A wireless signal intelligent sensing method, device, computer equipment and storage medium

Abstract

The present application provides a method, device, computer equipment and storage medium for intelligent perception of wireless signals. The method first needs to determine the target monitoring frequency band. Then determine the first power of the wireless signal in the frequency band, and judge whether the interference condition is met based on the first power. If the interference condition is met, a sliding window with a step bandwidth as the width traverses the target monitoring frequency band, and determines the second power of the wireless signal in the sliding window at each sliding, and judges whether there is an interference signal in the current sliding window. If so, it is determined as the target window. After that, the adjacent target windows are merged, and finally the type of interference signal is determined based on the distribution of the target window in the target monitoring frequency band. This method can comprehensively and accurately monitor wireless signals, promptly detect interference signals and determine their types, provide a basis for taking targeted interference suppression measures, and help improve the quality and stability of wireless signals.

Description

Technical Field

[0001] The present application relates to the field of wireless signal sensing technology, and in particular to a wireless signal intelligent sensing method, device, computer equipment and storage medium. Background Art

[0002] With the continuous development and popularization of communication technology, the factors that interfere with the transmission and reception of wireless signals are gradually increasing. These interferences will reduce the performance of the communication system and even lead to a decline in data transmission quality or communication interruption. Especially in special places such as airports, airports are often interfered with by wireless signals, including radio interference and interference with the dedicated frequency of ground-to-air communication.

[0003] ‌Radio interference‌ refers to the phenomenon that during the radio communication process, some electromagnetic energy enters the receiving system or channel directly or indirectly, resulting in a decrease in the quality of useful received signals, errors or loss of information, or even blocking of communications. This interference may come from various sources, such as radio and television signals, mobile communication equipment, etc. If the interference is strong to a certain extent, it may have a serious impact on aviation communications and affect the normal operation of flights. ‌Interference with the dedicated frequency for ground-to-air communication‌ means that the dedicated frequency for ground-to-air communication at the airport is interfered with by other signals, resulting in obstruction of normal communication and a major safety hazard. This interference may be caused by high-power speakers near the airport, white noise generated by lawn mowers, LED screen failures, improper use of radio walkie-talkies, illegal radio stations, etc. In traditional technologies, although it is possible to identify whether there is interference, it is often impossible to determine the type of interference, which makes it impossible to improve the anti-interference ability of the communication system in a targeted manner, which is not conducive to the management of the wireless environment. Summary of the invention

[0004] The purpose of the present application is to solve at least one of the above-mentioned technical defects, and in particular to provide a solution that can efficiently and accurately determine the occurrence of wireless interference and identify the type of wireless interference.

[0005] In a first aspect, the present application provides a wireless signal intelligent sensing method, which is applied to a wireless signal intelligent sensing device, wherein the wireless signal intelligent sensing device includes an antenna, and the antenna is used to collect wireless signals. The wireless signal intelligent sensing method includes:

[0006] The target monitoring frequency band is determined according to the central frequency point of the target frequency band and the monitoring bandwidth; the monitoring bandwidth is greater than the width of the target frequency band;

[0007] Determine a first power of the wireless signal in a target monitoring frequency band;

[0008] Determining whether an interference condition is met according to the first power;

[0009] If so, the target monitoring frequency band is traversed with a sliding window whose width is the step bandwidth; the step bandwidth is smaller than the monitoring bandwidth;

[0010] During each sliding operation, the second power of the wireless signal in the sliding window is determined, and it is judged whether there is an interference signal in the current sliding window according to the second power. If so, the current sliding window is determined as a target window;

[0011] Merge adjacent target windows;

[0012] The type of interference signal is determined based on the distribution of the target window in the target monitoring frequency band.

[0013] In one embodiment, determining the type of interference signal according to the distribution of the target window in the target monitoring frequency band includes:

[0014] For any target window, if the target window covers the entire target monitoring frequency band, it is determined that the type of interference signal corresponding to the target window is white noise interference;

[0015] If the target window only covers part of the target monitoring frequency band, then determine whether the target window contains the target frequency band;

[0016] If not, it is determined that the type of interference signal corresponding to the target window is adjacent frequency interference;

[0017] If so, when the frequency band of the target window is exactly the same as the target frequency band, the type of interference signal corresponding to the target window is determined to be co-channel interference; when the frequency band of the target window is not exactly the same as the target frequency band, the type of interference signal corresponding to the target window is determined to be broadband interference.

[0018] In one of the embodiments, after determining the type of the interference signal according to the distribution of the target window in the target monitoring frequency band, the method further includes:

[0019] According to the preset priority, one is selected from the frequency bands to be detected as a new target frequency band, and the step of determining the target monitoring frequency band according to the center frequency point and monitoring bandwidth of the target frequency band is returned to continue execution until all the frequency bands to be detected have been selected as target frequency bands.

[0020] In one embodiment, determining whether the interference condition is met according to the first power includes:

[0021] If the first power is greater than the first threshold, or the signal-to-noise ratio determined based on the first power and the third power is less than the signal-to-noise ratio threshold, it is determined that the first power meets the interference condition; the third power is the power of the wireless signal in the target frequency band.

