Radio monitoring special vehicle and system

Abstract

The invention discloses a radio monitoring special vehicle and system, and belongs to the technical field of radio monitoring, and the radio monitoring special vehicle comprises a special vehicle platform, a radio monitoring system, a signal collection module, a data processing module, a direction finding positioning module, a spectrum analysis module, a signal identification module, a dynamic frequency database and a task management module. The data processing module carries out filtering processing and feature extraction on the received digital signals, potential abnormal signals are effectively recognized, the accuracy and timeliness of radio monitoring are improved, the support vector machine model is adopted for abnormal signal recognition, and the recognition accuracy is improved; the direction finding positioning module is combined with TDOA and DOA algorithms, high-precision positioning of a signal source is achieved, the geographic positioning accuracy of radio monitoring is improved, a positioning result and an abnormal signal recognition result are combined, the positioning precision is further optimized, and more reliable position information is provided for radio monitoring.

Description

Technical Field

[0001] The present invention belongs to the technical field of radio monitoring, and specifically refers to a special radio monitoring vehicle and system. Background Art

[0002] With the rapid development and wide application of wireless communication technology, the electromagnetic environment has become increasingly complex. Various legal and illegal radio signals coexist in limited spectrum resources, which puts forward higher requirements for fields such as spectrum management, interference detection, and illegal signal identification. Although traditional fixed radio monitoring stations can provide certain monitoring capabilities, they have obvious deficiencies in terms of coverage, flexibility, and response speed;

[0003] However, there are still certain defects in existing special radio monitoring vehicles and systems. Existing special radio monitoring vehicles and systems lack effective filtering and noise reduction mechanisms, resulting in low signal quality. They rely on fixed feature extraction methods set by humans and cannot dynamically adapt to different types of signals, reducing the ability to identify potential abnormal signals. For this reason, a special radio monitoring vehicle and system are proposed. Using traditional pattern recognition algorithms for abnormal signal detection results in low recognition rates and easy false alarms. Existing radio monitoring systems only use a single direction finding or positioning technology, resulting in low positioning accuracy. They only provide basic spectrograms or simple frequency domain analysis and cannot deeply explore the time-frequency characteristics of signals, making it difficult to identify complex non-stationary signals. They usually use fixed modulation methods and communication protocol databases and lack an adaptive update mechanism, making it difficult to cope with newly emerging signal types and protocols. For this reason, a special radio monitoring vehicle and system are proposed. Summary of the Invention

[0004] The purpose of the present invention is to provide a special radio monitoring vehicle and system to solve the problems raised in the above background art.

[0005] To achieve the above purpose, the present invention provides the following technical solution: A special radio monitoring vehicle and system, including a special vehicle platform, a radio monitoring system, a signal acquisition module, a data processing module, a direction finding and positioning module, a spectrum analysis module, a signal recognition module, a dynamic frequency database, and a task management module;

[0006] The special vehicle platform is used to perform radio monitoring tasks at different locations;

[0007] The signal acquisition module is used to acquire radio signals in the target area;

[0008] The data processing module is used to analyze the received digital signals, extract key features, and identify potential abnormal signals;

[0009] The direction finding and positioning module is used to calculate the azimuth and geographical coordinates of the signal source in real time;

[0010] The spectrum analysis module is used to deeply analyze the signal, extract its spectrum characteristics and generate a time-frequency spectrogram;

[0011] The signal recognition module is used to automatically identify the modulation type and communication protocol of the signal;

[0012] The dynamic frequency database is used to store spectrum occupancy templates, illegal signal feature library information, and update adaptively;

[0013] The task management module is used to provide a user-friendly interface to monitor the system status and arrange the task execution order.

[0014] Among them, the signal acquisition module collects radio signals in the target area; the signal acquisition module includes a wideband antenna array, a tunable RF front end, and an analog-to-digital converter. The wideband antenna array is correctly installed and connected to the radio monitoring system. According to the requirements of the monitoring task, the antenna mode and operating frequency range are selected, and the wideband antenna array starts to work, automatically scanning various radio signals in the target area. The antenna array can cover a wide frequency band from low frequency to high frequency, and the captured radio signals are wirelessly transmitted to the tunable RF front end.

