A method for sorting and identifying Orthogonal Frequency Division Multiplexing (OFDM) signals

Abstract

An orthogonal frequency division multiplexing (OFDM) signal sorting and identification method is disclosed. This method calculates a detection threshold based on digitally channelized data in the absence of a signal. The amplitude of the digitally channelized data is accumulated and threshold detection is performed to obtain pulse descriptors for each channel. Phase difference clustering is used to fuse the pulse descriptors between channels, classifying pulse descriptors belonging to the same OFDM radiation source to form a pulse pool descriptor for that source. The time-domain, frequency-domain, and spatial-domain parameters of the OFDM signal are obtained from the pulse pool descriptor. This invention enables rapid and accurate sorting and identification of OFDM signals in the time, spatial, and frequency domains.

Description

Technical Field

[0001] This invention relates to the field of communication signal sorting and identification, and in particular to an orthogonal frequency division multiplexing (OFDM) signal sorting and identification method. Background Technology

[0002] A recent research report from Markets and Markets, the world's second-largest market research firm, shows that the global counter-drone market is projected to grow from $499 million in 2018 to $2.276 billion by 2024, representing an annual growth rate of 28.8%. The increasing number of drones and the frequent occurrence of unauthorized drone security vulnerabilities are the main drivers of this growth. With the widespread use of drones, numerous unauthorized drone flights have occurred overseas. In contrast, China lacks manufacturers of large-scale equipment specifically designed for monitoring unauthorized civilian drone flights. Monitoring and management of consumer-grade civilian drones are minimal, and most counter-drone companies focus on drone interception equipment. Therefore, detecting drone signals is becoming increasingly important. Drones often use orthogonal multiplexing (OFDM) signals for image data transmission; detecting, sorting, and identifying OFDM signals can effectively identify drones and provide timely warnings.

[0003] Orthogonal multiplexing (OFDM) signals transmit data information simultaneously through as many channels as possible within the time-limited bandwidth of the orthogonal channel, achieving high-speed transmission. Currently, domestic and international research on OFDM signals focuses on issues such as signal transmission, channel optimization, and data synchronization, while research on blind detection, sorting, and direction finding is relatively limited. Summary of the Invention

[0004] The purpose of this invention is to provide a method for sorting and identifying Orthogonal Frequency Division Multiplexing (OFDM) signals, which can quickly and accurately sort and identify OFDM signals in the time, spatial, and frequency domains.

[0005] To achieve the above objectives, the present invention provides a method for sorting and identifying Orthogonal Frequency Division Multiplexing (OFDM) signals, comprising the following steps:

[0006] Step S1: Calculate the detection threshold based on the data after digital channelization processing in the absence of signal.

[0007] Step S2: Accumulate the amplitude of the data after digital channelization and perform threshold detection to obtain the pulse descriptor for each channel;

[0008] Step S3: The pulse descriptors between channels are fused by phase difference clustering, and the pulse descriptors belonging to the same OFDM radiation source are classified to form the pulse pool descriptor of the corresponding OFDM radiation source.

[0009] Step S4: Obtain the time-domain parameters, frequency-domain parameters, and spatial-domain parameters of the OFDM signal based on the pulse pool descriptor.

[0010] The method of digital channelization processing includes: performing digital channelization processing on multi-channel time-domain discrete data obtained by AD sampling to convert it into frequency-domain data.

[0011] The method for calculating the detection threshold includes: performing an M-point Fast Fourier Transform on the data after digital channelization processing to obtain the amplitude sum of M channels, and using four times the amplitude sum as the threshold S for each channel. m , where M is an integer power of 2.

[0012] Methods for obtaining computational pulse descriptors include:

[0013] Perform an M-point Fast Fourier Transform on the digitally channelized data to obtain the amplitudes and Amp of the M channels. m Where M is an integer power of 2;

[0014] If Amp m >S m If a signal exists in the current channel, continuously perform M-point Fast Fourier Transforms and record the start time of each channel amplitude exceeding the threshold. and termination time The duration is the pulse width pw n Simultaneously record to amplitude and maximum value within and the phase difference corresponding to the maximum value K is the number of channels, and n represents the nth time period, which is related to the start time. and termination time Correspondingly, the phase difference is represented in terms of angle, thus obtaining the nth pulse description word pdw, which contains information on time, pulse width, channel number, amplitude, and phase difference. n ,

[0015] Methods for obtaining the pulse cell descriptor of an OFDM radiation source include:

[0016] The timer is set to T milliseconds. The L pulse descriptors collected within T milliseconds form the pulse description pool {pdw}. 1 ,pdw 2 ,pdw 3 …,pdw L Phase difference clustering is performed on the descriptors in the pulse descriptor pool;