[0022] In one of the embodiments, judging whether there is an interference signal in the current sliding window according to the second power includes:

[0023] If the second power is greater than the second threshold, it is determined that there is an interference signal in the current sliding window.

[0024] In a second aspect, the present application provides a wireless signal intelligent sensing method, which is applied to a wireless signal intelligent sensing system, the wireless signal intelligent sensing system is deployed in a target area, the wireless signal intelligent sensing system includes multiple wireless signal intelligent sensing devices, the wireless signal intelligent sensing device is configured to execute the wireless signal intelligent sensing method in any of the above embodiments, the target area is divided into multiple grids, each grid is provided with a one-to-one corresponding wireless signal intelligent sensing device, and the wireless signal intelligent sensing method includes:

[0025] Collect detection information uploaded by each wireless signal intelligent sensing device; the detection information includes the type of interference signal and the second power corresponding to the target window where the interference signal is located;

[0026] For the same type of interference signal, the wireless signal intelligent sensing device including the interference signal of the type in the uploaded detection information is determined as the target device, and the distance between the signal source of the interference signal of the type and each target device is determined respectively according to the second power uploaded by at least three target devices;

[0027] Determine the location of the signal source based on the distance between the signal source and each target device.

[0028] In one embodiment, determining the location of the signal source according to the distance between the signal source and each target device includes:

[0029] For any target device, an auxiliary circle is generated with the location of the target device as the center and the distance between the target device and the signal source as the radius;

[0030] The location of the signal source is determined based on the intersection of the auxiliary circles.

[0031] In a third aspect, the present application provides a wireless signal intelligent sensing device, which is applied to a wireless signal intelligent sensing device. The wireless signal intelligent sensing device includes an antenna, which is used to collect wireless signals. The wireless signal intelligent sensing device includes:

[0032] An initialization module is used to determine a target monitoring frequency band according to a central frequency point of the target frequency band and a monitoring bandwidth; the monitoring bandwidth is greater than a width of the target frequency band;

[0033] A first power determination module, used to determine a first power of a wireless signal in a target monitoring frequency band;

[0034] A first judging module, used for judging whether an interference condition is met according to the first power;

[0035] A traversal module, used to traverse the target monitoring frequency band with a sliding window having a width as a step bandwidth when the interference condition is met;

[0036] A second judgment module is used to determine the second power of the wireless signal in the sliding window at each sliding, and judge whether there is an interference signal in the current sliding window according to the second power, and if so, determine the current sliding window as a target window;

[0037] A merging module, used to merge adjacent target windows;

[0038] The type determination module is used to determine the type of interference signal according to the distribution of the target window in the target monitoring frequency band.

[0039] In a fourth aspect, the present application provides a computer device comprising one or more processors and a memory, wherein the memory stores computer-readable instructions, and when the computer-readable instructions are executed by one or more processors, the steps of the wireless signal intelligent sensing method in any of the above embodiments are executed.

[0040] In a fifth aspect, the present application provides a storage medium storing computer-readable instructions. When the computer-readable instructions are executed by one or more processors, the one or more processors execute the steps of the wireless signal intelligent sensing method in any of the above embodiments.

[0041] It can be seen from the above technical solutions that the embodiments of the present application have the following advantages:

[0042] Based on the wireless signal intelligent perception method in this embodiment, the target monitoring frequency band is first determined according to the center frequency of the target frequency band and the monitoring bandwidth greater than the width of the target frequency band. Then, the first power of the wireless signal in the frequency band is determined, and whether the interference condition is met is determined according to the first power. If the interference condition is met, the sliding window with the step bandwidth as the width traverses the target monitoring frequency band, and the second power of the wireless signal in the sliding window is determined at each sliding, and it is determined whether there is an interference signal in the current sliding window. If it exists, it is determined as the target window. After that, the adjacent target windows are merged, and finally the type of interference signal is determined according to the distribution of the target window in the target monitoring frequency band. This method can comprehensively and accurately monitor wireless signals, timely detect interference signals and determine their types. By setting the monitoring bandwidth greater than the width of the target frequency band, the area where interference may occur can be more widely monitored. The target window is determined by sliding window traversal and power judgment, and then the adjacent target windows are merged, so that the position and range of the interference signal can be more accurately located. Finally, the type of interference signal is determined according to the distribution of the target window, which provides a basis for taking targeted interference suppression measures and helps to improve the quality and stability of wireless signals. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0044] Figure 1 A flowchart of a wireless signal intelligent sensing method in one embodiment of the present application;

[0045] Figure 2 A schematic diagram of a flow chart for identifying interference signal types in one embodiment of the present application;

[0046] Figure 3 A schematic diagram of locating an interference signal source in one embodiment of the present application;

[0047] Figure 4 This is a flow chart of a method for intelligently sensing wireless signals in another embodiment of the present application;

[0048] Figure 5 An internal structure diagram of a computer device provided for one embodiment of the present application. DETAILED DESCRIPTION

