[0045] Pressure-sensitive cables are laid around factory perimeter walls, workshop entrances, around important equipment, and in warehouse areas. Pressure-sensitive cables of different specifications and sensitivities are selected according to the characteristics and security requirements of different areas. For example, high-sensitivity, long-distance pressure-sensitive cables are used on perimeter walls to ensure that any intrusion attempts to climb over the wall can be detected; short-distance, high-precision pressure-sensitive cables are used around important equipment to more accurately locate the intrusion.

[0046] A signal acquisition and processing module is installed in the factory's central monitoring room. This module is connected to the varistor cable network via a dedicated data line. It can collect the electrical signals generated by the varistor cables in real time, and amplify, filter and digitize them. The signal acquisition and processing module uses high-performance analog front-end chips and digital signal processors to ensure signal quality and stability.

[0047] The positioning algorithm module and mobile path tracking module are configured on the server in the central monitoring room. The positioning algorithm module adopts multi-parameter fusion positioning technology, comprehensively considering factors such as signal strength, signal propagation time and geometric layout of cables to accurately calculate the intrusion location. The mobile path tracking module tracks the intruder's movement path based on continuous intrusion location information through data analysis and pattern recognition algorithms.

[0048] An alarm and display module is set up in the central monitoring room, including an audible and visual alarm, a large-screen display and a mobile alarm terminal (such as a mobile phone, tablet computer, etc.). When an intrusion is detected, an audible and visual alarm is sounded, and the intrusion location and movement path are displayed on the large-screen display. At the same time, the alarm information is sent to the mobile alarm terminal of the relevant security personnel so that they can take timely response measures.

[0049] After the system is deployed, the system is calibrated and tested. First, the response of the pressure-sensitive cable and the performance of the signal acquisition and processing module are tested by applying simulated intrusion pressure at a known location. Then, the positioning algorithm module is calibrated using a standard signal source, and the parameters are adjusted to ensure positioning accuracy. Finally, the mobile path tracking module is tested to verify the accuracy of trajectory prediction and tracking by simulating the movement path of the intruder.

[0050] After the system enters normal operating state, the pressure-sensitive cable network continuously monitors the pressure changes in the surrounding environment. The signal acquisition and processing module collects and processes the signals generated by the pressure-sensitive cable in real time, and transmits the data to the positioning algorithm module and the mobile path tracking module.

[0051] When environmental factors change, the specific calculation process for adjusting positioning parameters is as follows: Define the signal propagation speed With temperature ,humidity , air pressure The relationship is The specific function form adopts the linear model ,in , , , is the coefficient to be determined. When the environmental factors change, the adjusted signal propagation time is , the original propagation time is , the adjusted propagation speed is ,but ,in is the distance between the intrusion location and the cable node, and the actual location is defined as The positioning result is , the positioning error is , by comparing the test with a standard signal source with a known position, the positioning parameters can be adjusted to reduce the error.

[0052] When an intrusion event occurs, the intrusion location coordinates are defined as , the signal strength is , the signal propagation time is , the cable geometry layout function is , the signal strength weight is , the signal propagation time weight is , the cable geometry weight is ,but ,in , , They represent the location information based on signal strength, signal propagation time, and cable geometry, respectively.

[0053] The coordinates of the three cable nodes are known to be , , , and the corresponding distances are , , , according to the geometric relationship, we get the equation system: , by solving the equations, we can get the intrusion location coordinates ; Definition The local positioning result of the nodes is , the weight is , a total of nodes, the comprehensive positioning result is .

[0054] The mobile path tracking module tracks the intruder's mobile path based on the continuous intrusion location information. , The locations are and , the time interval is , then the moving speed , define the previous moment Location information , then the direction changes , residence time It is determined by the duration of the position change being less than a certain threshold, and the threshold is defined as ,but , the dwell time starts to be accumulated until the position change is greater than the threshold.

[0055] The speed range of uniform linear motion is defined as , the direction change range is ,when and When , it is judged to be uniform linear motion; the set of position points is , in an area The number of locations within is , the area is , the density of the location points in this area is .

[0056] By analyzing the historical movement path of the intruder, using the neural network algorithm, inputting the current position and movement parameters, outputting the position prediction at the future moment, using the neural network for prediction, and inputting the current position And the movement parameters , the output is the position at the future time , define the training data set as , the goal is to find a function Make , the model parameters are continuously adjusted through the optimization algorithm to minimize the prediction error, and the current state is defined as , then the predicted future position is .

[0057] When an intrusion is detected, the alarm and display module will sound an audible and visual alarm and display the intrusion location and movement path on a large-screen display. At the same time, the alarm information will be sent to the security personnel's mobile alarm terminal so that they can take timely response measures.