[0015] Among them, for the signal acquisition module, the tunable RF front end performs preliminary processing on the signal, including but not limited to amplification, filtering, and frequency conversion. Inside the tunable RF front end, the RF parameters are adjusted according to the current operation requirements. The signal after preliminary processing is sent to the analog-to-digital converter, and the analog-to-digital converter converts the analog signal into a digital signal. The digital signal obtained after analog-to-digital conversion is transmitted to the data processing module.

[0016] Among them, the data processing module analyzes the received digital signal, extracts key features, and identifies potential abnormal signals; the obtained digital signal is filtered to remove noise and unwanted frequency components and perform noise reduction. Feature extraction is performed on the processed digital signal, and the implementation formula is:

[0017]

[0018] In the formula, X k represents the k-th frequency domain feature in the frequency domain, and N represents the total number of samples.

[0019] Among them, for the data processing module, the feature vector x = [x k is extracted from the frequency domain feature X 1 , x 2 ,..., x i , and each x i is from Xk The extracted eigenvalue is input into the support vector machine model to identify abnormal signals. The implementation formula is as follows:

[0020]

[0021] In the formula, f(x) represents the identified abnormal signal, and α i represents the Lagrange multiplier, y i represents the label of the training sample x i , K(x i , x) represents the kernel function, which calculates the similarity between two samples. b represents the bias term, and nsv represents the number of support vectors.

[0022] Among them, the direction finding and positioning module is used to calculate the azimuth angle and geographical coordinates of the signal source in real time; obtain the preliminarily processed digital signal and the identified abnormal signal, synchronize the timestamps of each receiving point through a high-precision clock. For each pair of receiving points, calculate the time difference between the signal arriving at these two points. Based on the TDOA values between multiple receiving points, establish a set of nonlinear equations to describe the position relationship of the signal source relative to each receiving point. According to the signal received by the array antenna through the DOC algorithm, estimate the direction angle of the signal arrival. Combine the distance difference information obtained by TDOA with the direction information provided by DOA to form a more accurate position estimate. If the geographical location of the receiving station is known, then according to the relative distance difference and direction angle, use triangulation or other geometric methods to calculate the exact geographical coordinates of the signal source, and combine the positioning result with the abnormal signal recognition result to optimize the positioning accuracy.

[0023] Among them, the spectrum analysis module is used to deeply analyze the signal, extract its spectral features and generate a time-frequency spectrogram; obtain the frequency domain feature X k , calculate the power spectral density according to X k and extract spectral features. Segment the signal into multiple shorter time periods through short-time Fourier transform, and apply the fast Fourier transform to each time period respectively. Generate a time-frequency spectrogram according to the results of STFT to show the frequency composition and intensity distribution of the signal at different time points. Identify any abnormal patterns according to the extracted spectral features.

[0024] Among them, the signal recognition module is used to automatically identify the modulation type and communication protocol of the signal. Obtain the processed signal feature data from the spectrum analysis module, compare the extracted signal feature data with the templates in the preset modulation mode database and classify them. When the modulation type is determined, further analyze the frame structure of the signal to identify the specific communication protocol, and compare the analysis result with the known communication protocol database to identify the specific protocol type.

[0025] Among them, the dynamic frequency database is used to store spectrum occupancy templates and illegal signal feature library information and update adaptively; obtain initial data, including legal spectrum usage and known illegal signal features, regularly scan the spectrum of a specified area through the signal acquisition module of the radio monitoring system to obtain the usage of the current frequency band, generate a spectrum occupancy template based on the scan results, when a suspected illegal signal is detected, extract its features through the signal recognition module, and classify and store them in the illegal signal feature library, add detailed annotations to each illegal signal feature, and immediately trigger the update process once a new spectrum usage pattern or illegal signal is discovered.

[0026] Among them, the task management module is used to provide a user-friendly interface to monitor the system status and arrange the task execution order; obtain and display the working status of the signal acquisition module, spectrum analysis module, and direction finding and positioning module in real time, set thresholds and rules, automatically trigger an alarm and highlight relevant information on the interface when an abnormal situation is detected, automatically sort based on the importance and urgency of the tasks, optimize the task execution order, dynamically adjust the task plan according to the real-time monitored data and changes in external conditions, and realize remote login and operation through the network interface, enabling operators to manage and monitor the radio monitoring system anywhere.