[0049] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0050] The present application provides a wireless signal intelligent sensing method, which is applied to a wireless signal intelligent sensing device. The wireless signal intelligent sensing device includes an antenna, and the antenna is used to collect wireless signals. Specifically, the antenna adopts a radio frequency antenna, which can collect all frequency band wireless signals in the space. In view of the limited bandwidth of the low-frequency band antenna, a combiner can be used to realize wireless signal reception. The combined wireless signal is input to the radio frequency unit, which serves as a signal input unit and supports full-band link matching for the received wireless signal. The radio frequency unit transmits the wireless signal to the frequency conversion circuit, which can convert the wireless signal at a fixed time to the corresponding intermediate frequency band. In view of the fact that the analog-to-digital conversion unit can only process part of the broadband signal, it is necessary to analyze the wireless signal of the full frequency band in turn through the frequency conversion circuit and the filtering circuit. The wireless signal after the frequency conversion circuit and the filtering unit is input to the analog-to-digital conversion unit to realize sampling, and the power statistics unit realizes the fixed / variable bandwidth power statistics analysis in the spectrum under the control of the control unit. A parsing module can also be set to decode and analyze the information transmitted by the wireless signal.

[0051] Through the wireless signal intelligent sensing device and the sensing method configured therein, it is possible to analyze whether the communication system at the location where the wireless signal intelligent sensing device is set is interfered with and the type of interference. Specifically, refer to Figure 1 The wireless signal intelligent sensing method includes steps S102 to S114.

[0052] S102, determining a target monitoring frequency band according to a central frequency point of the target frequency band and a monitoring bandwidth. The monitoring bandwidth is greater than a width of the target frequency band.

[0053] It can be understood that the transmission and reception of wireless signals are usually carried out within a specific frequency band. The content transmitted by wireless signals in different frequency bands is also different. For example, in an airport environment, band A is used for communication and band B is used for navigation. The target frequency band is the frequency range where the specific signal we are concerned about is located, and the center frequency point is the center position of this frequency band, which can help us quickly locate the target frequency band. The monitoring bandwidth is set to monitor the signal conditions around the target frequency band more widely, because the interference signal may come from near the target frequency band. By determining a monitoring bandwidth wider than the target frequency band, the source of interference signals that may affect the target frequency band can be discovered in advance. Therefore, when we want to monitor a specific wireless communication frequency band, after knowing the center frequency point of the target frequency band, we can use this center frequency point as a benchmark and combine it with the monitoring bandwidth to determine a wider target monitoring frequency band.

[0054] The selection of monitoring bandwidth should take into account a variety of factors, such as the characteristics of the target frequency band, the types of possible interference sources, environmental factors, etc. If the target frequency band is used for low-power wireless communication, a relatively narrow monitoring bandwidth may need to be set to avoid too many irrelevant signals interfering with the analysis. If the target frequency band is in a complex electromagnetic environment, a wider monitoring bandwidth may need to be set to ensure that potential interference signals can be captured. When determining the target monitoring frequency band, the center frequency can be used as the center and half of the monitoring bandwidth can be extended to both sides to obtain the complete target monitoring frequency band. For example, if the center frequency of the target frequency band is 1GHz and the monitoring bandwidth is set to 200MHz, then the target monitoring frequency band is from 0.9GHz to 1.1GHz.

[0055] S104: Determine a first power of the wireless signal in a target monitoring frequency band.

[0056] It can be understood that the wireless signal in this step refers to the full-band wireless signal received by the antenna on the wireless signal intelligent sensing device. Power is an important indicator to measure the strength of signal energy. Determining the first power of the wireless signal in the target monitoring frequency band can help us understand the strength and stability of the signal. In the target monitoring frequency band, the power of the wireless signal will be affected by many factors, such as the power of the transmitting source, distance, propagation environment, etc. By measuring the first power, we can preliminarily judge the quality of the signal and possible problems. The first power can be obtained by integrating the power of the wireless signal in the target monitoring frequency band, and specifically, the periodogram method, Welch method, BT method, etc. can be used.

[0057] S106: Determine whether an interference condition is met according to the first power.

[0058] It can be understood that the interference condition refers to a pre-set standard for determining whether a wireless signal is interfered with. When a wireless signal is interfered with during transmission, its power in the target monitoring frequency band will change. By comparing the first power of the wireless signal with the preset interference condition, it can be determined whether the signal is interfered with. The interference condition can be set according to specific application scenarios and requirements. For example, the power of the wireless signal in the target frequency band under an ideal wireless environment can be determined first, and a fixed value can be added to the power to obtain a first threshold. If the first power is higher than the first threshold, it means that in the target monitoring frequency band including the target frequency band, there are other signal sources other than the effective signal source sending signals and being received by the wireless signal intelligent sensing device, and the signal can be considered to be interfered with at this time. Or a power change rate can be set, and if the change rate of the first power within a period of time exceeds a certain range, the signal can also be considered to be interfered with. In addition, other signal quality indicators, such as signal-to-noise ratio, can be combined to comprehensively determine whether the signal is interfered with. The power of the wireless signal in the target frequency band can be defined as a third power, and the first power can be subtracted from the third power to obtain the noise power, and the noise power can be compared with the third power to obtain the signal-to-noise ratio. When the signal-to-noise ratio is less than the signal-to-noise ratio threshold, it can be considered that the signal is interfered.