[0058] In summary: The system can detect and respond to intrusion incidents in a timely manner through high-precision positioning and real-time mobile path tracking, effectively protecting the safety of factory equipment and property. It adopts advanced deep learning algorithms and multi-parameter fusion positioning technology, which can accurately distinguish between normal activities and intrusion behaviors, reduce false alarm rates, and reduce the workload of security personnel. It displays the intrusion location and movement path in real time, provides accurate information for security personnel, enables them to quickly take effective response measures, and improves emergency response efficiency. The system can automatically learn and adapt to environmental changes in the factory, realize intelligent management, and improve the reliability and stability of security protection. The system adopts a modular design and can be expanded and upgraded according to the actual needs of the factory to adapt to application scenarios of different scales and complexities.

[0059] Embodiment 2

[0060] Important scientific research institutions usually have advanced scientific research equipment, valuable experimental data and highly confidential research results, and have extremely high requirements for security protection. The building structure of scientific research institutions is complex, including laboratories, offices, storage areas and other functional areas. There may be certain interference factors in the surrounding environment. The specific implementation of using this system to provide security protection for important scientific research institutions is as follows:

[0061] Pressure-sensitive cables are laid around the perimeter walls, building entrances, important laboratories and data storage areas of scientific research institutions. Different types of pressure-sensitive cables are selected according to the security levels and protection requirements of different areas. For example, pressure-sensitive cables with high anti-interference capabilities are used at perimeter walls to prevent external interference from affecting the system; high-precision, miniaturized pressure-sensitive cables are used inside important laboratories to more accurately detect intrusions.

[0062] A signal acquisition and processing module is installed in the security monitoring center of the scientific research institution. The module is connected to the varistor cable network through a dedicated communication line. It can collect the electrical signals generated by the varistor cable in real time, and amplify, filter and digitize them. The signal acquisition and processing module uses high-performance sensors and signal processing chips to ensure the quality and stability of the signal.

[0063] The positioning algorithm module and mobile path tracking module are configured on the server of the security monitoring center. The positioning algorithm module adopts multi-parameter fusion positioning technology, comprehensively considering factors such as signal strength, signal propagation time, geometric layout of cables, and building structure to accurately calculate the intrusion location. The mobile path tracking module tracks the intruder's movement path based on continuous intrusion location information through data analysis and pattern recognition algorithms.

[0064] An alarm and display module is set up in the security monitoring center, including an audible and visual alarm, a large-screen display and a mobile alarm terminal (such as a mobile phone, tablet computer, etc.). When an intrusion event is detected, an audible and visual alarm is issued, and the intrusion location and movement path are displayed on the large-screen display. At the same time, the alarm information is sent to the mobile alarm terminal of the relevant security personnel so that they can take timely response measures.

[0065] After the system is deployed, the system is calibrated and tested. First, the response of the pressure-sensitive cable and the performance of the signal acquisition and processing module are tested by applying simulated intrusion pressure at a known location. Then, the positioning algorithm module is calibrated using a standard signal source, and the parameters are adjusted to ensure positioning accuracy. Considering that the building structure of the scientific research institution may have an impact on signal propagation, a building structure compensation test is performed to improve positioning accuracy. Finally, the mobile path tracking module is tested to verify the accuracy of trajectory prediction and tracking by simulating the movement path of the intruder.

[0066] After the system enters normal operating state, the pressure-sensitive cable network continuously monitors the pressure changes in the surrounding environment. The signal acquisition and processing module collects and processes the signals generated by the pressure-sensitive cable in real time, and transmits the data to the positioning algorithm module and the mobile path tracking module.

[0067] When environmental factors change, the specific calculation process for adjusting positioning parameters is as follows: Define the signal propagation speed With temperature ,humidity , air pressure The relationship is The specific function form adopts the linear model ,in , , , is the coefficient to be determined. When the environmental factors change, the adjusted signal propagation time is , the original propagation time is , the adjusted propagation speed is ,but ,in is the distance between the intrusion location and the cable node, and the actual location is defined as The positioning result is , the positioning error is , by comparing the test with a standard signal source with a known position, the positioning parameters can be adjusted to reduce the error.

[0068] When an intrusion event occurs, the intrusion location coordinates are defined as , the signal strength is , the signal propagation time is , the cable geometry layout function is , the signal strength weight is , the signal propagation time weight is , the cable geometry weight is ,but ,in , , They represent the location information based on signal strength, signal propagation time, and cable geometry, respectively.

[0069] The coordinates of the three cable nodes are known to be , , , and the corresponding distances are , , , according to the geometric relationship, we get the equation system: , by solving the equations, we can get the intrusion location coordinates ; Definition The local positioning result of the nodes is , the weight is , a total of nodes, the comprehensive positioning result is .