[0027] Compared with the prior art, the beneficial effects of the present invention are:

[0028] 1. The present invention filters and extracts features from the received digital signals through the data processing module, effectively identifies potential abnormal signals, improves the accuracy and timeliness of radio monitoring, and uses the support vector machine model for abnormal signal identification, improving the accuracy of identification;

[0029] 2. The present invention combines the TDOA and DOA algorithms through the direction finding and positioning module to achieve high-precision positioning of the signal source, improves the geographical positioning accuracy of radio monitoring, combines the positioning results with the abnormal signal identification results, and further optimizes the positioning accuracy, providing more reliable location information for radio monitoring;

[0030] 3. The present invention generates a time-frequency spectrogram through the spectrum analysis module through short-time Fourier transform and fast Fourier transform, deeply analyzes the spectrum characteristics of the signals, improves the ability to identify the frequency composition of the signals, and can identify any abnormal patterns based on the extracted spectrum characteristics, providing important spectrum information for radio monitoring;

[0031] 4. The present invention can automatically identify the modulation type and communication protocol of the signals through the signal recognition module by comparing the preset modulation mode database and communication protocol database, improving the intelligent level of radio monitoring. Description of the Drawings

[0032] Figure 1 This is a schematic structural diagram of a special vehicle and system for radio monitoring according to the present invention;

[0033] Figure 2 This is the operation process of a special vehicle and system for radio monitoring according to the present invention Figure 1 ;

[0034] Figure 3 This is the operation process of a special vehicle and system for radio monitoring according to the present invention Figure 2 ;

[0035] Figure 4 This is the operation process of a special vehicle and system for radio monitoring according to the present invention Figure 3 . Specific embodiments

[0036] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0037] Embodiment

[0038] Please refer to Figures 1 - 4 as shown, the present invention provides a technical solution: including a special vehicle platform, a radio monitoring system, a signal acquisition module, a data processing module, a direction finding and positioning module, a spectrum analysis module, a signal recognition module, a dynamic frequency database, and a task management module;

[0039] The special vehicle platform is used to perform radio monitoring tasks at different locations;

[0040] The signal acquisition module is used to collect radio signals in the target area;

[0041] The data processing module is used to analyze the received digital signals, extract key features, and identify potential abnormal signals;

[0042] The direction finding and positioning module is used to calculate the azimuth angle and geographical coordinates of the signal source in real time;

[0043] The spectrum analysis module is used to deeply analyze the signal, extract its spectrum features and generate a time-frequency map;

[0044] The signal recognition module is used to automatically identify the modulation type and communication protocol of the signal;

[0045] The dynamic frequency database is used to store spectrum occupancy templates, illegal signal feature library information, and update adaptively;

[0046] The task management module is used to provide a user-friendly interface to monitor the system status and arrange the task execution order.

[0047] Among them, the signal acquisition module acquires radio signals in the target area; the signal acquisition module includes a wide-band antenna array, a tunable RF front-end, and an analog-to-digital converter. The wide-band antenna array is correctly installed and connected to the radio monitoring system. According to the requirements of the monitoring task, the antenna mode and the operating frequency range are selected. The wide-band antenna array starts to work and automatically scans various radio signals in the target area. The antenna array can cover a wide frequency band from low frequency to high frequency, and the captured radio signals are wirelessly transmitted to the tunable RF front-end.

[0048] Among them, for the signal acquisition module, the tunable RF front-end performs preliminary processing on the signals, including but not limited to amplification, filtering, and frequency conversion. Inside the tunable RF front-end, the RF parameters are adjusted according to the current operation requirements. The signals after preliminary processing are sent to the analog-to-digital converter, and the analog-to-digital converter converts the analog signals into digital signals. The digital signals obtained after analog-to-digital conversion are transmitted to the data processing module.

[0049] Among them, the data processing module analyzes the received digital signals, extracts key features, and identifies potential abnormal signals; the obtained digital signals are subjected to filtering processing to remove noise and unnecessary frequency components and perform noise reduction. Feature extraction is performed on the processed digital signals, and the implementation formula is:

[0050]

[0051] In the formula, X k represents the k-th frequency domain feature in the frequency domain, and N represents the total number of samples.