[0059] S108: If yes, traverse the target monitoring frequency band with a sliding window whose width is the step bandwidth.

[0060] It can be understood that the step bandwidth is a small bandwidth smaller than the monitoring bandwidth. When it is determined that the wireless signal meets the interference condition, it is necessary to further determine the specific frequency band information of the interference signal. By traversing the target monitoring frequency band with a sliding window whose width is the step bandwidth, the target monitoring frequency band can be divided into multiple small intervals, and these intervals are analyzed one by one to determine the specific frequency band information of the interference signal.

[0061] Generally speaking, if the target monitoring frequency band is wide and the frequency range of the interference signal is uncertain, a smaller step bandwidth can be selected to ensure that the entire frequency band can be fully analyzed. For example, if the width of the target frequency band is 20kHz, the monitoring bandwidth can be selected as 1MHz and the step bandwidth can be selected as 10kHz. If the target monitoring frequency band is narrow, or there are high requirements for the analysis speed, a larger step bandwidth can be selected. Then, starting from the starting position of the target monitoring frequency band, analyze it section by section in units of sliding windows. Each time the sliding window is moved, the position of the current sliding window in the target monitoring frequency band is recorded, and the signal in the sliding window is analyzed.

[0062] S110, during each sliding, determining the second power of the wireless signal in the sliding window, and judging whether there is an interference signal in the current sliding window according to the second power, and if so, determining the current sliding window as the target window.

[0063] It can be understood that in the process of the sliding window traversing the target monitoring frequency band, it is necessary to determine the wireless signal power in each sliding window, that is, the second power. By analyzing the second power, it can be determined whether there is an interference signal in the current sliding window. If the second power in the sliding window is greater than the background noise under theoretical conditions, it can be considered that there may be an interference signal in the current sliding window. Such a sliding window is determined as a target window for subsequent more in-depth analysis and processing. Therefore, the second threshold value can be obtained based on the theoretical background noise. When the second power is greater than the second threshold value, it can be determined that there is an interference signal in the current sliding window. For each target window, it is necessary to record the frequency band information of the target window, and it is also necessary to record its corresponding second power for subsequent analysis.

[0064] S112: Merge adjacent target windows.

[0065] It is understandable that after determining multiple target windows, it may be found that some adjacent target windows are actually caused by the same interference signal source. Merging adjacent target windows can reduce the complexity of analysis and improve the accuracy of interference identification. By merging target windows, the scattered interference signal areas can be integrated into a larger area, making it easier to determine and process the subsequent interference signal type. For example, if multiple adjacent sliding windows are determined as target windows, it is likely that the frequency band of the interference signal is wider, and the combination of multiple sliding windows covers its frequency band range. By merging these target windows, the interference signal can be analyzed as a whole.

[0066] For example, target windows that are adjacent in frequency and whose interval is less than a certain threshold can be regarded as adjacent target windows. Then, all target windows are traversed, and for each target window, it is checked whether it is adjacent to other target windows. If adjacent target windows are found, they are merged into a larger target window. The merging method can be to merge the frequency ranges of the two target windows together, or to take their union. At the same time, the relevant information of the target window, such as power, frequency band information, etc., can be updated. In the merging process, data structure operations can be used to implement it, such as merging arrays, connecting linked lists, etc. The merged target window can be used as a whole for subsequent analysis and processing. If the frequency band corresponding to the merged target window is a decodable frequency band, decoding analysis can be performed to obtain the cell number, signal-to-noise ratio, power, frequency, bandwidth, MAC address and other information of the interference signal.

[0067] S114, determining the type of the interference signal according to the distribution of the target window in the target monitoring frequency band.

[0068] It can be understood that different types of interference signals have different distribution characteristics in the target monitoring frequency band. By analyzing the distribution of the target window in the target monitoring frequency band, the type of interference signal can be inferred. For example, broadband interference covers a wider frequency range. White noise interference is distributed in the entire frequency band, and the power remains basically constant. By observing the distribution of the target window, the type of interference signal can be determined in combination with its characteristics. This is very important for taking targeted interference suppression measures.

[0069] Based on the wireless signal intelligent perception method in this embodiment, the target monitoring frequency band is first determined according to the center frequency of the target frequency band and the monitoring bandwidth greater than the width of the target frequency band. Then, the first power of the wireless signal in the frequency band is determined, and whether the interference condition is met is determined according to the first power. If the interference condition is met, the sliding window with the step bandwidth as the width traverses the target monitoring frequency band, and the second power of the wireless signal in the sliding window is determined at each sliding, and it is determined whether there is an interference signal in the current sliding window. If it exists, it is determined as the target window. After that, the adjacent target windows are merged, and finally the type of interference signal is determined according to the distribution of the target window in the target monitoring frequency band. This method can comprehensively and accurately monitor wireless signals, timely detect interference signals and determine their types. By setting the monitoring bandwidth greater than the width of the target frequency band, the area where interference may occur can be more widely monitored. The target window is determined by sliding window traversal and power judgment, and then the adjacent target windows are merged, so that the position and range of the interference signal can be more accurately located. Finally, the type of interference signal is determined according to the distribution of the target window, which provides a basis for taking targeted interference suppression measures and helps to improve the quality and stability of wireless signals.

