A separation method applicable to Mode A / C airborne response pulse collision conditions

Abstract

This invention belongs to the technical field of aviation transponder pulse overlap signal separation methods, specifically relating to a separation method applicable to Mode A / C aviation transponder pulse collision conditions. By analyzing the differential characteristics of the Mode A / C aviation transponder signal waveform in the time and energy domains, the pulse collision signal is effectively split. Based on the waveform definition characteristics of the Mode A / C aviation transponder signal, the pulse frame is accurately recovered from the separated signal, ultimately completing the separation process of the Mode A / C collision pulse signal. This invention requires only a single-channel receiver to achieve signal separation, reducing system implementation costs and engineering difficulty, effectively improving the system monitoring capability in densely overlapping electromagnetic environments, and providing an efficient and engineered solution for transponder pulse signal separation tasks in scenarios such as air traffic surveillance and low-altitude airspace management.

Description

Technical Field

[0001] This invention belongs to the field of separation method technology, and particularly relates to a separation method applicable to Mode A / C aviation response pulse collision conditions. Background Technology

[0002] In modern air traffic control systems, the Mode A / C transponder is a core component, undertaking critical functions such as aircraft identification and altitude information reporting. The accuracy of its signal transmission directly impacts airspace operational safety. With the continuous growth of civil aviation traffic and the increasing aircraft density in airspace, the simultaneous transponding of multiple aircraft can easily lead to pulse signal interleaving and collisions. This results in superimposed and distorted pulse signals in the I and Q data frames acquired by the receiver, making it impossible to directly extract valid information and posing a significant challenge to subsequent signal decoding and target identification.

[0003] Current traditional pulse separation methods are mostly designed for single-type overlapping scenarios, lacking precise adaptation to key parameters such as the binarization characteristics of mode A / C pulse signals and standard pulse width range. When faced with complex collision situations where pulse width and amplitude overlap coexist, they suffer from low separation accuracy, high false negative and false positive rates, and poor adaptability. Especially in environments with strong noise interference, traditional methods struggle to accurately distinguish noise from valid pulse signals and cannot effectively decompose superimposed composite pulses, severely impacting the signal processing efficiency and reliability of aviation transponder systems. Therefore, a targeted pulse separation technology with stable separation performance is urgently needed to solve these problems. Summary of the Invention

[0004] The purpose of this invention is to address the aforementioned technical problems by providing a separation method applicable to Mode A / C aviation response pulse collision conditions.

[0005] In view of this, the present invention provides a separation method applicable to Mode A / C airborne response pulse collision conditions, characterized by comprising the following steps: Step 1: Initialize system operating parameters; Step 2: Construct the A / C standard pulse template, denoted as... ; Step 3: Calculate the modulus of each received I and Q data frame to obtain the sequence; Step 4: Calculate the noise threshold for the current data frame; Step 5: Generate the first pulse descriptor in the current data frame; Step Six: Following the same processing flow as Step Five, generate all remaining pulse descriptors in the data frame sequentially to generate the pulse descriptor PDW={PDW1,PDW2,…,PDW} for the current data frame. Q}; Step 7: Determine the pulse reference amplitude in the data frame; Step 8: Detect the overlap type of the first pulse in the current data frame; Step 9: Separate pulse width overlap types; Step 10: Determine and separate overlapping pulses; Step 11: Receive and process the next frame of data.

[0006] Preferably, in step one, the system normalized sampling frequency, noise threshold expansion coefficient, pulse tolerance, standard pulse width, standard pulse width range, amplitude deviation threshold, and single frame data length are initialized and set respectively.

[0007] Preferably, the template in step two The elements in the array consist of binary symbols of 0 and 1, and their length is . . The first half of the elements consists of continuous elements. Composed of 1s, template The latter part of the elements is composed of consecutive elements. It consists of 0s.

[0008] Preferably, step three specifically includes the following steps: Step S11: Receive a frame of I and Q data sequence of length L. , ; in , These represent the I-channel and Q-channel data corresponding to the nth time step in the current data frame sampled by the ADC; Step S12: Based on the data frame obtained in step S11, perform modulo operations point by point and denot it as... The calculation method is as follows: , .

[0009] Preferably, the sequence obtained in step S12 after modulo operation is used in step four. The noise threshold is calculated as follows: n=1,2,…,L; Where L is the length of the received data determined in step S11, This is the noise threshold expansion coefficient set in step one.

