Radio signal intelligent detection method and system suitable for multi-band system

Abstract

The invention relates to the technical field of intelligent detection, and particularly discloses a radio signal intelligent detection method and system suitable for a multi-band system, and the method comprises the following steps: S1, setting a detection buffer area, equally dividing and selecting time points, obtaining a radio signal and a communication quality index of terminal equipment in real time, and determining an optimal communication quality index; s2, generating a communication quality curve according to the communication quality index, extracting a plurality of characteristic indexes of the radio signal, and obtaining a characteristic curve of each index changing along with time; s3, comparing the communication quality curve with each signal characteristic curve, and establishing an adaptive rule model of signal characteristics and communication quality; predicting signal characteristics when the communication quality is optimal based on the model, and combining equipment information and performing real-time correction; according to the method, the signal detection performance of the terminal equipment in a multi-band system is optimized by dynamically analyzing the relationship between the signal characteristics and the communication quality.

Description

Technical Field

[0001] The present invention relates to the field of intelligent detection technology, and in particular to a method and system for intelligent detection of radio signals applicable to multi-band systems. Background Art

[0002] In today's communications technology, the detection and analysis of radio signals in the environment is a crucial task. Existing technologies typically rely on specialized equipment and advanced algorithms to meticulously process various radio signals. Specifically, by detecting the complex array of radio signals in the environment, key information is extracted from multiple dimensions, including signal strength, frequency band, and unique signal characteristics. Then, using specialized algorithms and specialized equipment, these signals are accurately classified, clearly displaying detailed information such as the signal's carrier, the type of mobile phone being used, and the exact distance.

[0003] However, in real-world applications, mobile phones do not remain in a fixed state while users are using them. To ensure real-time communication quality, mobile phones dynamically adjust radio signal characteristics, such as transmit power, based on surrounding environmental conditions. While this adaptive adjustment mechanism helps ensure smooth communication, it also causes the characteristics of wireless signals to constantly change. For example, when a user moves from an area with a weak signal to one with a stronger signal, the phone may reduce transmit power, complicating recognition based on stable signal characteristics. Due to the constant changes in signal characteristics, recognition results also fluctuate continuously, making accurate recognition and analysis difficult and impacting the stability and reliability of related technologies in practical applications. Summary of the Invention

[0004] The purpose of the present invention is to provide a method and system for intelligent detection of radio signals applicable to multi-band systems, and to solve the following technical problems.

[0005] The purpose of the present invention can be achieved through the following technical solutions: A multi-band radio signal intelligent detection method includes the following steps: Step S1: Setting a detection buffer interval, selecting a number of equally spaced time points within the detection buffer interval, acquiring radio signals of terminal devices within the detection buffer interval, and acquiring the communication quality index of the terminal devices at each time point in real time; and determining the optimal communication quality index of the terminal devices; Step S2: generating a communication quality curve of the terminal device according to the communication quality index obtained in real time; and extracting a plurality of signal characteristic indicators of the radio signal, obtaining the signal characteristics of the signal characteristic indicators at each time point, and obtaining a signal characteristic change curve of each signal characteristic indicator; Step S3: For any signal characteristic indicator, the communication quality curve is compared with the signal characteristic change curve of the signal characteristic indicator to obtain an adaptive rule model between the signal characteristic indicator and the communication quality index; According to the adaptive rule model, the signal characteristics of each signal characteristic indicator of the terminal device at the best communication quality index are predicted, and the device information of the terminal device is obtained, and the device information is corrected in real time.

[0006] As a further solution of the present invention: the process of setting the detection buffer interval includes: The time period length T is preset, and the time when the radio signal of the terminal device is detected is recorded as the starting time t0. According to the time period length and the starting time, the detection buffer interval [t0, t0+T] is obtained.

[0007] As a further solution of the present invention: the process of obtaining the communication quality index of the terminal device includes: Set the signal strength range to [-110, 0] dBm, where the signal strength range represents the power strength range of the base station signal received by the terminal device; obtain the power strength of the base station signal received by the terminal device, and obtain the signal-to-noise ratio of the base station signal, and then obtain the communication quality index of the terminal device. , where K1 and K2 are weight coefficients, and K1>0, K2>0, where RSSI represents the power strength of the base station signal received by the terminal device, and SNR represents the signal-to-noise ratio of the base station signal.