[0052] Among them, for the data processing module, the feature vector x = [x k , x 1 ,..., x 2 ,..., x i is extracted from the frequency domain features X. Each x i is the eigenvalue extracted from X k . The feature vector is input into the support vector machine model to identify abnormal signals, and the implementation formula is:

[0053]

[0054] In the formula, f(x) represents the identified abnormal signal, α i represents the Lagrange multiplier, y i represents the label of the training sample x i , and K(x i, x) represents the kernel function that calculates the similarity between two samples, b represents the bias term, and nsv represents the number of support vectors.

[0055] Among them, the direction finding and positioning module is used to calculate the azimuth and geographical coordinates of the signal source in real time; obtain the preliminarily processed digital signals and the identified abnormal signals, synchronize the timestamps of each receiving point through a high-precision clock, for each pair of receiving points, calculate the time difference between the signal arriving at these two points, based on the TDOA values between multiple receiving points, establish a set of nonlinear equations to describe the position relationship of the signal source relative to each receiving point, estimate the direction angle of the signal arrival according to the signals received by the array antenna through the DOC algorithm, combine the distance difference information obtained by TDOA with the direction information provided by DOA to form a more accurate position estimate. If the geographical location of the receiving site is known, then according to the relative distance difference and direction angle, use triangulation or other geometric methods to calculate the exact geographical coordinates of the signal source, and combine the positioning result with the abnormal signal recognition result to optimize the positioning accuracy.

[0056] Among them, the spectrum analysis module is used to deeply analyze the signal, extract its spectral features and generate a time-frequency spectrogram; obtain the frequency domain feature X k , according to X k calculate the power spectral density and extract spectral features, segment the signal into multiple shorter time periods through short-time Fourier transform, and apply the fast Fourier transform to each time period respectively. Generate a time-frequency spectrogram according to the results of STFT to display the frequency composition and intensity distribution of the signal at different time points, and identify any abnormal patterns according to the extracted spectral features.

[0057] Among them, the signal recognition module is used to automatically identify the modulation type and communication protocol of the signal, obtain the processed signal feature data from the spectrum analysis module, compare the extracted signal feature data with the templates in the preset modulation mode database and classify them. When the modulation type is determined, further analyze the frame structure of the signal to identify the specific communication protocol, and compare the analysis result with the known communication protocol database to identify the specific protocol type.

[0058] Among them, the dynamic frequency database is used to store spectrum occupancy templates, illegal signal feature library information, and update adaptively; obtain initial data, including legal spectrum usage conditions and known illegal signal features, regularly scan the spectrum of a specified area through the signal acquisition module of the radio monitoring system to obtain the usage conditions of the current frequency band, generate a spectrum occupancy template according to the scanning results, when a suspected illegal signal is detected, extract its features through the signal recognition module and classify and store them in the illegal signal feature library, add detailed annotations to each illegal signal feature, and immediately trigger the update process once a new spectrum usage pattern or illegal signal is discovered.

[0059] Among them, the task management module is used to provide a user-friendly interface to monitor the system status and arrange the task execution order; obtain and display the working status of the signal acquisition module, spectrum analysis module, and direction finding and positioning module in real time, and set thresholds and rules. When an abnormal situation is detected, it automatically triggers an alarm and highlights relevant information on the interface, automatically sorts based on the importance and urgency of tasks, optimizes the task execution order, dynamically adjusts the task plan according to the real-time monitored data and changes in external conditions, and realizes remote login and operation through a network interface, enabling operators to manage and monitor the radio monitoring system anywhere.

