Time-domain adaptive burst signal detection method, device, system, equipment, medium and product

Abstract

The application provides a time domain adaptive burst signal detection method, device, system, equipment, medium and product, which comprises the following steps: performing radio frequency analog signal processing on a received radio signal to generate an analog intermediate frequency signal; performing digital signal processing on the analog intermediate frequency signal after sampling to generate baseband IQ data; performing autocorrelation accumulation and smoothing filtering on the baseband IQ data to calculate an adaptive burst detection threshold; and performing burst signal detection on the baseband IQ data by using the adaptive burst detection threshold. The application takes the actually sampled signal as prior information to calculate the adaptive burst detection threshold and thus completes the burst signal detection, so that the burr false alarm caused by the influence of environmental noise can be effectively avoided.

Description

Technical Field

[0001] This invention relates to the field of radio target monitoring technology, and more specifically, to a time-domain adaptive burst signal detection method, apparatus, system, equipment, medium, and product. Background Technology

[0002] A burst signal is a wireless communication signal radiated into space by the signal initiator within an extremely short period of time. The effective duration of a signal radiated in this way is extremely short, greatly reducing the probability of being detected or intercepted by a third party and improving the anti-interception capability of the communication system. Short-duration burst signals are increasingly widely used due to their anti-interception properties, and their real-time detection is of paramount importance in electromagnetic environment monitoring. However, the increasingly complex electromagnetic environment leads to more noise and interference in communication systems, making the effective detection of burst signals, which exhibit random energy distribution over time, increasingly difficult. For the detection and information recovery of burst signals, effective burst signal detection must first be performed, and the signal content within the signal's duration must be effectively received before signal parameter extraction, demodulation, and decoding can be performed.

[0003] Currently, commonly used signal detection methods include frequency domain fixed energy threshold detection, correlation detection, maximum likelihood estimation detection, and matched filtering. Frequency domain fixed energy threshold detection uses a fixed threshold to determine whether a signal within the frequency bandwidth is positive or negative; however, it is susceptible to channel and environmental variations, and fluctuations in the signal and background can easily increase the probability of false alarms. Correlation detection requires using a dedicated signal synchronization header or constructing a corresponding burst sequence for signal correlation detection; practical application has shown that this method suffers from false alarm spikes and low detection accuracy. Maximum likelihood estimation detection performs data detection by estimating noise power, but it is also susceptible to false alarms due to noise fluctuations caused by channel variations. Matched filtering is sensitive to carrier frequency offset, limiting its application scenarios, and requires dynamic threshold decision; setting the threshold without prior information can easily lead to false alarms and missed detections. Summary of the Invention

[0004] The present invention aims to provide a time-domain adaptive burst signal detection method, device, system, equipment, medium and product to solve the problem that current signal detection in complex electromagnetic environments is easily affected by electromagnetic background fluctuations, resulting in false detection and missed detection.

[0005] In a first aspect, the present invention provides a time-domain adaptive burst signal detection method, comprising: The received radio signals are processed using radio frequency analog signal processing to generate analog intermediate frequency signals; The analog intermediate frequency signal is sampled and then digital signal processed to generate baseband IQ data; Autocorrelation accumulation and smoothing filtering are performed on the baseband IQ data to calculate the adaptive burst detection threshold; Burst signal detection is performed on baseband IQ data using an adaptive burst detection threshold.

[0006] In a preferred embodiment, calculating the adaptive burst detection threshold includes: For the baseband IQ data after autocorrelation accumulation and smoothing filtering, its envelope is calculated in real time as the near-end threshold; The mean of the baseband IQ data after autocorrelation accumulation and smoothing filtering is calculated in real time and used as the far-end threshold. The near-end threshold and the far-end threshold are weighted and then used as the adaptive burst detection threshold.

