Signal detection and identification method and system

Abstract

The invention discloses a signal detection and identification method. The method comprises the following steps: S1, determining a specific specification of a signal to be detected and identified; s2, extracting signal features of the signal with the specific specification; s3, distinguishing signal bandwidths and signal types on frequency points based on the signal features; s4, positioning an accurate burst initial position based on the instantaneous phase curve of the signal or the unique code information of the signal; accurately determining each burst end position based on signal demodulation or based on a frame structure of the signal; and S5, counting repeatability characteristics of the burst initial position, and calculating frequency offset and / or signal-to-noise ratio information of the signal based on the repeatability characteristics. The invention further discloses a corresponding system, electronic equipment and a computer readable storage medium, the target digital signal can be detected under the condition that noise packets and other interferences exist, the precision is within one symbol error of 98% or above, and the modulation and symbol rate and related information characteristics of the target signal are extracted.

Description

Technical Field

[0001] The present invention relates to the technical field of signal detection and recognition and noise suppression, and in particular to a signal detection and recognition method and system. Background Art

[0002] There are a large number of noise packets in the target signal, including stationary noise and non-stationary noise. Among them, stationary noise is noise whose statistical characteristics remain unchanged in time. The mean and variance of stationary noise are constant at any time. Non-stationary noise is noise whose statistical characteristics change in time. The mean, variance or autocorrelation function of non-stationary noise may change in time. Stationary noise remains stable in the time domain and is easier to handle. Non-stationary noise requires more complex methods for modeling and processing. The traditional general method of signal detection and identification is to calculate the start and end positions of the burst through spectrum conversion and accumulation operations in the frequency domain, and then obtain the modulation information by identifying the constellation diagram of the effective information, and calculate the symbol rate by accumulating the energy at the symbol moment. However, the above method has the technical defects of large amount of calculation and the accuracy of the calculated burst start and end positions does not meet the business requirements, which leads to the identification of interference as a signal, causing false detection, and then causing errors in subsequent information extraction.

[0003] In addition, the commonly used frequency offset estimation methods currently have problems such as limited signal phase values, invalid estimation values ​​when the phase value exceeds π, and a small frequency offset estimation range when the frequency synchronization symbol length is short, which limits the performance of the system. For signals with a fixed frame structure and a small and discontinuous number of frequency synchronization symbols, the traditional method of estimating frequency offset using conjugate multiplication of frequency synchronization symbols will result in a too small frequency offset estimation range. Once the range is exceeded, the frequency offset estimation method will fail, limiting the performance of the system. Summary of the invention

[0004] In order to solve the problems existing in the prior art, the present invention develops a signal detection and identification method and system, which detects the target digital signal in the presence of noise packets and other interferences, with an accuracy of more than 98% within one symbol error, and extracts the modulation and symbol rate of the target signal, related information and other features. Since the specifications of the required detection signal are known, the present invention specifically extracts specific signal features. First, the signal bandwidth and signal type at the frequency point are distinguished according to the more obvious frequency domain characteristics of the signal; the signal starting point position is accurately determined through the instantaneous phase curve of the signal or the unique code information of the signal; the end position of each burst is accurately determined by signal demodulation or according to the frame structure of the signal; some signals with frame structure determine the position of the frame header and each burst in the wireless frame, and then extract relevant information according to the frame structure indicated by the special field of the signal; some signals without frame structure calculate relevant information by demodulating the information of the corresponding bit position; the type of signal with high repeatability at the starting position of the signal calculates the frequency deviation and signal-to-noise ratio information of the signal according to the frequency domain spectrum of the signal; the remaining types directly calculate the frequency deviation by calculating the maximum point of the frequency domain correlation value through the correlation characteristics.

[0005] In one aspect, the present invention provides a signal detection and identification method, comprising:

[0006] S1, determining specific specifications of the signal to be detected and identified;

[0007] S2, extracting signal features of the signal having the specific specification;

[0008] S3, distinguishing the signal bandwidth and signal type at the frequency point based on the signal characteristics;

[0009] S4, locating the precise burst start position based on the instantaneous phase curve of the signal or the unique code information of the signal; accurately determining each burst end position based on signal demodulation or based on the frame structure of the signal;

[0010] S5, counting the repetitive characteristics of the burst start position, and calculating the frequency deviation and / or signal-to-noise ratio information of the signal based on the repetitive characteristics.