[0070] The mobile path tracking module tracks the intruder's mobile path based on the continuous intrusion location information. , The locations are and , the time interval is , then the moving speed , define the previous moment Location information , then the direction changes , residence time It is determined by the duration of the position change being less than a certain threshold, and the threshold is defined as ,but , the dwell time starts to be accumulated until the position change is greater than the threshold.

[0071] The speed range of uniform linear motion is defined as , the direction change range is ,when and When , it is judged to be uniform linear motion; the set of position points is , in an area The number of locations within is , the area is , the density of the location points in this area is .

[0072] By analyzing the historical movement path of the intruder, using the neural network algorithm, inputting the current position and movement parameters, outputting the position prediction at the future moment, using the neural network for prediction, and inputting the current position And the movement parameters , the output is the position at the future time , define the training data set as , the goal is to find a function Make , the model parameters are continuously adjusted through the optimization algorithm to minimize the prediction error, and the current state is defined as , then the predicted future position is .

[0073] When an intrusion is detected, the alarm and display module will sound an audible and visual alarm and display the intrusion location and movement path on a large-screen display. At the same time, the alarm information will be sent to the security personnel's mobile alarm terminal so that they can take timely response measures.

[0074] In summary: the system provides high-precision intrusion detection and positioning functions for important scientific research institutions, effectively protecting the safety of scientific research equipment, experimental data and research results. Taking into account factors such as building structure, it can accurately locate the intrusion location and track the intruder's movement path in the complex environment of scientific research institutions, and display the intrusion location and movement path in real time, so that security personnel can quickly take effective response measures and improve emergency response efficiency. The system can automatically learn and adapt to environmental changes in scientific research institutions, realize intelligent management, improve the reliability and stability of security protection, prevent unauthorized personnel from entering important areas, and protect the confidential information of scientific research institutions from being leaked.

[0075] It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above and that the invention can be implemented in other specific forms without departing from the spirit or essential features of the invention. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations falling within the meaning and scope of the same elements of the claims be included in the invention. Any reference numeral in a claim should not be considered as limiting the claim to which it relates.

Claims

1. A pressure-sensitive cable intrusion detection system, characterized in that: The system includes a pressure-sensitive cable network, a signal acquisition and processing module, a positioning algorithm module, a moving path tracking module and an alarm and display module. The pressure-sensitive cable network is composed of multiple sections of pressure-sensitive cables, covering areas that require safety protection. The signal acquisition and processing module is responsible for real-time acquisition of signals generated by the pressure-sensitive cables and processing them. The positioning algorithm module accurately calculates the intrusion position according to the signal changes at different positions in the pressure-sensitive cable network. The moving path tracking module tracks the moving path of the intruder based on continuous intrusion position information. The alarm and display module sends an alarm signal when an intrusion event is detected, and displays the intrusion position and moving path. The positioning algorithm module comprehensively considers multiple parameters for positioning calculation, specifically including a data preprocessing unit, a positioning calculation unit, a dynamic calibration unit and a distributed computing coordination unit. The positioning calculation unit combines the signal propagation time and the geometric layout of the cable to perform multi-parameter fusion positioning. The specific calculation process is as follows: Multi-parameter fusion positioning: Define the intrusion location coordinates as , the signal strength is , the signal propagation time is , the cable geometry layout function is , the signal strength weight is , the signal propagation time weight is , the cable geometry weight is ,but ,in , , They represent the location information based on signal strength, signal propagation time, and cable geometry respectively; Positioning calculation: The coordinates of the three cable nodes are known to be , , , and the corresponding distances are , , , according to the geometric relationship, we get the equation system: , by solving the equations, we can get the intrusion location coordinates ; Distributed computing: Defining The local positioning result of the nodes is , the weight is , a total of nodes, the comprehensive positioning result is ; The mobile path tracking module includes a data acquisition and preprocessing unit, a trajectory analysis unit, a trajectory prediction unit and a multi-source information fusion unit.

2. A pressure-sensitive cable intrusion detection system according to claim 1, characterized in that: The data preprocessing unit receives the pressure-sensitive cable network signals transmitted by the signal acquisition and processing module, preprocesses these signals, and transmits the processed signals and characteristic information to the positioning calculation unit. The positioning calculation unit combines the signal propagation time and the geometric layout of the cable to perform multi-parameter fusion positioning. The distributed computing coordination unit assigns the positioning calculation task to multiple nodes. Each node uploads the result after performing local calculation. The dynamic calibration unit monitors the environmental changes and cable performance changes in real time. When the environmental factors change, the positioning parameters are adjusted according to the new signal propagation speed, and the signal propagation time is recalculated. The dynamic calibration unit monitors the environmental changes and cable performance changes in real time. When the environmental factors change, the specific calculation process of adjusting the positioning parameters is as follows: Environmental Monitoring: Defining Signal Propagation Speed With temperature ,humidity , air pressure The relationship is The specific function form adopts the linear model ,in , , , is the coefficient to be determined; Parameter adjustment: When environmental factors change, the adjusted signal propagation time is , the original propagation time is , the adjusted propagation speed is ,but ,in is the distance between the intrusion location and the cable node; Periodic calibration and verification: Define the actual position as The positioning result is , the positioning error is , by comparing the test with a standard signal source with a known position, the positioning parameters can be adjusted to reduce the error.