[0008] As a further solution of the present invention: the process of determining the best communication quality index includes: Set the maximum signal-to-noise ratio of the base station signal, the setting range of the maximum signal-to-noise ratio is [20, 40] dB, and obtain the best communication quality index , where SNR max Indicates the maximum signal-to-noise ratio.

[0009] As a further solution of the present invention: the process of extracting each signal characteristic indicator in the radio signal includes: The radio signal is amplified and filtered to suppress out-of-band interference, and the sampling rate of the radio signal is determined based on the Quistle theorem, and the analog signal is converted into a digital signal according to the sampling rate; the synchronization sequence of the radio signal is identified through a detection algorithm, the time position of the synchronization sequence is obtained, and the frame boundary and symbol period are determined; and the digital signal is fast Fourier transformed to obtain a frequency domain signal; based on the frequency domain signal, several signal characteristic indicators of the radio signal are obtained, and the signal characteristic indicators include modulation mode, bandwidth, spectrum characteristics and frame structure.

[0010] As a further solution of the present invention: the process of acquiring the signal characteristics includes: For any time point, obtain the value of the signal characteristic indicator at the time point. If the value of the signal characteristic indicator is a numerical value, directly record the numerical value as the signal characteristic of the signal characteristic indicator; if the value of the signal characteristic indicator is not, binary encode the numerical value to obtain a binary numerical value, and record the binary numerical value as the signal characteristic of the signal characteristic indicator.

[0011] As a further solution of the present invention: the process of comparing the communication quality curve with the signal characteristic change curve includes: Obtaining a monotonically increasing interval and a monotonically decreasing interval on the communication quality curve, both of which are recorded as signal change intervals, and obtaining a monotonically increasing interval and a monotonically decreasing interval on the signal characteristic change curve, both of which are recorded as characteristic change intervals; Get the horizontal coordinates of the starting point and end point of each signal change interval, and get the signal change endpoint set {(P1 start , P1 end ), (P2 start , P2 end ),...,(Pn start , Pn end )}, where Pn start Indicates the horizontal coordinate corresponding to the starting point of the nth signal change interval, Pn end The horizontal coordinate corresponding to the end point of the nth signal change interval, where n is the total number of signal change intervals; Get the horizontal coordinates corresponding to the starting point and end point of each feature change interval, and get the feature change endpoint set {(P1´ start , P1´ end ), (P2´ start , P2´ end ),...,(Pm´ start , Pm´ end )}, where Pm´ start Indicates the horizontal coordinate corresponding to the starting point of the mth feature change interval, Pm´ end Indicates the abscissa corresponding to the end point of the mth feature change interval, where m is the total number of feature change intervals; Set the delay threshold time, if the communication quality curve and the signal characteristic change curve meet , then the signal characteristic index corresponding to the signal characteristic change curve is marked as a non-fixed characteristic; otherwise, the signal characteristic index corresponding to the signal characteristic change curve is marked as a fixed characteristic; wherein, Pi start Indicates the horizontal coordinate corresponding to the starting point of the i-th signal change interval, Pi´ startRepresents the horizontal coordinate corresponding to the starting point of the i-th feature change interval, i∈[1,n] and i is a positive integer.

[0012] As a further solution of the present invention: the process of obtaining the adaptive rule model includes: Each signal change interval is intercepted, and the feature change interval of each non-fixed feature is intercepted. For any communication quality index in the signal change interval, the signal feature corresponding to the communication quality index is obtained in the feature change interval with the same number, and the communication quality index and its corresponding signal feature are recorded as a set of sample data, thereby obtaining several sets of sample data, which are recorded as sample data sets; an initial model is established based on a neural network, the sample data sets are input into the initial model, and the initial model is trained to obtain an adaptive rule model representing that the signal feature changes with the communication quality index.