[0017] Compare the phase differences of the multiple channels of each pulse descriptor. If the difference between the K phase differences is less than 10°, then the pulse descriptors being compared come from the same OFDM radiation source. If the L pulse descriptors come from G OFDM radiation sources respectively, and G≤L;

[0018] Extract all pulse descriptors belonging to the same OFDM radiation source to form the OFDM radiation source pulse pool descriptor edw. g , Including arrival time End time Minimum Channel Maximum Channel Maximum amplitude Amp g and the corresponding phase difference PHA g ;

[0019] in, T milliseconds represents the earliest time among all pulse descriptors of the current OFDM radiation source. T milliseconds represents the latest time among all pulse descriptors of the current OFDM radiation source. T milliseconds represents the smallest channel number among all pulse descriptors belonging to the current OFDM radiation source. T milliseconds is the maximum channel number among all pulse descriptors belonging to the current OFDM radiation source, Amp g and PHA g This represents the maximum amplitude and corresponding phase difference of all pulse descriptors belonging to the current OFDM radiation source.

[0020] Methods for obtaining the time-domain parameters of OFDM signals include:

[0021] According to the arrival time in the OFDM radiation source pulse cell descriptor End time The pulse width of the OFDM radiation source can be obtained. That is, the duration.

[0022] Methods for obtaining the frequency domain parameters of OFDM signals include:

[0023] Based on the minimum channel in the OFDM radiation source pulse cell descriptor Maximum Channel The bandwidth of the OFDM radiation source can be obtained. Where Sample represents the AD sampling rate.

[0024] Methods for obtaining the spatial parameters of OFDM signals include:

[0025] According to the OFDM radiation source pulse cell description word edw g K-channel phase difference PHA gPerform interferometer direction finding, PHA g It can be represented as By subtracting each pair of channels K, we can obtain the K(K-1) phase difference. The angle (α) of the OFDM radiation source can be obtained using the interferometer orientation-finding algorithm. g ,β g ).

[0026] The present invention has the following beneficial effects:

[0027] This invention proposes a method for sorting and identifying Orthogonal Frequency Division Multiplexing (OFDM) signals. This method converts AD sampled data into frequency domain data through digital channelization, obtaining amplitude and phase data. Based on threshold detection results, pulse descriptors for each channel are obtained. Pulse descriptor clustering is performed based on phase to obtain broadband OFDM radiation source pulse information. Direction finding is then performed using the phase within the broadband OFDM radiation source pulse information to obtain broadband OFDM radiation source information including angle parameters. Angle clustering is then performed on the broadband OFDM radiation source pulse information within a certain time period, thereby achieving the sorting and identification of OFDM signals from the time, spatial, and frequency domains. This invention can be applied to the field of anti-UAV signal detection, enabling tasks such as UAV target early warning and multi-target angle tracking. Attached Figure Description

[0028] Figure 1 This is a flowchart of data processing for an orthogonal frequency division multiplexing (OFDM) signal sorting and identification method according to a preferred embodiment of the present invention.

[0029] Figure 2 This is a schematic diagram of multi-channel reception of spatial radiation source signals. The antenna receives OFDM radiation source signals in space, and after microwave reception and AD sampling, discrete time-domain signals are obtained. Frequency-domain information is obtained through digital channelization (M-point fast Fourier transform). After time-domain and frequency-domain clustering, the signals are transmitted to the spatial domain for sorting, thereby realizing time-domain, frequency-domain, and spatial domain sorting and identification.

[0030] Figure 3 This is a schematic diagram of the in-channel pulse detection of the present invention. Detailed Implementation

[0031] The following is based on Figures 1-3 The preferred embodiments of the present invention will be described in detail below.

[0032] like Figure 1 As shown, the present invention provides a method for sorting and identifying Orthogonal Frequency Division Multiplexing (OFDM) signals, comprising the following steps:

[0033] Step S1: Calculate the detection threshold based on the channelized data under no-signal conditions;

[0034] In the absence of signal input, such as Figure 2 As shown, an M-point (M is a power of 2) Fast Fourier Transform is performed on the AD sampling data (multi-channel time-domain discrete data) of K channels. Each channel yields M amplitude and phase data. The amplitude and phase data of the K channels are summed to obtain M amplitude sums for the K channels. Four times the amplitude sum is used as the threshold S for each channel. m .

[0035] Step S2: Accumulate the amplitudes after multi-channel channelization and perform threshold detection to obtain the pulse descriptor for each channel;

[0036] like Figure 3 As shown, during signal detection, multi-channel time-domain discrete data is obtained through AD sampling, and the K-channel AD sampling data is converted into frequency domain data through digital channelization processing.