[0070] In one embodiment, see Figure 2 , determining the type of interference signal according to the distribution of the target window in the target monitoring frequency band, including steps S202 to S208.

[0071] S202: For any target window, if the target window covers the entire target monitoring frequency band, determine that the type of the interference signal corresponding to the target window is white noise interference.

[0072] It can be understood that the spectrum distribution of white noise interference is relatively uniform, and there is no specific frequency concentration area. In wireless signal transmission, white noise interference may come from various random noise sources in nature, such as thermal noise, shot noise, etc., or it may be caused by factors such as internal noise of electronic equipment. The type of white noise interference is determined by judging whether the target window covers the entire target monitoring frequency band. This is based on the characteristics of white noise, that is, it is distributed in a wider frequency range. When a target window covers the entire target monitoring frequency band, it means that there is an interference signal in the entire monitoring range, then it is likely to be white noise interference.

[0073] Specifically, it is necessary to accurately record the position and range of each target window in the target monitoring frequency band. When analyzing a target window, its frequency range is compared with the target monitoring frequency band. If the starting frequency and ending frequency of the target window are consistent with the starting frequency and ending frequency of the target monitoring frequency band, respectively, then it can be determined that the target window covers the entire target monitoring frequency band. In order to more accurately determine whether it is white noise interference, further spectrum analysis can be performed on the signal in the target window. For example, a spectrum analyzer can be used to measure the part of the target window other than the target frequency band to observe whether its spectrum distribution is relatively uniform. If the power level of the signal is relatively stable within the frequency range, without obvious peaks or valleys, then it can be more certain that the interference signal is white noise interference. In practical applications, a judgment threshold corresponding to white noise interference can be set. If the power changes of the signal in the part of the target window other than the target frequency band are all less than the judgment threshold, it can be determined to be white noise interference.

[0074] S204: If the target window only covers part of the target monitoring frequency band, determine whether the target window includes the target frequency band.

[0075] It can be understood that when the target window only covers part of the target monitoring frequency band, it is necessary to further determine whether the target window contains the target frequency band to determine the type of interference signal. If the target window contains the target frequency band, the interference signal may have a direct impact on the wireless signal in the target frequency band; if the target window does not contain the target frequency band, the interference signal may be interference from other frequency ranges, and the impact on the target frequency band is relatively small or indirect. By judging the inclusion relationship between the target window and the target frequency band, different types of interference signals can be preliminarily distinguished, providing a basis for the subsequent determination of the type of interference signal.

[0076] Specifically, this step requires clarifying the positional relationship between the target window and the target frequency band on the frequency axis. The comparison can be made by recording the starting frequency and ending frequency of the target window, and the starting frequency and ending frequency of the target frequency band. If the starting frequency of the target window is less than the starting frequency of the target frequency band, and the ending frequency of the target window is greater than the starting frequency of the target frequency band, and the ending frequency of the target window is less than the ending frequency of the target frequency band, then it can be determined that the target window contains the target frequency band.

[0077] S206: If not, determine that the type of the interference signal corresponding to the target window is adjacent channel interference.

[0078] It can be understood that adjacent-channel interference refers to interference signals in frequency bands other than the target frequency band. In wireless communication systems, different wireless signals are usually transmitted on different frequency bands, but due to factors such as the non-ideality of the transmitting equipment and the performance limitations of the filter, signals in adjacent frequency bands may leak to the vicinity of the target frequency band, thereby generating adjacent-channel interference. The intensity of adjacent-channel interference is usually related to the frequency interval between the interference source and the target frequency band. The smaller the frequency interval, the stronger the interference. When the target window does not include the target frequency band, it means that the interference signal comes from the frequency range near the target frequency band, which meets the definition of adjacent-channel interference, and the interference signal can be determined to be adjacent-channel interference.

[0079] S208, if yes, then when the frequency band of the target window is exactly the same as the target frequency band, the type of interference signal corresponding to the target window is determined to be co-channel interference; when the frequency band of the target window is not exactly the same as the target frequency band, the type of interference signal corresponding to the target window is determined to be broadband interference.

[0080] It can be understood that if the target window contains the target frequency band, it is necessary to further determine the relationship between the frequency band of the target window and the target frequency band. When the frequency band of the target window is exactly the same as the target frequency band, it means that the interference signal and the target signal are at the same frequency. This interference is called co-channel interference. Co-channel interference is usually caused by multiple transmitting sources transmitting signals at the same frequency, or the same signal reaching the receiving end on different paths due to reflection, scattering, etc. When the frequency band of the target window is not exactly the same as the target frequency band, it means that the interference signal covers a wider frequency range and partially overlaps with the target frequency band. This interference is called broadband interference. Broadband interference may come from a variety of interference sources, such as noise from other wireless communication systems and electronic equipment.