[0013] A multi-band radio signal intelligent detection system comprising: Signal acquisition module: includes a detection center and terminal devices; sets a detection buffer zone of the detection center, selects several time points equally spaced within the detection buffer zone, acquires radio signals of terminal devices within the detection buffer zone, and obtains the communication quality index of the terminal devices at each time point in real time; and determines the optimal communication quality index of the terminal devices; Preprocessing module: sets a detection buffer interval, selects a number of time points equally spaced within the detection buffer interval, obtains radio signals of terminal devices within the detection buffer interval, and obtains the communication quality index of the terminal devices at each time point in real time; and determines the optimal communication quality index of the terminal devices; Feature matching module: for any signal feature indicator, compares the communication quality curve with the signal feature change curve of the signal feature indicator to obtain an adaptive rule model between the signal feature indicator and the communication quality index; According to the adaptive rule model, the signal characteristics of each signal characteristic indicator of the terminal device at the best communication quality index are predicted, and the device information of the terminal device is obtained, and the device information is corrected in real time.

[0014] Beneficial effects of the present invention: The present invention dynamically predicts signal characteristics under optimal communication conditions by analyzing the relationship between signal characteristics and communication quality in real time, significantly improving the signal detection performance and stability of terminal devices in multi-band environments. It also establishes an adaptive rule model for signal characteristics and communication quality, which can automatically correct device information and adapt to dynamic changes in signal characteristics (such as transmission power adjustment), solving the problem of inaccurate recognition caused by signal fluctuations in traditional methods. The present invention also combines neural networks and decision tree models to extract key indicators such as device distance, operator, and type from signal characteristics at optimal communication quality, thereby improving the accuracy and reliability of device identification. It extracts characteristics such as modulation mode and bandwidth through signal amplification, filtering, Fourier transform, and other technologies, effectively suppressing out-of-band interference and enhancing signal analysis capabilities in complex electromagnetic environments. It is suitable for a variety of terminal devices such as mobile phones, tablets, and smart watches, supports real-time monitoring and correction, and meets the intelligent detection needs of multi-band standards (such as 5G and Wi-Fi). The present invention solves the problem of unstable recognition caused by dynamic signal changes and improves the accuracy, adaptability, and applicability of radio signal detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The present invention will be further described below with reference to the accompanying drawings.

[0016] Figure 1 This is a schematic diagram of the steps of a multi-band radio signal intelligent detection method according to the present invention; Figure 2 The present invention is a schematic diagram of a radio signal intelligent detection system applicable to multi-band systems. DETAILED DESCRIPTION