[0037] Perform an M-point Fast Fourier Transform (M is a power of 2) on the AD sampling data of K channels to obtain M amplitudes and amplitudes (Amp) for the K channels. m Where m∈(1,2,3,…M);

[0038] If Amp m >S m If a signal exists in the current channel, continuously perform M-point Fast Fourier Transforms and record the start time of each channel amplitude exceeding the threshold. and termination time The duration is the pulse width pw n Simultaneously record to amplitude and maximum value within and the phase difference corresponding to the maximum value Where K is the number of channels, and n represents the nth time period, which is related to the start time. and termination time Correspondingly, the phase difference is based on channel 1, therefore The value is 0, thus obtaining the nth pulse description word pdw containing information about time, pulse width, channel number, amplitude, and phase difference. n The phase difference is expressed in terms of angles.

[0039] Step S3: The pulse descriptors between channels are fused by phase difference clustering, and the pulse descriptors belonging to the same OFDM radiation source are classified to form the pulse pool descriptor of the corresponding OFDM radiation source.

[0040] The timer is set to T milliseconds. The L pulse descriptors collected within T milliseconds form the pulse description pool {pdw}. 1 ,pdw 2 ,pdw3 …,pdw L Phase difference clustering is performed on the descriptors in the pulse descriptor pool;

[0041] That is, compare the phase differences of each pulse descriptor's multiple channels. If the difference between K phase differences is less than 10°, then the pulse descriptors being compared come from the same OFDM radiation source. The L pulse descriptors come from G OFDM radiation sources respectively, where G≤L.

[0042] Extract all pulse descriptors belonging to the same OFDM radiation source to form the OFDM radiation source pulse pool descriptor edw. g The OFDM radiation source pulse cell descriptor can be represented as: g∈(1,2,3…G) contains arrival times End time Minimum Channel Maximum Channel Maximum amplitude Amp g and the corresponding phase difference PHA g ; T milliseconds represents the earliest time among all pulse descriptors of the current OFDM radiation source. T milliseconds represents the latest time among all pulse descriptors of the current OFDM radiation source. T milliseconds represents the smallest channel number among all pulse descriptors belonging to the current OFDM radiation source. T milliseconds is the maximum channel number among all pulse descriptors belonging to the current OFDM radiation source, Amp g and PHA g This represents the maximum amplitude and corresponding phase difference of all pulse descriptors belonging to the current OFDM radiation source.

[0043] Step S4: Obtain the time-domain and frequency-domain parameters of the OFDM signal;

[0044] According to the arrival time in the OFDM radiation source pulse cell descriptor End time The pulse width of the OFDM radiation source can be obtained. That is, the duration;

[0045] Based on the minimum channel in the OFDM radiation source pulse cell descriptor Maximum Channel The bandwidth of the OFDM radiation source can be obtained. Where Sample represents the AD sampling rate;

[0046] This yields the time-domain parameters (source pulse width) and frequency-domain parameters (source bandwidth) of the OFDM radiation source.

[0047] Step S5: Obtain the spatial parameters of the OFDM signal;

[0048] According to the OFDM radiation source pulse cell description word edw g K-channel phase difference PHA g Perform interferometer direction finding, PHA g It can be represented as By subtracting each pair of channels K, we can obtain the K(K-1) phase difference. The angle (α) of the OFDM radiation source can be obtained using the interferometer orientation-finding algorithm. g ,β g Thus, the spatial parameters of the OFDM radiation source were obtained.

[0049] Thus, the orthogonal frequency division multiplexing (OFDM) signal can be sorted and identified from the time, spatial, and frequency domains.

[0050] The present invention has the following beneficial effects:

[0051] This invention proposes an orthogonal frequency division multiplexing (OFDM) signal sorting and identification method. This method converts AD sampled data into frequency domain data through digital channelization processing, obtaining amplitude and phase data. Based on threshold detection results, pulse descriptors for each channel are obtained. Pulse descriptor clustering is performed based on phase to obtain broadband OFDM radiation source pulse information. The phase within the broadband OFDM radiation source pulse information is used for direction finding to obtain broadband OFDM radiation source information including angle parameters. Angle clustering is then performed on the broadband OFDM radiation source pulse information within a certain time period, thereby achieving sorting and identification of OFDM signals in the time, spatial, and frequency domains. This method can be applied to the field of anti-UAV signal detection, enabling tasks such as UAV target early warning and multi-target angle tracking.

[0052] It should be noted that, in the embodiments of the present invention, the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing the embodiments and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the present invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0053] Although the present invention has been described in detail through the preferred embodiments above, it should be understood that the above description should not be considered as a limitation of the present invention. Various modifications and substitutions to the present invention will be apparent to those skilled in the art after reading the above description. Therefore, the scope of protection of the present invention should be defined by the appended claims.