[0081] Specifically, compare the start frequency and end frequency of the target window with the start frequency and end frequency of the target frequency band. If the two are exactly the same, it can be determined as co-channel interference. If the frequency range of the target window includes the target frequency band, but is not exactly the same, it can be determined as broadband interference.

[0082] In one of the embodiments, after determining the type of interference signal based on the distribution of the target window in the target monitoring frequency band, it also includes: selecting one from the frequency bands to be detected as a new target frequency band according to a preset priority, and returning to the step of determining the target monitoring frequency band based on the center frequency point and monitoring bandwidth of the target frequency band until all frequency bands to be detected have been selected as target frequency bands.

[0083] It is understandable that in a wireless signal environment, there may be multiple different frequency bands that need to be detected and analyzed for interference. These frequency bands are the frequency bands to be detected. By selecting new target frequency bands from the frequency bands to be detected according to the preset priority, each frequency band can be checked one by one in a targeted and systematic manner. The purpose of this is to ensure that all important frequency bands in the entire wireless signal environment can be fully monitored and analyzed, so as to promptly discover and deal with possible interference problems.

[0084] Among them, the switching of the target frequency band needs to rely on the frequency conversion circuit in the wireless signal intelligent sensing device, and the local oscillator parameters need to be reconfigured. The setting of preset priorities can be based on a variety of factors, such as the importance of different frequency bands, the frequency of use, and the degree of impact on system performance. For some frequency bands used by key businesses, a higher priority can be given and detection and analysis can be given priority. After determining the interference signal type of a target frequency band, continue to select a new target frequency band for processing, which can achieve comprehensive wireless signal intelligent perception and improve the stability and reliability of the entire wireless signal system.

[0085] For example, in a multi-band wireless communication system, some bands may be used for important data transmission, while other bands may be used for low-priority communication or backup communication. In this case, the bands used for important data transmission can be set to a higher priority to give priority to interference detection and analysis. If an interference signal is found in a target band and its type is determined, by selecting a new target band to continue the detection process, it can be discovered in time whether other bands also have interference problems, so that appropriate measures can be taken to suppress interference or adjust system configuration.

[0086] The present application provides a wireless signal intelligent sensing method, which is applied to a wireless signal intelligent sensing system. The method can locate the interference source of the wireless signal in a wider range. Specifically, the wireless signal intelligent sensing system includes multiple wireless signal intelligent sensing devices, and the wireless signal intelligent sensing devices are configured to execute the wireless signal intelligent sensing method in any of the above embodiments. Figure 3 , the wireless signal intelligent perception system is deployed in the target area. The target area here is a specific geographical range or spatial area where the wireless signals need to be monitored and perceived. The target area can be determined by first determining the location of all wireless signal receiving devices and signal receiving areas in a specific scene (such as an airport). Based on these signal receiving areas, the minimum enclosing rectangle that includes all signal receiving areas is determined as the target area.

[0087] The target area is divided into multiple grids, and each grid needs to be equipped with a wireless signal intelligent sensing device, such as Figure 3As shown in the figure, the target area is divided into 9 grids, and wireless signal intelligent sensing devices AF are set respectively. Each wireless signal intelligent sensing device has a certain detection range. When dividing the grids, the size of the grid should take into account the detection range of the wireless signal intelligent sensing device, so that the signal emitted by the interference signal source appearing in any grid can be received by at least three different wireless signal intelligent sensing devices. Specifically, the detection range of the wireless signal intelligent sensing device can cover not only the grid where it is located, but also other grids adjacent to the grid. For example, the wireless signal intelligent sensing device E can cover grids 1-9, and the wireless signal intelligent sensing device F can cover grids 2, 3, 5, 6, 8, and 9. The size of each grid can be the same or can be differentiated, which is not limited in this embodiment.

[0088] Through the above settings, in order to locate the interference signal source in the target area, it is also necessary to implement the wireless signal intelligent perception method applied to the system, see Figure 4 The wireless signal intelligent sensing method includes steps S402 to S406.

[0089] S402: Collect detection information uploaded by each wireless signal intelligent sensing device. The detection information includes the type of interference signal and the second power corresponding to the target window where the interference signal is located.

[0090] It can be understood that in addition to the wireless signal intelligent sensing device, the entire system can also be provided with a control center for communicating with each wireless signal intelligent sensing device to obtain the interference signal detection result of each wireless signal intelligent sensing device. The detection result is called detection information, which includes the interference signal type identified by the wireless signal intelligent sensing device and the second power recorded during the identification process.

[0091] S404: For the same type of interference signal, the wireless signal intelligent sensing device including the interference signal of this type in the uploaded detection information is determined as the target device, and the distance between the signal source of the interference signal of this type and each target device is determined respectively according to the second power uploaded by at least three target devices.