[0017] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0018] See also Figure 1 As shown, the present invention is a method for intelligent detection of radio signals applicable to multi-band systems, comprising the following steps: Step S1: Setting a detection buffer interval, selecting a number of equally spaced time points within the detection buffer interval, acquiring radio signals of terminal devices within the detection buffer interval, and acquiring the communication quality index of the terminal devices at each time point in real time; and determining the optimal communication quality index of the terminal devices; The radio signal is collected by the detection center's multi-band receiving antenna (covering 800MHz to 6GHz) and RF front-end, capturing the downlink or uplink communication signals between the terminal device and the base station in real time, including control signaling, data frames, etc., and converting the analog signals into digital IQ data (sampling rate ≥ 2 times the signal bandwidth, in accordance with the Quistle theorem) through an analog-to-digital converter (ADC), which is then stored in a local cache. In a preferred embodiment of the present invention, the process of setting the detection buffer interval includes: The length of the time period T is preset, and the time when the detection of the radio signal of the terminal device starts is recorded as the starting time t0. According to the length of the time period and the starting time, the detection buffer interval [t0, t0+T] is obtained; Specifically, the length of the time period is preset for different scenarios based on actual conditions. For example, in a static indoor environment (such as an office or home), where terminal signals fluctuate slowly, T can be set to 30 seconds to 1 minute, sufficient to cover the stable signal fluctuation period. In a mobile outdoor environment (such as a street or in a vehicle), where terminal movement causes frequent signal fluctuations, T needs to be extended to 2 to 5 minutes to ensure that at least 2 to 3 frequency band switching or power adjustment events are captured. Select N time points (N ≥ 10 to ensure data density) equally within the buffer, with the interval between adjacent time points being T / N. For example, if T = 2 minutes (120 seconds) and N = 12, then select a time point every 10 seconds and number them from 1 to 12 to facilitate subsequent curve coordinate mapping. As a preferred embodiment of the present invention, the terminal device includes a mobile phone, a tablet, a laptop computer and a smart watch; As a preferred embodiment of the present invention, the process of obtaining the communication quality index of the terminal device includes: Set the signal strength range to [-110, 0] dBm, where the signal strength range represents the power strength range of the base station signal received by the terminal device; obtain the power strength of the base station signal received by the terminal device, and obtain the signal-to-noise ratio of the base station signal, and then obtain the communication quality index of the terminal device. , where K1 and K2 are weight coefficients, and K1>0, K2>0, where RSSI represents the power strength of the base station signal received by the terminal device, and SNR represents the signal-to-noise ratio of the base station signal; The weight coefficient reflects the contribution ratio of signal strength to signal-to-noise ratio; As a preferred embodiment of the present invention, the process of determining the best communication quality index includes: Set the maximum signal-to-noise ratio of the base station signal, the setting range of the maximum signal-to-noise ratio is [20, 40] dB, and obtain the best communication quality index , where SNRmax Indicates the maximum signal-to-noise ratio; Specifically, the power strength of the base station signal is sampled in real time by the power detection module of the radio frequency front end. The sampling is performed 10 times per second, and the maximum and minimum values ​​are removed and the average value is taken to obtain the RSSI value at that time point. The effective range of RSSI is set to [-110, 0] dBm. The signal-to-noise ratio of the base station signal is determined by separating the signal power from the noise power through frequency domain analysis: the noise power is measured during the silent period of the signal frame (such as the GP guard interval of LTE), and the total power is measured during the data transmission period. The difference between the two is the SNR; Furthermore, the weight coefficients are set according to the scenario. When in a signal-dominated scenario (such as a suburban area), K1=0.6 and K2=0.4. In this case, signal strength has a greater impact on communication quality. When in an interference-dominated scenario (such as a dense urban area), K1=0.4 and K2=0.6. In this case, anti-interference ability is more critical. K1+K2=1 ensures that the index can be quantified and compared. Step S2: generating a communication quality curve of the terminal device according to the communication quality index obtained in real time; and extracting a plurality of signal characteristic indicators of the radio signal, obtaining the signal characteristics of the signal characteristic indicators at each time point, and obtaining a signal characteristic change curve of each signal characteristic indicator; As a preferred embodiment of the present invention, the process of generating the communication quality curve includes: Numbering each time point, using the number as the horizontal coordinate and the communication quality index as the vertical coordinate, to establish a coordinate system. On the coordinate system, convert each numbered time point and its corresponding communication quality index into a coordinate point at a corresponding position, and fit each coordinate point to obtain a communication quality curve. Specifically, the communication quality index at each time point corresponds to the coordinate point (P, Q P ), P is the Pth number, Q P is the communication quality index at the Pth time point, and the coordinate points are fitted using the cubic spline interpolation