[0007] In a preferred embodiment, the step of using an adaptive burst detection threshold to detect burst signals in baseband IQ data includes: Real-time calculation of baseband IQ data energy in the time domain; The energy of the baseband IQ data is compared with the adaptive burst detection threshold. For baseband IQ data with energy greater than the adaptive burst detection threshold, the recording time and energy are recorded. When the energy of the baseband IQ data is less than the adaptive burst detection threshold, the duration of the signal existence is calculated based on the recording time as the burst signal detection result.

[0008] In a second aspect, the present invention provides a time-domain adaptive burst signal detection device, comprising: The receiving channel is used to perform radio frequency analog signal processing on the received radio signals to generate analog intermediate frequency signals; The sampling module is used to sample analog intermediate frequency signals into digital signals; The preprocessing module is used to perform digital signal processing on the sampled digital signals to generate baseband IQ data; The threshold calculation module is used to perform autocorrelation accumulation and smoothing filtering on baseband IQ data, and calculate the adaptive burst detection threshold; The burst detection module is used to detect burst signals in baseband IQ data using an adaptive burst detection threshold.

[0009] In a preferred embodiment, the threshold calculation module includes: The envelope calculation module is used to calculate the envelope of the baseband IQ data after autocorrelation accumulation and smoothing filtering in real time as a near-end threshold. The mean calculation module is used to calculate the mean of the baseband IQ data after autocorrelation accumulation and smoothing filtering in real time as a far-end threshold. The weighting module is used to weight the near-end threshold and the far-end threshold and then use the weighted result as the adaptive burst detection threshold.

[0010] In a preferred embodiment, the burst detection module includes: The energy calculation module is used to calculate the baseband IQ data energy in the time domain in real time. The comparison and recording module is used to compare the energy of the baseband IQ data with the adaptive burst detection threshold. For baseband IQ data with energy greater than the adaptive burst detection threshold, the recording time and energy are used. When the energy of the baseband IQ data is less than the adaptive burst detection threshold, the duration of the signal existence is calculated based on the recording time as the burst signal detection result.

[0011] Thirdly, the present invention provides a radio monitoring system, comprising: a receiving antenna and the aforementioned time-domain adaptive burst signal detection device; The receiving antenna is used to receive radio signals; A time-domain adaptive burst signal detection device is used to detect burst signals in received radio signals.

[0012] Fourthly, the present invention provides an electronic device, comprising: At least one processor; and a memory communicatively connected to said at least one processor; The memory stores instructions that can be executed by the at least one processor, and the at least one processor executes the instructions stored in the memory to perform the above-described method.

[0013] Fifthly, the present invention provides a computer-readable storage medium for storing instructions that, when executed, cause the above-described method to be implemented.

[0014] In a sixth aspect, the present invention provides a computer program product that, when invoked by a computer, causes the computer to execute the above-described method.

[0015] In summary, the beneficial effects of this invention are: 1. High detection accuracy. Compared to traditional burst signal detection methods, this invention uses the intercepted signal (including electromagnetic background) as prior information for the adaptive burst detection threshold. This allows the calculated adaptive burst detection threshold to more accurately filter out the electromagnetic background and more accurately detect the incoming signal. Actual measurements show that this method has good adaptability for burst signals with a signal-to-noise ratio of 8dB or higher, achieving an effective detection probability of over 85%.

[0016] 2. Strong adaptability to different scenarios. This invention filters and amplifies the signal through the receiving channel. By performing autocorrelation accumulation and smoothing filtering on the real-time acquired signal, and calculating the envelope and continuous mean, the adaptive burst detection threshold is obtained through weighted averaging. Compared with traditional burst signal detection methods, this invention does not require any prior information other than the finished design of the radio monitoring system, and has a stronger adaptability to burst signal scenarios. Attached Figure Description

[0017] Figure 1 This is a flowchart of a time-domain adaptive burst signal detection method provided in an embodiment of the present invention.

[0018] Figure 2 This is an example test result diagram of a time-domain adaptive burst signal detection method provided in an embodiment of the present invention.

[0019] Figure 3 This is a schematic diagram of a time-domain adaptive burst signal detection device and a radio monitoring system provided in an embodiment of the present invention.