[0092] It can be understood that different types of interference signals correspond to different interference signal sources, so the same type of interference signals need to be analyzed separately. For the same type of interference signal, the device that has uploaded the detection information of the interference signal of this type is determined as the target device, so that the situation of the interference signal of this type can be analyzed centrally. Through the second power uploaded by at least three target devices, the signal propagation model can be used to determine the distance between the signal source of the interference signal and each target device. In general, the power of the signal decays with the increase of the distance. According to the known signal propagation model and power attenuation law, the distance between the signal source and the device can be inferred from the measured power value. Specifically, in the free space propagation model, the signal power is inversely proportional to the square of the distance. The distance between the signal source and the target device can be calculated by measuring the second power and parameters such as the average signal transmission power of the same type of interference signal source found in the target area.

[0093] by Figure 3 For example, Figure 3 The interference signal source in the example emits white noise interference, and the detection information reported by the wireless signal intelligent sensing devices C, F, and I all reflect that they have detected white noise interference. For this type of white noise interference, it is necessary to determine the distance between the interference signal source and itself according to the second power corresponding to the white noise interference reported by the wireless signal intelligent sensing devices C, F, and I.

[0094] S406: Determine the position of the signal source according to the distance between the signal source and each target device.

[0095] It can be understood that after the distance between the signal source and each target device is determined through the previous steps, the position of the signal source can be determined using a geometric positioning method. For example, a triangulation positioning method or a multilateral positioning method can be used. In a specific embodiment, in the last positioning step, for any target device, an auxiliary circle is generated with the location of the target device as the center and the distance between the target device and the signal source as the radius. Finally, the position of the signal source is determined based on the intersection of the auxiliary circles.

[0096] The present application provides a wireless signal intelligent sensing device, which is applied to a wireless signal intelligent sensing device. The wireless signal intelligent sensing device includes an antenna, which is used to collect wireless signals. The wireless signal intelligent sensing device includes an initialization module, a first power determination module, a first judgment module, a traversal module, a second judgment module, a merging module and a type determination module. The initialization module is used to determine the target monitoring frequency band according to the central frequency point and the monitoring bandwidth of the target frequency band. The monitoring bandwidth is greater than the width of the target frequency band. The first power determination module is used to determine the first power of the wireless signal in the target monitoring frequency band. The first judgment module is used to determine whether the interference condition is met according to the first power. The traversal module is used to traverse the target monitoring frequency band with a sliding window whose width is the step bandwidth when the interference condition is met. The second judgment module is used to determine the second power of the wireless signal in the sliding window at each sliding, and determine whether there is an interference signal in the current sliding window according to the second power. If so, the current sliding window is determined as the target window. The merging module is used to merge adjacent target windows. The type determination module is used to determine the type of interference signal according to the distribution of the target window in the target monitoring frequency band.

[0097] For the specific limitations of the wireless signal intelligent sensing device, please refer to the limitations of the wireless signal intelligent sensing method above, which will not be repeated here. Each module in the above-mentioned wireless signal intelligent sensing device can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules. It should be noted that the division of modules in the embodiment of the present application is schematic and is only a logical function division. There may be other division methods in actual implementation.

[0098] In one of the embodiments, computer-readable instructions are stored in the memory, and when the computer-readable instructions are executed by one or more processors, the steps of the wireless signal intelligent sensing method in any of the above embodiments are executed.

[0099] Indicatively, Figure 5 As shown, Figure 5 A schematic diagram of the internal structure of a computer device provided in an embodiment of the present application. Figure 5 The computer device 500 includes a processing component 502, which further includes one or more processors, and a memory resource represented by a memory 501, for storing instructions executable by the processing component 502, such as an application. The application stored in the memory 501 may include one or more modules, each corresponding to a set of instructions. In addition, the processing component 502 is configured to execute instructions to perform the steps of the wireless signal intelligent sensing method of any of the above embodiments.

[0100] The computer device 500 may further include a power supply component 503 configured to perform power management of the computer device 500 , a wired or wireless network interface 504 configured to connect the computer device 500 to a network, and an input / output (I / O) interface 505 .

[0101] In one embodiment, when the computer-readable instructions are executed by one or more processors, the one or more processors execute the steps of the wireless signal intelligent sensing method in any of the above embodiments.

[0102] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0103] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The various embodiments can be combined as needed, and the same or similar parts can refer to each other.

[0104] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A wireless signal intelligent sensing method, characterized in that: Applied to a wireless signal intelligent sensing device, the wireless signal intelligent sensing device includes an antenna, the antenna is used to collect wireless signals, and the wireless signal intelligent sensing method includes: Determining a target monitoring frequency band according to a central frequency point of the target frequency band and a monitoring bandwidth; the monitoring bandwidth is greater than a width of the target frequency band; Determine a first power of the wireless signal in the target monitoring frequency band; Determining whether an interference condition is met according to the first power; If yes, traverse the target monitoring frequency band with a sliding window having a width equal to a step bandwidth; the step bandwidth is smaller than the monitoring bandwidth; During each sliding operation, determining a second power of the wireless signal in the sliding window, and judging whether there is an interference signal in the current sliding window according to the second power, and if so, determining the current sliding window as a target window; Merging adjacent target windows; Determine the type of the interference signal according to the distribution of the target window in the target monitoring frequency band; determine the type of the interference signal according to the distribution of the target window in the target monitoring frequency band, including: for any one of the target windows, if the target window covers the entire target monitoring frequency band, determine that the type of the interference signal corresponding to the target window is white noise interference; if the target window only covers part of the target monitoring frequency band, determine whether the target frequency band is included in the target window; if not, determine that the type of the interference signal corresponding to the target window is adjacent-frequency interference; if so, if the frequency band of the target window is exactly the same as the target frequency band, determine that the type of the interference signal corresponding to the target window is co-channel interference; if the frequency band of the target window is not exactly the same as the target frequency band, determine that the type of the interference signal corresponding to the target window is broadband interference.