[0060] Working principle: The signal acquisition module captures radio signals in the target area through a wideband antenna array. The antenna array can cover a wide range of frequency bands and can effectively capture signals from low frequency to high frequency. The captured signals are preliminarily processed by a tunable radio frequency front end. The signals after preliminary processing are sent to an analog-to-digital converter and converted into digital signals. The data processing module receives the digital signals from the signal acquisition module and performs filtering to remove noise and unwanted frequency components. The processed signals are subjected to feature extraction, and the feature vectors are input into a support vector machine model for abnormal signal recognition. Direction finding and positioning are used to locate the signal source based on the preliminarily processed digital signals and the recognized abnormal signals. By synchronizing the timestamps of each receiving point with a high-precision clock, the time difference between the signals arriving at different receiving points is calculated. Based on the TDOA value, a non-linear equation is established to describe the position relationship of the signal source. The direction angle of signal arrival is estimated through the DOC algorithm. The distance difference information obtained from TDOA is combined with the direction information provided by DOA to form an accurate position estimate. If the geographical location of the receiving station is known, the triangulation method is used to calculate the exact geographical coordinates of the signal source. The spectrum analysis module deeply analyzes the signals, extracts spectrum features and generates a time-frequency map. Abnormal patterns are identified by calculating the power spectral density and extracting spectrum features. The signal is segmented into multiple shorter time periods through short-time Fourier transform, and the fast Fourier transform (FFT) is applied to each time period. A time-frequency map is generated according to the results of STFT, showing the frequency composition and intensity distribution of the signal at different time points. The signal recognition module automatically identifies the modulation type and communication protocol of the signal, obtains the processed signal feature data from the spectrum analysis module, and compares and classifies it with the templates in the preset modulation mode database. After determining the modulation type, the frame structure of the signal is further analyzed to identify the specific communication protocol, and the analysis results are compared with the known communication protocol database to identify the specific protocol type. The dynamic frequency database stores spectrum occupancy templates and illegal signal feature library information and updates adaptively. The initial data includes legal spectrum usage and known illegal signal features. The current usage of the frequency band is obtained through regular spectrum scanning, and a spectrum occupancy template is generated according to the scanning results. When a suspected illegal signal is detected, its features are extracted and classified and stored in the illegal signal feature library. Once a new spectrum usage pattern or illegal signal is discovered, the update process is immediately triggered. The task management module real-time obtains and displays the working status of each module, sets thresholds and rules to trigger alarms and display relevant information, automatically sorts the task execution order based on the importance and urgency of the tasks, and dynamically adjusts the task plan according to the real-time monitored data and changes in external conditions. Remote login and operation are achieved through a network interface, enabling operators to manage and monitor the radio monitoring system from any location.

[0061] Although embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the present invention, and the scope of the present invention is defined by the appended claims and their equivalents.

[0062] The present invention and its embodiments have been described above. Such description is not restrictive. What is shown in the drawings is only one of the embodiments of the present invention, and the actual structure is not limited thereto. Generally speaking, if those of ordinary skill in the art are inspired by it and, without departing from the purpose of the present invention, creatively design structural modes and embodiments similar to the technical solution, they shall fall within the protection scope of the present invention.

Claims

1. A radio monitoring special vehicle and system, characterized in that: It includes special vehicle platform, radio monitoring system, signal acquisition module, data processing module, direction finding and positioning module, spectrum analysis module, signal recognition module, dynamic frequency database and task management module; The special vehicle platform is used to perform radio monitoring tasks at different locations; The signal acquisition module is used to collect radio signals in the target area; The data processing module is used to analyze the received digital signals, extract key features, and identify potential abnormal signals; The direction finding and positioning module is used to calculate the azimuth and geographic coordinates of the signal source in real time; The spectrum analysis module is used to perform in-depth analysis on the signal, extract its spectrum features and generate a time-frequency spectrum; The signal identification module is used to automatically identify the modulation type and communication protocol of the signal; The dynamic frequency database is used to store spectrum occupancy templates and illegal signal feature library information, and is updated adaptively; The task management module is used to provide a user-friendly interface to monitor system status and arrange the task execution sequence.

2. A radio monitoring special vehicle and system according to claim 1, characterized in that: The signal acquisition module collects radio signals in the target area; the signal acquisition module includes a wide-band antenna array, a tunable radio frequency front end and an analog-to-digital converter. The wide-band antenna array is correctly installed and connected to the radio monitoring system. The antenna mode and the operating frequency range are selected according to the requirements of the monitoring task. The wide-band antenna array starts working and automatically scans various radio signals in the target area. The antenna array can cover a wide frequency band from low frequency to high frequency, and the captured radio signals are transmitted to the tunable radio frequency front end via wireless.

3. A radio monitoring special vehicle and system according to claim 2, characterized in that: The signal acquisition module and the tunable RF front end perform preliminary processing on the signal, including but not limited to amplification, filtering and frequency conversion. In the tunable RF front end, the RF parameters are adjusted according to the current operation requirements. The signal after preliminary processing is sent to the analog-to-digital converter, and the analog-to-digital converter converts the analog signal into a digital signal. The digital signal obtained after the analog-to-digital conversion is transmitted to the data processing module.