[0020] Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0022] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0023] The present invention provides a time-domain adaptive burst signal detection method, the design principle of which is as follows: The received radio signal undergoes radio frequency analog signal processing, including analog signal frequency conversion, filtering, and amplification, to generate an analog intermediate frequency (IF) signal. The analog IF signal is then sampled and subjected to digital signal processing, including digital frequency conversion, filtering, and amplification, to generate baseband IQ data, represented as: (1) in, For signal, It is noise.

[0024] The variance of baseband IQ data is expressed as: (2) The autocorrelation accumulation of baseband IQ data is expressed as: (3) The variance of the baseband IQ data after autocorrelation accumulation is expressed as: (4) (5) Based on the non-correlation of noise in the time domain, equation (5) can be simplified to: (6) Considering the impact of noise on the signal, the energy distribution of burst signals is random over time. Therefore, when detecting burst signals, the expected threshold increases with the presence of the signal and is causally related to the burst of the signal.

[0025] If we use the envelope of a signal as the real-time criterion for determining whether a signal exists, according to the definition of envelope: (7) in, This represents the envelope of the baseband IQ data. Indicates the maximum envelope coefficient; The embodiments of the present invention are designed with (In practice, it can be set to any value as needed), and the envelope of the real-time received signal is calculated in the time domain.

[0026] The expected value of baseband IQ data can be expressed as: (8) in, This represents the probability of a sudden signal occurring. According to mathematical derivation, when... When the expected value of the baseband IQ data is expressed by the mean, the mean of the sampled values ​​over a certain period of time can be used to express the expected value of the received signal over a certain period of time.

[0027] According to the constant false alarm rate (CFAR) theory, when the received signal follows a certain probability distribution, there is a corresponding adaptive burst detection threshold that maintains a constant false alarm probability when detecting the received signal. The detection threshold can be expressed as: (9) in, This represents the nominal factor for the adaptive burst detection threshold. This indicates the amount of burst signal detected. Indicates the envelope. This represents the expected value, which in this embodiment of the invention is also the mean. , These represent the weighting factors for the envelope and expectation, respectively, and can be set to any value according to the actual situation and needs.

[0028] As can be seen from the calculation process of constant false alarm rate (CFAR), its threshold calculation method can be determined by the false alarm probability and power level, for baseband IQ data. The power level can be expressed as: (10) Based on the above design principles, such as Figure 1 As shown in the figure, an embodiment of the present invention provides a time-domain adaptive burst signal detection method, which includes the following steps: S100 performs radio frequency analog signal processing on the received radio signals, including analog signal frequency conversion, filtering and amplification, to generate an analog intermediate frequency signal; wherein, the radio signal is the captured target incoming wave radiation signal, which can be realized by a receiving antenna, which converts the electromagnetic wave energy induction, amplitude, arrival time and other information propagating in the air into a radio signal.

[0029] S200 performs digital signal processing on the analog intermediate frequency signal after sampling, including digital frequency conversion, filtering and amplification, to generate baseband IQ data; among which, sampling can be carried out by AD sampling to convert the analog intermediate frequency signal into a digital signal for subsequent processing.

[0030] S300 performs autocorrelation accumulation and smoothing filtering on the baseband IQ data to calculate the adaptive burst detection threshold. Due to signal fluctuations and external environmental influences, especially in areas with dense communication signals, noise distribution often exhibits random fluctuations in the energy spectrum. For burst signal detection, the spikes caused by noise fluctuations are often mistaken for weak burst signals and detected. However, these spikes are uncorrelated in the time domain. Therefore, in this embodiment, smoothing filtering effectively weakens these spikes and improves signal detection accuracy. Smoothing filtering compresses the energy of the original signal towards the desired value in the time domain. The more times the smoothing filter is applied, the smaller the variance of the baseband IQ data in the time domain. The example in this embodiment uses 128 smoothing filters, but this number can be set to any number depending on the actual situation and needs.