3. A pressure-sensitive cable intrusion detection system according to claim 2, characterized in that: The specific process of the distributed computing coordination unit assigning the positioning computing task to multiple nodes is as follows: Task allocation: Define the overall positioning calculation task as , a total of nodes, and assign tasks to each node so that the amount of tasks undertaken by each node is ; Data synchronization: define the The data of the nodes is , the synchronized data is , ; Monitor the computation process: define the The calculation progress of each node is The total progress is , , monitor the calculation progress of each node in real time.

4. A pressure-sensitive cable intrusion detection system according to claim 1, characterized in that: The data acquisition and preprocessing unit receives the intrusion location information output from the positioning algorithm module and preprocesses the information. After receiving the preprocessed data, the trajectory analysis unit starts to calculate the movement parameters of the intruder, and identifies the action mode of the intruder based on these parameters. At the same time, the movement path rules of the intruder in different time periods are analyzed. The trajectory prediction unit uses a neural network to predict the trajectory according to the result of the trajectory analysis unit, and uses the trained model to predict the future movement direction and possible target position of the intruder in real time according to the current state. The multi-source information fusion unit receives data from other sensors and fuses it with the position information of the pressure-sensitive cable to improve the accuracy and reliability of mobile path tracking. The specific process of the trajectory analysis unit calculating the movement parameters of the intruder and identifying the action mode of the intruder is as follows: Calculate the movement parameters: define two consecutive moments , The locations are and , the time interval is , then the moving speed , define the previous moment Location information , then the direction changes , residence time It is determined by the duration of the position change being less than a certain threshold, and the threshold is defined as ,but , the residence time starts to be accumulated until the position change is greater than the threshold; Identify the action mode: Define the speed range of uniform linear motion as , the direction change range is ,when and When , it is judged to be uniform linear motion; Analyze the path rules: The set of location points is , in an area The number of locations within is , the area is , the density of the location points in this area is .

5. A pressure-sensitive cable intrusion detection system according to claim 4, characterized in that: The specific steps of the trajectory prediction unit using a neural network to perform trajectory prediction according to the result of the trajectory analysis unit are as follows: Use neural network for prediction, input is current position And the movement parameters , the output is the position at the future time ; Define the training data set as , the goal is to find a function Make , the model parameters are continuously adjusted through the optimization algorithm to minimize the prediction error; Define the current state as , then the predicted future position is .

6. A pressure-sensitive cable intrusion detection system according to claim 4, characterized in that: The specific steps of the multi-source information fusion unit receiving data from other sensors and fusing the data with the position information of the pressure-sensitive cable include: Receive multi-source data: define other sensor data as , and the position information of the pressure-sensitive cable to integrate; Data fusion processing: weighted fusion method is used to define the weight of pressure-sensitive cable data as , the weights of other sensor data are ,and , the position after fusion is ; Cross validation: Define the error between the fused position and the actual position as , the error is reduced by adjusting weights and fusion methods.

7. A pressure-sensitive cable intrusion detection system according to claim 1, characterized in that: The signal acquisition and processing module is a bridge between the pressure-sensitive cable network and the positioning algorithm module. The pressure-sensitive cable network senses changes in external pressure and converts them into electrical signal outputs. The signal acquisition and processing module is responsible for receiving these original signals from the pressure-sensitive cables. After preliminary processing, the sorted signal data is accurately transmitted to the positioning algorithm module. The signal acquisition and processing module analyzes the collected signals and extracts characteristic information related to intrusion, including signal strength, frequency and duration.

8. A pressure-sensitive cable intrusion detection system according to claim 1, characterized in that: The alarm and display module has various alarm modes, including sound and light alarm, SMS alarm and email alarm; Sound and light alarm: When an intrusion event is detected, a strong sound and light signal is issued. The sound part uses a high-decibel alarm sound, and the light signal uses a high-brightness flash light. Different flashing frequencies and colors are used to distinguish different levels of intrusion events. SMS alarm: The alarm and display module sends the alarm information to the mobile phones of relevant personnel in the form of SMS. The content of the SMS should include the time, location and severity of the intrusion event; Email alarm: The alarm and display module sends alarm information to the specified email address. Email alarm provides more detailed information, including intrusion event screenshots, video clips and data analysis reports.

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