[0010] Preferably, step five further includes the following steps: Step S21: Use the modulo-calculated sequence obtained in step S12 Starting from the first sample point in the data frame, check each sample point to see if its position coincides with a rising edge of a pulse. If the i-th sample data... The previous continuation The mean of the data samples is denoted as . Less than the i-th sample data The following continuation The mean of the data samples is denoted as . And the current data point Exceeding the noise threshold determined in step 4 ,Right now , Then the position of the i-th sample data is determined as the position of the rising edge of the first pulse, and it is output as the TOA result of the first pulse, denoted as TOA1; in, and The calculation method is as follows: , ; , ; Step S22: Determine the first falling edge of the pulse in the data frame and label it TOE1; Using the modulo-calculated sequence obtained in step S12 Starting from the first sample point in the data frame, check each sample point to see if its position coincides with a rising edge of a pulse. If the i-th sample data... The previous continuation The mean of the data samples is denoted as . Greater than the i-th sample data The following continuation The mean of the data samples is denoted as . And the current data point Exceeding the noise threshold determined in step 4 ,Right now , Then, the position of the i-th sample data is determined as the position of the falling edge of the first pulse, and it is output as the TOE result of the first pulse, denoted as TOE1; where, and The calculation method is as follows: , ; , ; Step S23: Determine the width of the first pulse in the data frame and denot it as PW1; The pulse width can be calculated based on the values ​​of pulse TOA1 and TOE1 obtained from steps S21 and S22. The first pulse width PW1 is calculated as PW1 = TOA1 - TOE1 + 1; Step S24: Determine the amplitude of the first pulse in the data frame, denoted as PA1, and the amplitude of the first half of the first pulse, denoted as PA2. The amplitude of the second half is denoted as ; Step S25: The first pulse descriptor PDW1 in the current data frame; Using the first pulse rising edge TOA1, the first pulse falling edge TOE1, the first pulse width PW1, and the first pulse amplitude PA1 obtained in steps S21-S25, the first pulse description word PDW1 is constructed. The data construction method of PDW1 is as follows: PDW1={TOA1, TOE1, PW1, PA1, ... , }

[0011] Preferably, step S24 specifically includes the following steps: Step S241: Determine the location of the candidate sample data within the pulse. Based on the pulses TOA1 and TOE1 detected in steps S21 and S22, respectively, use them as the start and end positions of the pulse signal selection interval, and take their midpoint as the data sample reference point. The method for obtaining this reference point is as follows: ,in Indicates rounding down; Based on this, the positions of the P-1 sample data points before and the P sample data points after the reference sample point are selected as the pulse amplitude positions to calculate the sample data interval. The calculation method is as follows: ; Step S242: Determine the amplitude of the first pulse in the data frame. The amplitude PA1 of the first pulse is calculated based on the data corresponding to the sample data interval determined in step S241, as follows: ; Step S243: Determine the amplitude of the first half pulse of the first pulse in the data frame. and the amplitude of the second half of the first pulse in the data frame The methods for obtaining the results are as follows: , .

[0012] Preferably, step seven specifically includes the following steps: Step S31: Select the pulse description word PDW1 generated in step six and check the recorded pulse width PW1 to determine if the pulse width is normal. If PW1 is within the pulse width range defined in step one... If the pulse width is within the range, the pulse width of the first pulse is determined to be normal; otherwise, the pulse width of the first pulse is determined to be abnormal. Step S32: Determine the pulse reference amplitude in the data frame According to the determination result of step S31, if the width of the first pulse is abnormal, then the amplitude of the first half of the pulse in PDW1 will be adjusted. Set as pulse reference amplitude, i.e. If the first pulse is normal, then the amplitude PA1 of the first pulse is set as the reference amplitude of the current data frame pulse, that is... .

[0013] Preferably, step eight includes selecting the pulse description word PDW1 in the PDW generated in step six and determining whether the pulses overlap by recording the pulse width PW1 in it; If PW1 exceeds the pulse width range defined in step one If the pulse overlap type is determined to be pulse width overlap, proceed to step nine for further processing; otherwise, compare PA1 with the reference pulse amplitude obtained in step seven. Compare; If the absolute error between the two is less than the amplitude deviation threshold in step 1 If the pulses do not overlap, a standard pulse template will be output at the corresponding position in the first channel. The amplitude is equal to the reference pulse amplitude. Conversely, if the pulse overlap type is determined to be pulse amplitude overlap, a standard pulse template is output at the corresponding position of PDW1 in channel 2. The amplitude is equal to the reference pulse amplitude. Then proceed to step ten.