method; For adjacent points (P, Q P ) and (P+1, Q P+1 ), smooth transitions are achieved through interpolation functions to avoid sudden rises and falls in the curve caused by single-point noise. After fitting, outliers whose residuals exceed a threshold (e.g., twice the average residual) are removed to ensure that the curve truly reflects the overall trend of communication quality (e.g., rising segments indicate signal improvement, and falling segments indicate signal deterioration). Calculate the average error between the fitted curve and the original coordinate points. If the error exceeds 5%, increase the number of time points (e.g., from N=30 to N=60) and refit until the error meets the requirements. As a preferred embodiment of the present invention, the process of extracting each signal characteristic indicator in the radio signal includes: amplifying and filtering the radio signal to suppress out-of-band interference, determining a sampling rate of the radio signal based on Quissite's theorem, and converting the analog signal into a digital signal according to the sampling rate; identifying a synchronization sequence of the radio signal through a detection algorithm, obtaining a time position of the synchronization sequence, and determining a frame boundary and a symbol period; performing a fast Fourier transform on the digital signal to obtain a frequency domain signal; and obtaining several signal characteristic indicators of the radio signal based on the frequency domain signal, wherein the signal characteristic indicators include a modulation mode, a bandwidth, a spectrum characteristic, and a frame structure; Specifically, synchronization sequence detection uses a sliding correlation algorithm to calculate the correlation between the received signal and a preset synchronization sequence template (such as the primary synchronization signal PSS sequence in LTE and the training sequence in GSM). When the correlation value exceeds a threshold (such as 0.8), the time position of the synchronization sequence is recorded (accurate to the symbol level). Frame boundaries and symbol periods are determined based on the synchronization sequence position, and the frame structure is divided according to the protocol specification. As a preferred embodiment of the present invention, the process of acquiring the signal characteristics includes: For any time point, obtain the value of the signal characteristic indicator at the time point. If the value of the signal characteristic indicator is a numerical value, directly record the numerical value as the signal characteristic of the signal characteristic indicator; if the value of the signal characteristic indicator is not, binary encode the numerical value to obtain a binary numerical value, and record the binary numerical value as the signal characteristic of the signal characteristic indicator; In a preferred embodiment of the present invention, the process of obtaining the signal characteristic change curve of the signal characteristic indicator includes: Establish a new coordinate system with the number of the time point as the horizontal coordinate and the signal feature as the vertical coordinate, convert each numbered time point and its corresponding signal feature into a coordinate point of the corresponding position in the new coordinate system, connect each coordinate point with a smooth curve, and record the curve as a signal feature change curve; Step S3: For any signal characteristic indicator, the communication quality curve is compared with the signal characteristic change curve of the signal characteristic indicator to obtain an adaptive rule model between the signal characteristic indicator and the communication quality index; Predicting, according to the adaptive rule model, signal characteristics of each signal characteristic indicator of the terminal device at the optimal communication quality index, obtaining device information of the terminal device, and modifying the device information in real time; In a preferred embodiment of the present invention, the process of comparing the communication quality curve with the signal characteristic change curve includes: Obtaining a monotonically increasing interval and a monotonically decreasing interval on the communication quality curve, both of which are recorded as signal change intervals, and obtaining a monotonically increasing interval and a monotonically decreasing interval on the signal characteristic change curve, both of which are recorded as characteristic change intervals; Get the horizontal coordinates of the starting point and end point of each signal change interval, and get the signal change endpoint set {(P1 start , P1 end ), (P2 start , P2 end ),...,(Pn start , Pn end )}, where Pn start Indicates the horizontal coordinate corresponding to the starting point of the nth signal change interval, Pn end The horizontal coordinate corresponding to the end point of the nth signal change interval, where n is the total number of signal change intervals; Get the horizontal coordinates corresponding to the starting point and end point of each feature change interval, and get the feature change endpoint set {(P1´ start , P1´ end ), (P2´ start , P2´ end ),...,(Pm´ start , Pm´ end )}, where Pm´ start Indicates the horizontal coordinate corresponding to the starting point of the mth feature change interval, Pm´ end Indicates the abscissa corresponding to the end point of the mth feature change interval, where m is the total number of feature change intervals; Set the delay threshold time, if the communication quality curve and the signal characteristic change curve meet , then the signal characteristic index corresponding to the signal characteristic change curve is marked as a non-fixed characteristic; otherwise, the signal characteristic index corresponding to the signal characteristic change curve is marked as a fixed characteristic; wherein, Pi start Indicates the horizontal coordinate corresponding to the starting point of the i-th signal change interval, Pi´ start Represents the horizontal coordinate corresponding to the starting point of the i-th feature change interval, i∈[1,n] and i is a positive integer; Specifically, the