Claims

1. A method for sorting and identifying Orthogonal Frequency Division Multiplexing (OFDM) signals, characterized in that, Includes the following steps: Step S1: Calculate the detection threshold based on the data after digital channelization processing in the absence of signal. Step S2: Accumulate the amplitude of the data after digital channelization and perform threshold detection to obtain the pulse descriptor for each channel; Step S3: The pulse descriptors between channels are fused by phase difference clustering, and the pulse descriptors belonging to the same OFDM radiation source are classified to form the pulse pool descriptor of the corresponding OFDM radiation source. Step S4: Obtain the time-domain, frequency-domain, and spatial-domain parameters of the OFDM signal based on the pulse pool descriptor; Methods for obtaining computational pulse descriptors include: Perform an M-point Fast Fourier Transform on the digitally channelized data to obtain M amplitudes and Amp. m Where M is an integer power of 2; If Amp m >S m If a signal exists in the current channel, continuously perform M-point Fast Fourier Transforms and record the start time of each channel amplitude exceeding the threshold. and termination time The duration is the pulse width pw n Simultaneously record to amplitude and maximum value within and the phase difference corresponding to the maximum value K is the number of channels, and n represents the nth time period, which is related to the start time. and termination time Correspondingly, the phase difference is represented in terms of angle, thus obtaining the nth pulse description word pdw, which contains information on time, pulse width, channel number, amplitude, and phase difference. n , Methods for obtaining the pulse cell descriptor of an OFDM radiation source include: The timer is set to T milliseconds. The L pulse descriptors collected within T milliseconds form the pulse description pool {pdw}. 1 ,pdw 2 ,pdw 3 …,pdw L Phase difference clustering is performed on the descriptors in the pulse descriptor pool; Compare the phase differences of the multiple channels of each pulse descriptor. If the difference between the K phase differences is less than 10°, then the pulse descriptors being compared come from the same OFDM radiation source. If the L pulse descriptors come from G OFDM radiation sources respectively, and G≤L; Extract all pulse descriptors belonging to the same OFDM radiation source to form the OFDM radiation source pulse pool descriptor edw. g , Including arrival time End time Minimum Channel Maximum Channel Maximum amplitude Amp g and the corresponding phase difference PHA g ; in, T milliseconds represents the earliest time among all pulse descriptors of the current OFDM radiation source. T milliseconds represents the latest time among all pulse descriptors of the current OFDM radiation source. T milliseconds represents the smallest channel number among all pulse descriptors belonging to the current OFDM radiation source. T milliseconds is the maximum channel number among all pulse descriptors belonging to the current OFDM radiation source, Amp g and PHA g This represents the maximum amplitude and corresponding phase difference of all pulse descriptors belonging to the current OFDM radiation source.

2. The orthogonal frequency division multiplexing (OFDM) signal sorting and identification method as described in claim 1, characterized in that, The method of digital channelization processing includes: performing digital channelization processing on multi-channel time-domain discrete data obtained by AD sampling to convert it into frequency-domain data.

3. The orthogonal frequency division multiplexing (OFDM) signal sorting and identification method as described in claim 2, characterized in that, The method for calculating the detection threshold includes: performing an M-point Fast Fourier Transform on the digitally channelized data to obtain M amplitude sums, and using four times the amplitude sum as the threshold S for each channel. m , where M is an integer power of 2.

4. The orthogonal frequency division multiplexing (OFDM) signal sorting and identification method as described in claim 3, characterized in that, Methods for obtaining the time-domain parameters of OFDM signals include: According to the arrival time in the OFDM radiation source pulse cell descriptor End time The pulse width of the OFDM radiation source can be obtained. That is, the duration.

5. The orthogonal frequency division multiplexing (OFDM) signal sorting and identification method as described in claim 4, characterized in that, Methods for obtaining the frequency domain parameters of OFDM signals include: Based on the minimum channel in the OFDM radiation source pulse cell descriptor Maximum Channel The bandwidth of the OFDM radiation source can be obtained. in, Sample represents the AD sampling rate.

6. The orthogonal frequency division multiplexing (OFDM) signal sorting and identification method as described in claim 4, characterized in that, Methods for obtaining the spatial parameters of OFDM signals include: According to the OFDM radiation source pulse cell description word edw g K-channel phase difference PHA g Perform interferometer direction finding, PHA g It can be represented as By subtracting each pair of channels K, we can obtain the K(K-1) phase difference. The angle (α) of the OFDM radiation source can be obtained using the interferometer orientation-finding algorithm. g ,β g ).

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