[0014] The beneficial effects of this invention are as follows: By constructing a standard binary pulse template of mode A / C, and combining point-by-point modulus calculation of I and Q data frames with adaptive calculation of noise threshold, accurate extraction of pulse rising edge, falling edge, and amplitude features is achieved, effectively solving the technical pain point of traditional methods in distinguishing between pulse width overlap and amplitude overlap. It comprehensively captures core parameters such as pulse TOA, TOE, PW, and PA through pulse descriptors, and then determines the overlap mode based on pulse width range and amplitude deviation threshold, executing targeted separation strategies. This significantly improves the pulse separation accuracy in complex collision scenarios, and even in environments with strong noise interference, it can stably distinguish between valid pulses and interference signals, with a significantly improved separation accuracy compared to traditional methods.

[0015] This method is rigorous and highly practical. Through standardized parameter initialization and modular processing steps, it adapts to different airspace pulse density scenarios and can efficiently process complex data frames with multi-pulse interleaving and collisions, significantly reducing the false negative and false positive rates. Furthermore, the dynamic determination method of pulse reference amplitude and the multi-channel output design not only simplify the subsequent signal decoding process but also enhance compatibility with existing aviation transponder systems, effectively improving the system's signal processing efficiency and reliability. This provides technical support for accurately obtaining critical information such as aircraft identity and altitude in air traffic control and possesses significant engineering application value. Attached Figure Description

[0016] Figure 1 This is a diagram showing the composition of the separation device of the present invention; Figure 2 This is a flowchart of the process of the present invention; Figure 3 This is a schematic diagram of the A / C overlapping signal of the input separation device in Example 1 (the upper sub-figure shows the data amplitude of one frame of the input device, and the lower sub-figure shows a magnified view of the overlapping area). Figure 4 The diagram shows the effect of the separation device output in Example 1 after mode A / C separation (the upper sub-figure shows the separation result output effect of channel 1, and the lower sub-figure shows the separation result output effect of channel 2). Figure 5 This is a schematic diagram of the A / C overlapping signal of the input separation device in Example 2 (the upper sub-figure shows the data amplitude of one frame of the input device, and the lower sub-figure shows a magnified view of the overlapping area). Figure 6 The image shows the effect of the separation device outputting mode A / C after separation in Example 2 (the upper sub-image shows the separation result output effect of channel 1, and the lower sub-image shows the separation result output effect of channel 2). Detailed Implementation

[0017] The technical solutions of the embodiments of this application will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the scope of protection of this application.

[0018] Example 1. Separation of overlapping signals under mode A / C pulse interleaving conditions; This embodiment uses the appendix Figure 1 The pulse overlap signal separation and processing flow shown is attached. Figure 2 The received data frames were used as input samples to verify the separation performance of the proposed method. The final signal separation results are detailed in the appendix. Figure 3 .

[0019] Step 1: Initialize system operating parameters; Initialize and set the system normalized sampling frequency (denoted as Fs, where Fs=80) and the noise threshold expansion coefficient (denoted as...). ,in =3), pulse tolerance limit (denoted as ,in =0.125×Fs=10), standard pulse width (denoted as ) ,in =0.45×Fs=36), standard pulse width range (denoted as ,in =[26,46]), amplitude deviation threshold (denoted as...) ,in =0.1), set the single frame data length (denoted as L, where L=13000).

[0020] Step 2: Construct the A / C standard pulse template (denoted as...) ).

[0021] template The elements in the array consist of binary symbols '0' and '1', and the array has a length of 72 data points. The first half of the template consists of 32 consecutive '1's. The latter part of the element consists of 32 consecutive '0's.

[0022] Step 3: Process the received I and Q data frames (denoted as...) Find the modulus.

[0023] Step 3.1. Receive a frame of I and Q data sequence with a length of L=13000. , .in , These represent the I-channel and Q-channel data corresponding to the nth time step in the current data frame sampled by the ADC, respectively.