[0011] As a preferred implementation, the signal characteristics are frequency domain characteristics of the signal.

[0012] As a preferred implementation, the frame structure of the signal includes part of the signal with a frame structure and part of the signal without a frame structure.

[0013] As a preferred implementation, the accurate burst start position positioning based on the instantaneous phase curve of the signal or the unique code information of the signal includes:

[0014] For some continuous phase modulated signals, the phase information changes with time, and the instantaneous phase changes very little, while the noise part has no phase information at all. By calculating the instantaneous phase information of the input data, the continuous phase modulated signal and the noise can be well distinguished. However, for discontinuous phase signals, the effect of using instantaneous phase to present is not good, so the unique code information is used. By demodulating multiple collected signals, sorting out their common fields or finding some standard protocols to obtain the unique code of the signal, and then generating the corresponding signal based on the unique code found, and performing correlation processing with the received signal data, the precise position of the unique code is obtained, and then the starting position of the signal is deduced based on the position of the unique code in the signal structure.

[0015] As a preferred implementation, the accurately determining the end position of each burst based on the frame structure of the signal includes:

[0016] For the signal having a frame structure, first determine the frame header of the signal and the position of each burst in the wireless frame; then extract relevant information for accurately determining the end position of each burst according to the frame structure indicated by the special field of the signal;

[0017] For the partially frameless signal, firstly, information of corresponding bit positions is acquired through demodulation; then, relevant information for accurately determining the end position of each burst is calculated according to the information of corresponding bit positions.

[0018] As a preferred implementation, for the signal having a frame structure, the accurate determination of each burst end position based on the frame structure of the signal may also be:

[0019] First, the symbol of the corresponding bit position is obtained by demodulation;

[0020] Based on the fact that the burst start position is accurate, the relevant information of each burst end position is accurately determined based on the sign of the corresponding bit position.

[0021] As a preferred implementation, S5 includes:

[0022] S51, for the signal whose burst start position repeatability exceeds a predetermined threshold, calculating the frequency deviation and signal-to-noise ratio information of the signal according to the frequency domain spectrum of the signal;

[0023] S52: For the remaining signals, the maximum point of the frequency domain correlation value is calculated through the correlation characteristics, and the frequency deviation of the signal is calculated according to the maximum point of the frequency domain correlation value.

[0024] A second aspect of the present invention is to provide a signal detection and recognition system for implementing the method of the first aspect, comprising:

[0025] A signal specification determination module (101), used to determine the specific specifications of the signal to be detected and identified;

[0026] A signal feature extraction module (102), used for extracting signal features of a signal having the specific specification;

[0027] A bandwidth and type determination module (103), used to distinguish the signal bandwidth and signal type at the frequency point based on the signal characteristics;

[0028] A burst start and end position determination module (104) is used to locate the precise burst start position based on the instantaneous phase curve of the signal or the unique code information of the signal; and to accurately determine each burst end position based on signal demodulation or based on the frame structure of the signal;

[0029] The signal feature recognition module (105) is used to count the repetitive features of the burst start position and calculate the frequency deviation and / or signal-to-noise ratio information of the signal based on the repetitive features.

[0030] A third aspect of the present invention provides an electronic device, comprising a processor and a memory, wherein the memory stores a plurality of instructions, and the processor is configured to read the instructions and execute the method described in the first aspect.

[0031] A fourth aspect of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores a plurality of instructions, and the plurality of instructions can be read by a processor and execute the method described in the first aspect.