communication quality curve and each signal characteristic change curve are segmented and analyzed to identify the monotonically increasing and monotonically decreasing intervals, that is, the stages where the signal characteristic values ​​continue to rise or fall over time; Traversing the communication quality curve, when the communication quality index at three or more consecutive time points shows that the latter value is greater than the former value (increasing) or the latter value is less than the former value (decreasing), the segment is marked as the signal change interval; for example, if the communication quality index at time points 5 to 8 rises from -30 to -20 (increasing), the interval is (5, 8), and the starting point abscissa P1 start =5, end point horizontal coordinate P1end =8; The same operation is performed on each signal characteristic change curve to identify the monotonic interval of the characteristic value; The delay threshold is determined based on the signal propagation delay and the device response speed. In indoor scenarios, there is less signal reflection and the device responds quickly, so the time is set to 1 to 2 time intervals. In outdoor mobile scenarios, the multipath effect is significant and the device switching delay is high, so the time is set to 3 to 5 time intervals. As a preferred embodiment of the present invention, the process of obtaining the adaptive rule model includes: Intercepting each signal change interval and intercepting each feature change interval of each non-fixed feature, for any communication quality index in the signal change interval, obtaining a signal feature corresponding to the communication quality index in the feature change interval with the same number, and recording the communication quality index and its corresponding signal feature as a set of sample data, thereby obtaining several sets of sample data, which are recorded as sample data sets; establishing an initial model based on a neural network, inputting the sample data sets into the initial model, training the initial model, and obtaining an adaptive rule model representing how the signal feature changes with changes in the communication quality index; Specifically, a BP neural network (3-layer structure: 1 neuron in the input layer (communication quality index), 10 to 20 neurons in the hidden layer, and 1 neuron in the output layer (eigenvalue)) was selected as the initial model. The sample data set was input, and the mean square error (MSE) was used as the loss function. The gradient descent method was used for iterative training. The learning rate was set to 0.01 to 0.05, and the number of iterations was 500 to 1000 until the loss function converged, that is, MSE < 0.01. After training, the model can output the mapping relationship between the communication quality index and the non-fixed eigenvalue. In a preferred embodiment of the present invention, the process of obtaining the device information of the terminal device includes: According to the adaptive rule model, signal features of each non-fixed feature at the optimal communication quality index are obtained and recorded as predicted signal features; and a sample library is established, wherein the sample library includes signal features corresponding to each device indicator, wherein the device indicators include device distance, device operator, and device type; Establishing an initial classification model based on a decision tree, training the initial classification model based on the sample library to obtain a classification model; sequentially inputting each predicted signal feature and each fixed feature signal feature into the classification model to obtain a number of device indicators, and obtaining device information of the terminal device from all the device indicators; Specifically, the sample library contains the mapping relationship between the features and indicators of known devices. For example, the associated feature of device distance is the signal strength attenuation rate, and the associated features of device operators are fixed features such as PLMN code and frequency band authorization range. Using the sample library as the training set, a decision tree is constructed. The root node is the core feature, such as the PLMN code to distinguish operators, and the child nodes are detailed features, such as the frequency band range to further confirm operators. During the training process, cross-validation is used to optimize the tree depth to avoid overfitting. The final model accuracy must be ≥ 90%. In a preferred embodiment of the present invention, the process of correcting the device information in real time includes: After the detection buffer period ends, the communication quality index of the terminal device is monitored in real time. When the communication quality index is consistent with the optimal communication quality index, the signal characteristics of each signal characteristic indicator at this time are obtained and recorded as the optimal signal characteristics; according to the classification model, the device indicators corresponding to each optimal signal characteristic are obtained and recorded as the optimal device indicators; and each device indicator in the device information is corrected according to each optimal device indicator. If any device indicator is inconsistent with the optimal device indicator, the device indicator in the device information is replaced with the optimal device indicator; Specifically, after the detection buffer period ends, the device enters the real-time monitoring mode. When the communication quality index is consistent with the optimal value, the actual value of the non-fixed feature at this time is recorded, which is the optimal signal feature; and the fixed feature does not need to be collected repeatedly; the optimal signal feature is input into the classification model to obtain the optimal device index. If the optimal index is consistent with the original device information, the original information is retained. If there is an inconsistency, the corresponding index in the original device information is replaced with the optimal index to complete the correction.