[0031] After performing autocorrelation accumulation and smoothing filtering on the baseband IQ data, the calculation of the adaptive burst detection threshold includes: For the baseband IQ data after autocorrelation accumulation and smoothing filtering, the envelope is calculated in real time using Equation (7) as the near-end threshold; The mean of the baseband IQ data after autocorrelation accumulation and smoothing filtering is calculated in real time and used as the far-end threshold. The near-end threshold and the far-end threshold are weighted using Equation (9) and then used as the adaptive burst detection threshold.

[0032] The S400 utilizes an adaptive burst detection threshold to detect burst signals in baseband IQ data. Specifically, it includes: The baseband IQ data energy is calculated in real time in the time domain. The baseband IQ data energy is compared with the adaptive burst detection threshold. The portion exceeding the adaptive burst detection threshold is used as evidence of signal presence, and the portion below the adaptive burst detection threshold is used as evidence of signal absence. Therefore, for baseband IQ data recording time and energy parameters with energy greater than the adaptive burst detection threshold, when the baseband IQ data energy is less than the adaptive burst detection threshold, the signal presence duration is calculated based on the recording time as the burst signal detection result.

[0033] like Figure 2 An example is shown. Using a time-domain adaptive burst signal detection method provided by an embodiment of the present invention, the burst signal detection performance under different energy distributions and noise influences is analyzed. Figure 2 This diagram illustrates the distribution of detection accuracy (10%~100%) for incoming signals at different signal-to-noise ratios (SNR) (1~12dB). After testing and verification with actual signals, the method of this invention demonstrates good adaptability to burst signals with an SNR of 8dB or higher, achieving an effective detection probability of over 85%, making it suitable for engineering applications.

[0034] Based on the same technological concept, such as Figure 3 As shown, this embodiment of the invention also provides a time-domain adaptive burst signal detection device, comprising: The receiving channel is used to perform radio frequency analog signal processing on the received radio signals to generate analog intermediate frequency signals; The sampling module is used to sample analog intermediate frequency signals into digital signals; The preprocessing module is used to perform digital signal processing on the sampled digital signals to generate baseband IQ data; The threshold calculation module is used to perform autocorrelation accumulation and smoothing filtering on baseband IQ data, and calculate the adaptive burst detection threshold; The burst detection module is used to detect burst signals in baseband IQ data using an adaptive burst detection threshold.

[0035] Furthermore, the threshold calculation module includes: The envelope calculation module is used to calculate the envelope of the baseband IQ data after autocorrelation accumulation and smoothing filtering in real time as a near-end threshold. The mean calculation module is used to calculate the mean of the baseband IQ data after autocorrelation accumulation and smoothing filtering in real time as a far-end threshold. The weighting module is used to weight the near-end threshold and the far-end threshold and then use the weighted result as the adaptive burst detection threshold.

[0036] The burst detection module includes: The energy calculation module is used to calculate the baseband IQ data energy in the time domain in real time. The comparison and recording module is used to compare the energy of the baseband IQ data with the adaptive burst detection threshold. For baseband IQ data with energy greater than the adaptive burst detection threshold, the recording time and energy are used. When the energy of the baseband IQ data is less than the adaptive burst detection threshold, the duration of the signal existence is calculated based on the recording time as the burst signal detection result.

[0037] The working principles of each functional module in the above-mentioned device can be referred to the description in the aforementioned design principles and method embodiments, and will not be repeated here.

[0038] Based on the same technical concept, embodiments of the present invention also provide a radio monitoring system, including: a receiving antenna and the aforementioned time-domain adaptive burst signal detection device; The receiving antenna is used to receive radio signals; The time-domain adaptive burst signal detection device is used to detect burst signals in received radio signals. Its specific working principle can be referred to the description in the aforementioned design principles and method embodiments, and will not be repeated here.