[0024] Step 3.2. Based on the data frame obtained in Step 3.1, perform modulo operations point by point, and denote the result as follows: The calculation method is as follows: , ; Step 4: Calculate the noise threshold of the current data frame (denoted as ). ).

[0025] Using the modulo-calculated sequence obtained in step 3.2 The noise threshold is calculated as follows; =0.3908, n=1,2,…,13000; Where 13000 is the received data length determined in step 3.1, and 3 is the noise threshold expansion coefficient set in step 1.

[0026] Step 5: Generate the first pulse descriptor (denoted as PDW1) in the current data frame; Step 5.1. Determine the first rising edge of the pulse in the data frame (denoted as TOA1); Using the modulo-calculated sequence obtained in step 3.2 Starting from the first sample point in the data frame, the system checks each sample point to see if its position coincides with a rising edge of a pulse. Currently, the 6600th sample data point has been detected. The mean of the previous three consecutive data samples (denoted as ) () smaller than the sample data The mean of the next three consecutive data samples (denoted as ) ), and the current data point Exceeding the noise threshold of 0.3908 determined in step 4, i.e. , Then, the position of the 6600th sample data is determined as the rising edge position of the first pulse, and it is output as the TOA result of the first pulse (denoted as TOA1). and The calculation method is as follows: =0.2229; =0.4812; Step 5.2. Determine the first falling edge of the pulse in the data frame (denoted as TOE1); Using the modulo-calculated sequence obtained in step 3.2 Starting from the first sample point in the data frame, the system checks each sample point to see if its position coincides with a rising edge of a pulse. Currently, the 6640th sample data point has been detected. The mean of the previous three consecutive data samples (denoted as ) () is greater than the sample data The mean of the next three consecutive data samples (denoted as ) ), and the current data point Exceeding the noise threshold of 0.3908 determined in step 4, i.e. , Then the first The location of each sample data point is determined as the position of the first falling edge of the pulse, and this is output as the TOE result of the first pulse (denoted as TOE1). and The calculation method is as follows: =0.4690; =0.2120; Step 5.3. Determine the width of the first pulse in the data frame (denoted as PW1); The pulse width can be calculated based on the pulse values ​​TOA1 and TOE1 obtained from steps 5.1 and 5.2. The first pulse width PW1 is calculated as PW1 = TOA1 - TOE1 + 1 = 41.

[0027] Step 5.4. Determine the amplitude of the first pulse in the data frame (denoted as PA1) and the amplitude of the first half of the first pulse (denoted as PA2). ) and the amplitude of the second half (denoted as ).

[0028] Step 5.4.1. Determine the location of the candidate sample data within the pulse. Based on the pulses TOA1 and TOE1 detected in Steps 5.1 and 5.2, respectively, use them as the start and end positions of the pulse signal selection interval, and take their midpoint as the data sample reference point. The method for determining this is as follows: =6620, where This indicates rounding down to the nearest integer.

[0029] Based on this, the positions of the first 7 and last 8 sample data points of the reference sample point are selected as the pulse amplitude positions to calculate the sample data interval. The calculation method is as follows: ; Step 5.4.2 Determine the amplitude of the first pulse in the data frame. Calculate the amplitude PA1 of the first pulse based on the data corresponding to the sample data interval determined in Step 5.1.1, as follows: =1.0592; Step 5.4.3 Determine the amplitude of the first half-pulse of the first pulse in the data frame. and the amplitude of the second half of the first pulse in the data frame The methods for obtaining the results are as follows: , ; Step 5.5. The first pulse descriptor PDW1 in the current data frame; Using the first pulse rising edge TOA1, the first pulse falling edge TOE1, the first pulse width PW1, and the first pulse amplitude PA1 obtained in steps 5.1 to 5.4, the first pulse description word PDW1 is constructed. The data construction method of PDW1 is as follows: PDW1={6600, 6640, 41, 1.0592, 1.0446, 1.0738}; Step 6: Following the same processing flow as in Step 5, sequentially generate all remaining pulse descriptors (PDW1, PDW2, ... PDW) in the data frame. Q Where Q is the total number of pulses in the current data frame (where Q=16), the pulse descriptor PDW={PDW1,PDW2, …,PDW} of the current data frame is generated. 16}

[0030] Step 7: Determine the pulse reference amplitude in the data frame (denoted as ). ) Step 7.1. Detect the validity of the first pulse width.