[0032] The method, system and electronic device provided by the present invention have the following beneficial effects:

[0033] The present invention extracts specific signal features in a targeted manner. First, the signal bandwidth and signal type at the frequency point are distinguished according to the more obvious frequency domain characteristics of the signal; the signal starting point position is accurately determined through the instantaneous phase curve of the signal or the unique code information of the signal; the end position of each burst is accurately determined by signal demodulation or according to the frame structure of the signal; for some signals with frame structure, the frame header and the position of each burst in the wireless frame are determined, and then the relevant information is extracted according to the frame structure indicated by the special field of the signal; for some signals without frame structure, the relevant information is calculated by demodulating the information of the corresponding bit position; for the type signal with high repeatability of the signal starting position, the frequency deviation and signal-to-noise ratio information of the signal are calculated according to the frequency domain spectrum of the signal; the remaining types directly calculate the frequency deviation by calculating the maximum point of the frequency domain correlation value through the correlation characteristics, and detect the target digital signal in the presence of noise packets and other interferences, with an accuracy of more than 98% within one symbol error, and extract the modulation and symbol rate of the target signal, related information and other characteristics. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 The figure is a flow chart of the signal detection and identification method described in the present invention.

[0035] Figure 2 Schematic diagram of the system architecture of the signal detection and identification method described in the present invention.

[0036] Figure 3 (a)- Figure 3 (c) is a time-frequency diagram of a signal of the time division multiplexing described in the present invention.

[0037] Figure 4 (a)- Figure 4 (b) is a schematic diagram of the result of starting position detection using unique code information as described in the present invention.

[0038] Figure 5 The figure is a schematic diagram of the structure of the electronic device described in the present invention. DETAILED DESCRIPTION

[0039] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0040] Embodiment 1

[0041] like Figure 1 As shown, this embodiment provides a signal detection and identification method, including:

[0042] S1, determining specific specifications of the signal to be detected and identified;

[0043] S2, extracting signal features of the signal having the specific specification;

[0044] S3, distinguishing the signal bandwidth and signal type at the frequency point based on the signal characteristics;

[0045] The signal bandwidth can be distinguished by the signal's cumulative spectrum characteristics, which is used for subsequent signal phase characteristic detection and filter bandwidth selection in unique code correlation detection, which is conducive to removing signal interference. The modulation type of the signal can be distinguished by the signal's N-squared spectrum characteristics and the differential high-order characteristics of the delayed conjugate. In part, the specific signal system can be identified by a priori signal and a known signal sample library can be retrieved. By distinguishing the specific type of the signal, a better detection method can be selected according to the type. Signals of known systems can be directly correlated with unique codes to obtain the most accurate results; continuous phase type signals can be detected by phase characteristics, and the operation speed is faster; the remaining part is detected and classified by recording specific spectrum characteristics.

[0046] S4, locating the precise burst start position based on the instantaneous phase curve of the signal or the unique code information of the signal; accurately determining each burst end position based on signal demodulation or based on the frame structure of the signal;

[0047] In this embodiment, S4 includes: demodulating multiple collected signals, sorting out their common fields or finding a unique code of a signal obtained by a partial standard protocol; then generating a corresponding signal based on the found unique code, and performing correlation processing with the received signal data.

[0048] S5, counting the repetitive characteristics of the burst start position, and calculating the frequency deviation and / or signal-to-noise ratio information of the signal based on the repetitive characteristics.

[0049] As a preferred implementation, the signal characteristics are frequency domain characteristics of the signal.

[0050] As a preferred implementation, the frame structure of the signal includes part of the signal with a frame structure and part of the signal without a frame structure.

[0051] As a preferred implementation, the accurate burst start position positioning based on the instantaneous phase curve of the signal or the unique code information of the signal includes:

[0052] For some continuous phase modulated signals, the phase information changes with time, and the instantaneous phase changes very little, while the noise part has no phase information at all. By calculating the instantaneous phase information of the input data, the continuous phase modulated signal and the noise can be well distinguished. However, for discontinuous phase signals, the effect of using instantaneous phase to present is not good, so the unique code information is used. By demodulating multiple collected signals, sorting out their common fields or finding some standard protocols to obtain the unique code of the signal, and then generating the corresponding signal based on the unique code found, and performing correlation processing with the received signal data, the precise position of the unique code is obtained, and then the starting position of the signal is deduced based on the position of the unique code in the signal structure.