[0039] Based on the same technical concept, embodiments of the present invention also provide an electronic device that can implement the time-domain adaptive burst signal detection method flow provided in the above embodiments of the present invention. In one embodiment, the electronic device can be a server, a terminal device, or other electronic devices. Figure 4 As shown, the electronic device may include: At least one processor and a memory connected to the at least one processor. In this embodiment of the invention, the specific connection medium between the processor and the memory is not limited. Figure 4 The example used is the connection between the processor and memory via a bus. The bus... Figure 4 The connections between other components are indicated by thick lines and are for illustrative purposes only, not as limiting information. Buses can be divided into address buses, data buses, control buses, etc., but for ease of representation, [the specific bus type is not shown here]. Figure 4 The processor is represented by a single thick line, but this does not imply that there is only one bus or one type of bus. Alternatively, a processor can also be called a controller; there are no restrictions on the name.

[0040] In this embodiment of the invention, the memory stores instructions that can be executed by at least one processor. By executing the instructions stored in the memory, at least one processor can execute a time-domain adaptive burst signal detection method as described above.

[0041] The processor is the control center of the device. It can connect to various parts of the control device through various interfaces and lines. By running or executing instructions stored in memory and calling data stored in memory, it can monitor the device's various functions and process data, thereby enabling overall monitoring of the device.

[0042] In an alternative design, the processor may include one or more processing units. The processor may integrate an application processor and a modem processor, wherein the application processor primarily handles the operating system, user interface, and applications, while the modem processor primarily handles wireless communication. It is understood that the modem processor may also not be integrated into the processor. In some embodiments, the processor and memory may be implemented on the same chip; in some embodiments, they may also be implemented separately on separate chips.

[0043] The processor can be a general-purpose processor, such as a CPU, digital signal processor, application-specific integrated circuit, field-programmable gate array or other programmable logic device, discrete gate or transistor logic device, or discrete hardware component, capable of implementing or executing the methods, steps, and logic block diagrams disclosed in the embodiments of this invention. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the time-domain adaptive burst signal detection method disclosed in the embodiments of this invention can be directly manifested as being executed by a hardware processor, or executed by a combination of hardware and software modules within the processor.

[0044] Memory, as a non-volatile computer-readable storage medium, can be used to store non-volatile software programs, non-volatile computer-executable programs, and modules. Memory can include at least one type of storage medium, such as flash memory, hard disk, multimedia card, card-type memory, random access memory (RAM), static random access memory (SRAM), programmable read-only memory (PROM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), magnetic memory, magnetic disk, optical disk, etc. Memory is any other medium capable of carrying or storing desired program code in the form of instructions or data structures, and accessible by a computer, but is not limited thereto. In embodiments of the present invention, memory can also be a circuit or any other device capable of implementing storage functions, used to store program instructions and / or data.

[0045] By designing and programming the processor, the code corresponding to the time-domain adaptive burst signal detection method described in the foregoing embodiments can be embedded into the chip, enabling the chip to execute the steps of the method described in the foregoing embodiments during runtime. How to design and program the processor is a technique well-known to those skilled in the art and will not be elaborated upon here.

[0046] Based on the same inventive concept, embodiments of the present invention also provide a storage medium storing computer instructions that, when executed on a computer, cause the computer to perform a time-domain adaptive burst signal detection method described above.

[0047] In some alternative embodiments, the present invention also provides a method for detecting time-domain adaptive burst signals that can also be implemented as a program product comprising program code that, when the program product is run on a device, causes the control device to perform the steps in a method for detecting time-domain adaptive burst signals according to various exemplary embodiments of the present invention as described above.

[0048] It should be noted that although several units or sub-units of the apparatus have been mentioned in the detailed description above, this division is merely exemplary and not mandatory. In fact, according to embodiments of the invention, the features and functions of two or more units described above can be embodied in one unit. Conversely, the features and functions of one unit described above can be further divided and embodied by multiple units. Furthermore, although the operation of the method of the invention is described in a specific order in the drawings, this does not require or imply that these operations must be performed in that specific order, or that all the operations shown must be performed to achieve the desired result. Additionally or alternatively, certain steps may be omitted, multiple steps may be combined into one step, and / or one step may be broken down into multiple steps.