2. The wireless signal intelligent sensing method according to claim 1, characterized in that: After determining the type of the interference signal according to the distribution of the target window in the target monitoring frequency band, the method further includes: According to the preset priority, one is selected from the frequency bands to be detected as the new target frequency band, and the step of determining the target monitoring frequency band according to the center frequency point and monitoring bandwidth of the target frequency band is returned to continue execution until all the frequency bands to be detected have been selected as the target frequency bands.

3. The wireless signal intelligent sensing method according to claim 1, characterized in that: The determining, according to the first power, whether an interference condition is met includes: If the first power is greater than a first threshold, or a signal-to-noise ratio determined based on the first power and the third power is less than a signal-to-noise ratio threshold, it is determined that the first power meets the interference condition; the third power is the power of the wireless signal in the target frequency band.

4. The wireless signal intelligent sensing method according to claim 1, characterized in that: The determining, according to the second power, whether there is an interference signal in the current sliding window includes: If the second power is greater than a second threshold, it is determined that the interference signal exists in the current sliding window.

5. A wireless signal intelligent sensing method, characterized in that: Applied to a wireless signal intelligent sensing system, the wireless signal intelligent sensing system is deployed in a target area, the wireless signal intelligent sensing system includes a plurality of wireless signal intelligent sensing devices, the wireless signal intelligent sensing devices are configured to execute the wireless signal intelligent sensing method according to any one of claims 1 to 4, the target area is divided into a plurality of grids, each of the grids is provided with a one-to-one corresponding wireless signal intelligent sensing device, and the wireless signal intelligent sensing method includes: Collecting detection information uploaded by each of the wireless signal intelligent sensing devices; the detection information includes the type of interference signal and the second power corresponding to the target window where the interference signal is located; For the interference signal of the same type, the wireless signal intelligent sensing device including the interference signal of the type in the uploaded detection information is determined as a target device, and the distance between the signal source of the interference signal of the type and each of the target devices is determined respectively according to the second power uploaded by at least three of the target devices; The position of the signal source is determined according to the distance between the signal source and each of the target devices.

6. The wireless signal intelligent sensing method according to claim 5 is characterized in that: The determining the position of the signal source according to the distance between the signal source and each of the target devices includes: For any one of the target devices, an auxiliary circle is generated with the location of the target device as the center and the distance between the target device and the signal source as the radius; The position of the signal source is determined according to the intersection points between the auxiliary circles.

7. A wireless signal intelligent sensing device, characterized in that: Applied to a wireless signal intelligent sensing device, the wireless signal intelligent sensing device includes an antenna, the antenna is used to collect wireless signals, and the wireless signal intelligent sensing device includes: An initialization module, used to determine a target monitoring frequency band according to a central frequency point of the target frequency band and a monitoring bandwidth; the monitoring bandwidth is greater than a width of the target frequency band; A first power determination module, used to determine a first power of the wireless signal in the target monitoring frequency band; A first judging module, configured to judge whether an interference condition is met according to the first power; A traversal module, used for traversing the target monitoring frequency band with a sliding window having a width as a step bandwidth when the interference condition is met; A second judgment module is used to determine the second power of the wireless signal in the sliding window at each sliding, and judge whether there is an interference signal in the current sliding window according to the second power, and if so, determine the current sliding window as a target window; A merging module, used for merging adjacent target windows; A type determination module is used to determine the type of the interference signal according to the distribution of the target window in the target monitoring frequency band; the determination of the type of the interference signal according to the distribution of the target window in the target monitoring frequency band includes: for any one of the target windows, if the target window covers the entire target monitoring frequency band, determining that the type of the interference signal corresponding to the target window is white noise interference; if the target window only covers part of the target monitoring frequency band, determining whether the target frequency band is included in the target window; if not, determining that the type of the interference signal corresponding to the target window is adjacent-frequency interference; if so, then when the frequency band of the target window is exactly the same as the target frequency band, determining that the type of the interference signal corresponding to the target window is co-channel interference; and when the frequency band of the target window is not exactly the same as the target frequency band, determining that the type of the interference signal corresponding to the target window is broadband interference.

8. A computer device, characterized in that: It includes one or more processors and a memory, wherein the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the one or more processors, the steps of the wireless signal intelligent sensing method described in any one of claims 1-4 or claims 5-6 are executed.

9. A storage medium, characterized in that: The storage medium stores computer-readable instructions, and when the computer-readable instructions are executed by one or more processors, the one or more processors execute the steps of the wireless signal intelligent sensing method according to any one of claims 1-4 or claims 5-6.

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