[0019] A multi-band radio signal intelligent detection system comprising: Signal acquisition module: includes a detection center and terminal devices; sets a detection buffer zone of the detection center, selects several time points equally spaced within the detection buffer zone, acquires radio signals of terminal devices within the detection buffer zone, and obtains the communication quality index of the terminal devices at each time point in real time; and determines the optimal communication quality index of the terminal devices; Preprocessing module: sets a detection buffer interval, selects a number of time points equally spaced within the detection buffer interval, obtains radio signals of terminal devices within the detection buffer interval, and obtains the communication quality index of the terminal devices at each time point in real time; and determines the optimal communication quality index of the terminal devices; Feature matching module: for any signal feature indicator, compares the communication quality curve with the signal feature change curve of the signal feature indicator to obtain an adaptive rule model between the signal feature indicator and the communication quality index; According to the adaptive rule model, the signal characteristics of each signal characteristic indicator of the terminal device at the best communication quality index are predicted, and the device information of the terminal device is obtained, and the device information is corrected in real time.

[0020] The above is a detailed description of one embodiment of the present invention. However, the content described is only a preferred embodiment of the present invention and should not be considered to limit the scope of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the present invention.

Claims

1. A method for intelligent detection of radio signals applicable to multi-band systems, characterized in that: The following steps are involved: Step S1: Setting a detection buffer interval, selecting a number of equally spaced time points within the detection buffer interval, acquiring radio signals of terminal devices within the detection buffer interval, and acquiring the communication quality index of the terminal devices at each time point in real time; and determining the optimal communication quality index of the terminal devices; Step S2: generating a communication quality curve of the terminal device according to the communication quality index obtained in real time; and extracting a plurality of signal characteristic indicators of the radio signal, obtaining the signal characteristics of the signal characteristic indicators at each time point, and obtaining a signal characteristic change curve of each signal characteristic indicator; Step S3: For any signal characteristic indicator, the communication quality curve is compared with the signal characteristic change curve of the signal characteristic indicator to obtain an adaptive rule model between the signal characteristic indicator and the communication quality index; According to the adaptive rule model, the signal characteristics of each signal characteristic indicator of the terminal device at the best communication quality index are predicted, and the device information of the terminal device is obtained, and the device information is corrected in real time.

2. The method for intelligent detection of radio signals applicable to multi-band systems according to claim 1, characterized in that: In step S1, the process of setting the detection buffer interval includes: The time period length T is preset, and the time when the radio signal of the terminal device is detected is recorded as the starting time t0. According to the time period length and the starting time, the detection buffer interval [t0, t0+T] is obtained.

3. The method for intelligent detection of radio signals applicable to multiple frequency bands according to claim 1, characterized in that: In step S1, the process of acquiring the communication quality index of the terminal device includes: Set the signal strength range to [-110, 0] dBm, where the signal strength range represents the power strength range of the base station signal received by the terminal device; obtain the power strength of the base station signal received by the terminal device, and obtain the signal-to-noise ratio of the base station signal, and then obtain the communication quality index of the terminal device. , where K1 and K2 are weight coefficients, and K1>0, K2>0, where RSSI represents the power strength of the base station signal received by the terminal device, and SNR represents the signal-to-noise ratio of the base station signal.

4. The method for intelligent detection of radio signals applicable to multiple frequency bands according to claim 3, characterized in that: In step S1, the process of determining the best communication quality index includes: Set the maximum signal-to-noise ratio of the base station signal, the setting range of the maximum signal-to-noise ratio is [20, 40] dB, and obtain the best communication quality index , where SNR max Indicates the maximum signal-to-noise ratio.

5. The method for intelligent detection of radio signals applicable to multiple frequency bands according to claim 1, characterized in that: In step S2, the process of extracting each signal characteristic indicator from the radio signal includes: The radio signal is amplified and filtered to suppress out-of-band interference, and the sampling rate of the radio signal is determined based on the Quistle theorem, and the analog signal is converted into a digital signal according to the sampling rate; the synchronization sequence of the radio signal is identified through a detection algorithm, the time position of the synchronization sequence is obtained, and the frame boundary and symbol period are determined; and the digital signal is fast Fourier transformed to obtain a frequency domain signal; based on the frequency domain signal, several signal characteristic indicators of the radio signal are obtained, and the signal characteristic indicators include modulation mode, bandwidth, spectrum characteristics and frame structure.