[0053] As a preferred implementation, the accurately determining the end position of each burst based on the frame structure of the signal includes:

[0054] For the signal having a frame structure, first determine the frame header of the signal and the position of each burst in the wireless frame; then extract relevant information for accurately determining the end position of each burst according to the frame structure indicated by the special field of the signal;

[0055] For the partially frameless signal, firstly, information of corresponding bit positions is acquired through demodulation; then, relevant information for accurately determining the end position of each burst is calculated according to the information of corresponding bit positions.

[0056] As a preferred implementation, for the signal having a frame structure, the accurate determination of each burst end position based on the frame structure of the signal may also be:

[0057] First, the symbol of the corresponding bit position is obtained by demodulation;

[0058] Based on the fact that the burst start position is accurate, the relevant information of each burst end position is accurately determined based on the sign of the corresponding bit position.

[0059] As a preferred implementation, S5 includes:

[0060] S51, for the signal whose burst start position repeatability exceeds a predetermined threshold, calculating the frequency deviation and signal-to-noise ratio information of the signal according to the frequency domain spectrum of the signal;

[0061] S52: For the remaining signals, the maximum point of the frequency domain correlation value is calculated through the correlation characteristics, and the frequency deviation of the signal is calculated according to the maximum point of the frequency domain correlation value.

[0062] Embodiment 2

[0063] like Figure 2 As shown, this embodiment provides a signal detection and identification system, which is used to implement the method of embodiment 1, including:

[0064] A signal specification determination module 101, used to determine a specific specification of the signal to be detected and identified;

[0065] A signal feature extraction module 102, used to extract signal features of a signal having the specific specification;

[0066] A bandwidth and type determination module 103, configured to distinguish the signal bandwidth and signal type at a frequency point based on the signal characteristics;

[0067] The burst start and end position determination module 104 is used to locate the precise burst start position based on the instantaneous phase curve of the signal or the unique code information of the signal; and to accurately determine each burst end position based on signal demodulation or based on the frame structure of the signal;

[0068] The signal feature recognition module 105 is used to count the repetitive features of the burst start position and calculate the frequency deviation and / or signal-to-noise ratio information of the signal based on the repetitive features.

[0069] Application Examples

[0070] Detect a certain time-division multiplexed signal:

[0071] The time-division multiplexed signal is divided into fixed-length fields according to the signal rules. There are two types: frame header field and user field. There are multiple fields in a wireless frame. The frame starts with the frame header, and the subsequent fields are user fields. The frame header appears fixedly, and the user field can be filled or empty according to the needs of the user transmitting the signal. Figure 3 (a)- Figure 3 (c) shows the time-frequency diagram of a time-division multiplexed signal.

[0072] There are two types of unique codes, namely the frame header field and the user field. The unique codes of the two fields are then used to perform signal correlation for subsequent signal detection. The detection results of the starting position obtained are as follows: Figure 4 (a)- Figure 4 (b) as shown.

[0073] The present invention also provides a memory storing a plurality of instructions, wherein the instructions are used to implement the method as in the first embodiment.

[0074] like Figure 5 As shown, the present invention also provides an electronic device, including a processor 301 and a memory 302 connected to the processor 301, the memory 302 stores a plurality of instructions, and the instructions can be loaded and executed by the processor so that the processor can execute the method as in the first embodiment.

[0075] Although preferred embodiments of the present invention have been described, additional changes and modifications may be made to these embodiments by those skilled in the art once the basic inventive concepts are known. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention. Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A signal detection and identification method, characterized in that: include: S1, determining specific specifications of the signal to be detected and identified; S2, extracting signal features of the signal having the specific specification; S3, distinguishing the signal bandwidth and signal type at the frequency point based on the signal characteristics; S4, locating the precise burst start position based on the instantaneous phase curve of the signal or the unique code information of the signal; accurately determining each burst end position based on signal demodulation or based on the frame structure of the signal; S5, counting the repetitive characteristics of the burst start position, and calculating the frequency deviation and / or signal-to-noise ratio information of the signal based on the repetitive characteristics.