4. A radio monitoring special vehicle and system according to claim 1, characterized in that: The data processing module analyzes the received digital signal, extracts key features, and identifies potential abnormal signals; obtains the digital signal for filtering, removes noise and unnecessary frequency components, and performs noise reduction, and extracts features from the processed digital signal, and the implementation formula is: In the formula, X k represents the kth frequency domain feature in the frequency domain, and N represents the total number of samples.

5. A radio monitoring special vehicle and system according to claim 4, characterized in that: The data processing module extracts X from the frequency domain features. k The extracted feature vector is x=[x1,x2,...,x i ], each x i From X k The extracted eigenvalues ​​are used to input the eigenvector into the support vector machine model to identify abnormal signals. The implementation formula is: In the formula, f(x) represents the identified abnormal signal, α i represents the Lagrange multiplier, y i Represents the training sample x i The label of K(x i ,x) represents the kernel function, which calculates the similarity between two samples, b represents the bias term, and nsv represents the number of support vectors.

6. A radio monitoring special vehicle and system according to claim 1, characterized in that: The direction finding and positioning module is used to calculate the azimuth and geographic coordinates of the signal source in real time; obtain the digital signal that has been preliminarily processed and the identified abnormal signal, synchronize the timestamps of each receiving point through a high-precision clock, and for each pair of receiving points, calculate the time difference between the arrival of the signal at these two points, and establish a set of nonlinear equations based on the TDOA values ​​between multiple receiving points to describe the positional relationship of the signal source relative to each receiving point. The DOC algorithm is used to estimate the direction angle of signal arrival based on the signal received by the array antenna, and the distance difference information obtained by TDOA is combined with the direction information provided by DOA to form a more accurate position estimate. If the geographical location of the receiving site is known, the exact geographic coordinates of the signal source are calculated based on the relative distance difference and the direction angle using triangulation or other geometric methods, and the positioning result is combined with the abnormal signal identification result to optimize the positioning accuracy.

7. A radio monitoring special vehicle and system according to claim 1, characterized in that: The spectrum analysis module is used to perform in-depth analysis on the signal, extract its spectrum features and generate a time-frequency spectrum; obtain the frequency domain feature X k , according to X k The power spectral density is calculated and the spectral features are extracted. The signal is divided into multiple shorter time periods through short-time Fourier transform, and fast Fourier transform is applied to each time period. A time-frequency spectrum is generated based on the results of STFT to show the frequency composition and intensity distribution of the signal at different time points. Any abnormal patterns can be identified based on the extracted spectral features.

8. A radio monitoring special vehicle and system according to claim 1, characterized in that: The signal identification module is used to automatically identify the modulation type and communication protocol of the signal, obtain the processed signal feature data from the spectrum analysis module, compare the extracted signal feature data with the template in the preset modulation method database and classify them, and when the modulation type is determined, further analyze the frame structure of the signal to identify the specific communication protocol, compare the analysis results with the known communication protocol database to identify the specific protocol type.

9. A radio monitoring special vehicle and system according to claim 1, characterized in that: The dynamic frequency database is used to store spectrum occupancy templates and illegal signal feature library information, and update them adaptively; obtain initial data, including legal spectrum usage and known illegal signal features, and regularly scan the spectrum of the designated area through the signal acquisition module of the radio monitoring system to obtain the usage of the current frequency band, and generate spectrum occupancy templates based on the scanning results. When a suspected illegal signal is detected, its features are extracted through the signal recognition module. They are classified and stored in the illegal signal feature library, and detailed annotations are added to each illegal signal feature. Once a new spectrum usage pattern or illegal signal is discovered, the update process is immediately triggered.

10. A radio monitoring special vehicle and system according to claim 1, characterized in that: The task management module is used to provide a user-friendly interface to monitor the system status and arrange the task execution order; acquire and display the working status of the signal acquisition module, spectrum analysis module, and direction finding and positioning module in real time, and set thresholds and rules. When an abnormal situation is detected, an alarm is automatically triggered and relevant information is highlighted on the interface. The tasks are automatically sorted based on their importance and urgency, and the task execution order is optimized. According to the real-time monitoring data and changes in external conditions, the task plan is dynamically adjusted, and remote login and operation are realized through the network interface, so that operators can manage and monitor the radio monitoring system at any location.

Images