[0031] Select the pulse description word PDW1 generated in step 6 and check the recorded pulse width PW1 to determine if the pulse width is normal. In step 6, PW1=41 is within the pulse width range defined in step 1. If the pulse width of the first pulse is within the range, it is determined that the pulse width is normal.

[0032] Step 7.2. Determine the pulse reference amplitude in the data frame. .

[0033] Based on the judgment result of step 7.1, the current PW1=41 is normal, so the amplitude of the first pulse PA1=1.0592 is set as the reference amplitude of the current data frame pulse, that is... .

[0034] Step 8: Detect the overlap type of the first pulse in the current data frame.

[0035] Select the pulse description word PDW1 generated in step 6 and determine whether the pulses overlap using the recorded pulse width PW1=41. Current Then compare PA1 with the reference pulse amplitude obtained in step 7. The absolute errors of the two are compared and found to be less than the amplitude deviation threshold in step 1. (Right now (This is because) the pulses did not overlap, and a standard pulse template was output at the corresponding position of the pulse in the first channel. The amplitude is equal to the reference pulse amplitude. .

[0036] Step 9: Pulse width overlap type separation.

[0037] Step 9.1 Calculate the amplitude of the pulse before and after the pulse and the pulse reference amplitude. Degree of difference.

[0038] Calculate the amplitude of the first half of the pulse and the amplitude of the second half of the pulse, and compare them with the pulse reference amplitude in the data frame obtained in step 7.2. The absolute degree of difference, and denoted as respectively. and The specific calculation method is as follows (since the first pulse does not overlap, the 6th pulse is used as an example); ; ; Step 9.2 Compare the amplitudes before and after the pulse with the pulse reference amplitude. The relative magnitude of the difference.

[0039] Based on the amplitude of the first half of the pulse and the pulse reference amplitude in step 9.1 difference and the amplitude of the second half of the pulse and the pulse reference amplitude difference Calculate the relative magnitude of the difference. ,in .

[0040] Step 9.3 Pulse separation output of pulse width overlap type.

[0041] The relative magnitude of the difference calculated in step 9.2 Determine the pulse output position. Specifically, because currently... Since the value is greater than 0, the standard pulse template is output at the position corresponding to the first half of the pulse in output channel 2. The amplitude is equal to the reference pulse amplitude. The output channel 1 pulse should correspond to the position of the second half of the pulse, which should output a standard pulse template. The amplitude is equal to the reference pulse amplitude. .

[0042] Step 10: Determine and separate the overlapping of other pulses.

[0043] Process the remaining PDWs (PDW2, ... PDW) output from step 6, excluding PDW1, using the same method as steps 8 and 9. 16 (where 16 is the number of pulses in the current data frame) to perform pulse overlap judgment and pulse overlap separation.

[0044] Step 11: Receive and process the next frame of data.

[0045] Receive the next frame of data and repeat steps 3 to 10 to perform overlapping signal separation processing on the next frame of data.

[0046] Example 2. Separation of overlapping signals under mode A / C pulse collision conditions; This embodiment uses the appendix Figure 1 The pulse overlap signal separation and processing flow shown is attached. Figure 4 The received data frames were used as input samples to verify the separation performance of the proposed method. The signal separation results are detailed in the appendix. Figure 5 .

[0047] Step 1: Parameter initialization settings and standard normalized pulse template construction.

[0048] Step 1: Initialize system operating parameters; Initialize and set the system normalized sampling frequency (denoted as Fs, where Fs=80) and the noise threshold expansion coefficient (denoted as...). ,in =3), pulse tolerance limit (denoted as ,in =0.125×Fs=10), standard pulse width (denoted as ) ,in =0.45×Fs=36), standard pulse width range (denoted as ,in =[26,46]), amplitude deviation threshold (denoted as...) ,in =0.1), set the single frame data length (denoted as L, where L=13000).

[0049] Step 2: Construct the A / C standard pulse template (denoted as...) ).

[0050] template The elements in the array consist of binary symbols '0' and '1', and the array has a length of 72 data points. The first half of the template consists of 32 consecutive '1's. The latter part of the element consists of 32 consecutive '0's.

[0051] Step 3: Process the received I and Q data frames (denoted as...) Find the modulus.

[0052] Step 3.1. Receive a frame of I and Q data sequence with a length of L=13000. , .in , These represent the I-channel and Q-channel data corresponding to the nth time step in the current data frame sampled by the ADC, respectively.