6. The method for intelligent detection of radio signals applicable to multiple frequency bands according to claim 1, characterized in that: In step S2, the signal feature acquisition process includes: For any time point, obtain the value of the signal characteristic indicator at the time point. If the value of the signal characteristic indicator is a numerical value, directly record the numerical value as the signal characteristic of the signal characteristic indicator; if the value of the signal characteristic indicator is not, binary encode the numerical value to obtain a binary numerical value, and record the binary numerical value as the signal characteristic of the signal characteristic indicator.

7. The method for intelligent detection of radio signals applicable to multiple frequency bands according to claim 1, characterized in that: In step S3, the process of comparing the communication quality curve with the signal characteristic change curve includes: Obtaining a monotonically increasing interval and a monotonically decreasing interval on the communication quality curve, both of which are recorded as signal change intervals, and obtaining a monotonically increasing interval and a monotonically decreasing interval on the signal characteristic change curve, both of which are recorded as characteristic change intervals; Get the horizontal coordinates of the starting point and end point of each signal change interval, and get the signal change endpoint set {(P1 start , P1 end ), (P2 start , P2 end ),...,(Pn start , Pn end )}, where Pn start Indicates the horizontal coordinate corresponding to the starting point of the nth signal change interval, Pn end The horizontal coordinate corresponding to the end point of the nth signal change interval, where n is the total number of signal change intervals; Get the horizontal coordinates corresponding to the starting point and end point of each feature change interval, and get the feature change endpoint set {(P1´ start , P1´ end ), (P2´ start , P2´ end ),...,(Pm´ start , Pm´ end )}, where Pm´ start Indicates the horizontal coordinate corresponding to the starting point of the mth feature change interval, Pm´ end Indicates the abscissa corresponding to the end point of the mth feature change interval, where m is the total number of feature change intervals; Set the delay threshold time, if the communication quality curve and the signal characteristic change curve meet , then the signal characteristic index corresponding to the signal characteristic change curve is marked as a non-fixed characteristic; otherwise, the signal characteristic index corresponding to the signal characteristic change curve is marked as a fixed characteristic; wherein, Pi start Indicates the horizontal coordinate corresponding to the starting point of the i-th signal change interval, Pi´ start Represents the horizontal coordinate corresponding to the starting point of the i-th feature change interval, i∈[1,n] and i is a positive integer.

8. The method for intelligent detection of radio signals applicable to multiple frequency bands according to claim 7, characterized in that: In step S3, the process of obtaining the adaptive rule model includes: Each signal change interval is intercepted, and the feature change interval of each non-fixed feature is intercepted. For any communication quality index in the signal change interval, the signal feature corresponding to the communication quality index is obtained in the feature change interval with the same number, and the communication quality index and its corresponding signal feature are recorded as a set of sample data, thereby obtaining several sets of sample data, which are recorded as sample data sets; an initial model is established based on a neural network, the sample data sets are input into the initial model, and the initial model is trained to obtain an adaptive rule model representing that the signal feature changes with the communication quality index.

9. An intelligent radio signal detection system suitable for multi-band systems, characterized in that: include: Signal acquisition module: including detection center and terminal equipment; Setting a detection buffer zone of the detection center, selecting a number of time points equally spaced within the detection buffer zone, acquiring radio signals of terminal devices within the detection buffer zone, and acquiring a communication quality index of the terminal devices at each time point in real time; and determining an optimal communication quality index of the terminal devices; Preprocessing module: sets a detection buffer interval, selects a number of time points equally spaced within the detection buffer interval, obtains radio signals of terminal devices within the detection buffer interval, and obtains the communication quality index of the terminal devices at each time point in real time; and determines the optimal communication quality index of the terminal devices; Feature matching module: for any signal feature indicator, compares the communication quality curve with the signal feature change curve of the signal feature indicator to obtain an adaptive rule model between the signal feature indicator and the communication quality index; According to the adaptive rule model, the signal characteristics of each signal characteristic indicator of the terminal device at the best communication quality index are predicted, and the device information of the terminal device is obtained, and the device information is corrected in real time.

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