2. A signal detection and identification method according to claim 1, characterized in that: The signal characteristics are frequency domain characteristics of the signal; the frame structure of the signal includes part of the signal with a frame structure and part of the signal without a frame structure.

3. A signal detection and identification method according to claim 2, characterized in that: The S3 includes: The signal bandwidth is distinguished by the signal cumulative spectrum characteristics, which is used for subsequent signal phase characteristic detection and filter bandwidth selection in unique code correlation detection; The modulation type of the signal is distinguished by the N-squared spectrum characteristics of the signal and the differential high-order characteristics of the delayed conjugate. The specific signal system is partially identified by a priori signal segment, and a known signal sample library is retrieved; By distinguishing the specific types of signals, a better detection method is selected according to the type, including: signals of known systems are directly detected through unique code correlation; signals of continuous phase type are detected through phase characteristics; the remaining parts are detected and classified by recording specific spectrum characteristics.

4. A signal detection and identification method according to claim 3, characterized in that: The S4 includes: For partially continuous phase modulated signals, the phase information changes with time, and the instantaneous phase changes very little, while the noise part has no phase information at all. The continuous phase modulated signal and the noise are distinguished by calculating the instantaneous phase information of the input data. For discontinuous phase signals, unique code information is used, and multiple collected signals are demodulated to sort out their common fields or find some standard protocols to obtain the unique code of the signal. Then, the corresponding signal is generated according to the obtained unique code, and the correlation processing is performed with the received signal data to obtain the precise position of the unique code. Then, according to the position of the unique code in the signal structure, the burst start position of the signal is inferred.

5. A signal detection and identification method according to claim 4, characterized in that: The accurate determination of each burst end position based on the signal frame structure includes: For the signal having a frame structure, first determine the frame header of the signal and the position of each burst in the wireless frame; then extract relevant information for accurately determining the end position of each burst according to the frame structure indicated by the special field of the signal; For the partially frameless signal, firstly, information of corresponding bit positions is acquired through demodulation; then, relevant information for accurately determining the end position of each burst is calculated according to the information of corresponding bit positions.

6. A signal detection and identification method according to claim 5, characterized in that: For the signal having a frame structure, the method of accurately determining the end position of each burst based on the frame structure of the signal may also be: First, the symbol of the corresponding bit position is obtained by demodulation; Based on the fact that the burst start position is accurate, the relevant information of each burst end position is accurately determined based on the sign of the corresponding bit position.

7. A signal detection and identification method according to claim 6, characterized in that: The S5 includes: S51, for the signal whose burst start position repeatability exceeds a predetermined threshold, calculating the frequency deviation and signal-to-noise ratio information of the signal according to the frequency domain spectrum of the signal; S52: For the remaining signals, the maximum point of the frequency domain correlation value is calculated through the correlation characteristics, and the frequency deviation of the signal is calculated according to the maximum point of the frequency domain correlation value.

8. A signal detection and recognition system, used to implement the method according to any one of claims 1 to 7, characterized in that: include: A signal specification determination module (101), used to determine the specific specifications of the signal to be detected and identified; A signal feature extraction module (102), used for extracting signal features of a signal having the specific specification; A bandwidth and type determination module (103), used to distinguish the signal bandwidth and signal type at the frequency point based on the signal characteristics; A burst start and end position determination module (104) is used to locate the precise burst start position based on the instantaneous phase curve of the signal or the unique code information of the signal; and to accurately determine each burst end position based on signal demodulation or based on the frame structure of the signal; The signal feature recognition module (105) is used to count the repetitive features of the burst start position and calculate the frequency deviation and / or signal-to-noise ratio information of the signal based on the repetitive features.

9. An electronic device, characterized in that: The method comprises a processor and a memory, wherein the memory stores a plurality of instructions, and the processor is used to read the instructions and execute the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a plurality of instructions, and the plurality of instructions can be read by a processor to execute the method according to any one of claims 1 to 7.

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