[0049] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0050] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a server, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0051] Program code for performing the operations of this invention can be written using any combination of one or more programming languages, including object-oriented programming languages ​​such as Java and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on the user's computing device, partially on the user's device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0052] In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0053] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0054] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0055] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A time-domain adaptive burst signal detection method, characterized in that, include: The received radio signals are processed using radio frequency analog signal processing to generate analog intermediate frequency signals; The analog intermediate frequency signal is sampled and then digital signal processed to generate baseband IQ data; Autocorrelation accumulation and smoothing filtering are performed on the baseband IQ data to calculate the adaptive burst detection threshold; Burst signal detection is performed on baseband IQ data using an adaptive burst detection threshold.

2. The time-domain adaptive burst signal detection method according to claim 1, characterized in that, The calculation of the adaptive burst detection threshold includes: For the baseband IQ data after autocorrelation accumulation and smoothing filtering, its envelope is calculated in real time as the near-end threshold; The mean of the baseband IQ data after autocorrelation accumulation and smoothing filtering is calculated in real time and used as the far-end threshold. The near-end threshold and the far-end threshold are weighted and then used as the adaptive burst detection threshold.

3. The time-domain adaptive burst signal detection method according to claim 1, characterized in that, The method of using an adaptive burst detection threshold to detect burst signals in baseband IQ data includes: Real-time calculation of baseband IQ data energy in the time domain; The energy of the baseband IQ data is compared with the adaptive burst detection threshold. For baseband IQ data with energy greater than the adaptive burst detection threshold, the recording time and energy are recorded. When the energy of the baseband IQ data is less than the adaptive burst detection threshold, the duration of the signal existence is calculated based on the recording time as the burst signal detection result.

4. A time-domain adaptive burst signal detection device, characterized in that, include: The receiving channel is used to perform radio frequency analog signal processing on the received radio signals to generate analog intermediate frequency signals; The sampling module is used to sample analog intermediate frequency signals into digital signals; The preprocessing module is used to perform digital signal processing on the sampled digital signals to generate baseband IQ data; The threshold calculation module is used to perform autocorrelation accumulation and smoothing filtering on baseband IQ data, and calculate the adaptive burst detection threshold; The burst detection module is used to detect burst signals in baseband IQ data using an adaptive burst detection threshold.

5. The time-domain adaptive burst signal detection device according to claim 4, characterized in that, The threshold calculation module includes: The envelope calculation module is used to calculate the envelope of the baseband IQ data after autocorrelation accumulation and smoothing filtering in real time as a near-end threshold. The mean calculation module is used to calculate the mean of the baseband IQ data after autocorrelation accumulation and smoothing filtering in real time as a far-end threshold. The weighting module is used to weight the near-end threshold and the far-end threshold and then use the weighted result as the adaptive burst detection threshold.

6. The time-domain adaptive burst signal detection device according to claim 4, characterized in that, The burst detection module includes: The energy calculation module is used to calculate the baseband IQ data energy in the time domain in real time. The comparison and recording module is used to compare the energy of the baseband IQ data with the adaptive burst detection threshold. For baseband IQ data with energy greater than the adaptive burst detection threshold, the recording time and energy are used. When the energy of the baseband IQ data is less than the adaptive burst detection threshold, the duration of the signal existence is calculated based on the recording time as the burst signal detection result.

7. A radio monitoring system, characterized in that, include: The receiving antenna and the time-domain adaptive burst signal detection device as described in any one of claims 4-6; The receiving antenna is used to receive radio signals; A time-domain adaptive burst signal detection device is used to detect burst signals in received radio signals.

8. An electronic device, characterized in that, include: At least one processor; and a memory communicatively connected to the at least one processor; The memory stores instructions executable by the at least one processor, which executes the instructions stored in the memory to perform the method as described in any one of claims 1-3.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium is used to store instructions that, when executed, cause the method as described in any one of claims 1-3 to be implemented.

10. A computer program product, characterized in that, When the computer program product is invoked by a computer, it causes the computer to perform the method as described in any one of claims 1-3.

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