[0053] Step 3.2. Based on the data frame obtained in Step 3.1, perform point-by-point modulo calculation and denote it as... The calculation method is as follows: , ; Step 4: Calculate the noise threshold of the current data frame (denoted as ). ).

[0054] Using the modulo-calculated sequence obtained in step 3.2 The noise threshold is calculated as follows; =0.4175, n=1,2,…,13000; Where 13000 is the received data length determined in step 3.1, and 3 is the noise threshold expansion coefficient set in step 1.

[0055] Step 5: Generate the first pulse descriptor (denoted as PDW1) in the current data frame; Step 5.1. Determine the first rising edge of the pulse in the data frame (denoted as TOA1); Using the modulo-calculated sequence obtained in step 3.2 Starting from the first sample point in the data frame, the system checks each sample point to see if its position coincides with a rising edge of a pulse. The 8000th sample data point has now been detected. The mean of the previous three consecutive data samples (denoted as ) () smaller than the sample data The mean of the next three consecutive data samples (denoted as ) ), and the current data point If the noise threshold of 0.4175 determined in step 4 is exceeded, i.e. , Then, the position of the 8000th sample data is determined as the rising edge position of the first pulse, and it is output as the TOA result of the first pulse (denoted as TOA1). and The calculation method is as follows: =0.1390; =0.6301; Step 5.2. Determine the first falling edge of the pulse in the data frame (denoted as TOE1); Using the modulo-calculated sequence obtained in step 3.2 Starting from the first sample point in the data frame, the system checks each sample point to see if its position coincides with a rising edge of a pulse. Currently, the 8042nd sample data point has been detected. The mean of the previous three consecutive data samples (denoted as ) () is greater than the sample data The mean of the next three consecutive data samples (denoted as ) ), and the current data point If the noise threshold of 0.4175 determined in step 4 is exceeded, i.e. , Then the first The location of each sample data point is determined as the position of the first falling edge of the pulse, and this is output as the TOE result of the first pulse (denoted as TOE1). and The calculation method is as follows: =0.6194; =0.1725; Step 5.3. Determine the width of the first pulse in the data frame (denoted as PW1); The pulse width can be calculated based on the values ​​of pulse TOA1 and TOE1 obtained from steps 5.1 and 5.2. The first pulse width PW1 is calculated as PW1 = TOA1 - TOE1 + 1 = 43.

[0056] Step 5.4. Determine the amplitude of the first pulse in the data frame (denoted as PA1) and the amplitude of the first half of the first pulse (denoted as PA2). ) and the amplitude of the second half (denoted as ).

[0057] Step 5.4.1. Determine the location of the candidate sample data within the pulse. Based on the pulses TOA1 and TOE1 detected in Steps 5.1 and 5.2, respectively, use them as the start and end positions of the pulse signal selection interval, and take their midpoint as the data sample reference point. The method for determining this is as follows: =8021, where This indicates rounding down to the nearest integer.

[0058] Based on this, the positions of the first 7 and last 8 sample data points of the reference sample point are selected as the pulse amplitude positions to calculate the sample data interval. The calculation method is as follows: ; Step 5.4.2 Determine the amplitude of the first pulse in the data frame. Calculate the amplitude PA1 of the first pulse based on the data corresponding to the sample data interval determined in Step 5.1.1, as follows: =1.5577; Step 5.4.3 Determine the amplitude of the first half-pulse of the first pulse in the data frame. and the amplitude of the second half of the first pulse in the data frame The methods for obtaining the results are as follows: , ; Step 5.5. The first pulse descriptor PDW1 in the current data frame; Using the first pulse rising edge TOA1, the first pulse falling edge TOE1, the first pulse width PW1, and the first pulse amplitude PA1 obtained in steps 5.1 to 5.4, the first pulse description word PDW1 is constructed. The data construction method of PDW1 is as follows: PDW1={8000, 8042, 43, 1.5577, 1.5566, 1.5588}; Step 6: Following the same processing flow as in Step 5, sequentially generate all remaining pulse descriptors (PDW1, PDW2, ... PDW) in the data frame. QWhere Q is the total number of pulses in the current data frame (where Q=12), the pulse descriptor PDW={PDW1,PDW2,…,PDW} of the current data frame is generated using this. 12}

[0059] Step 7: Determine the pulse reference amplitude in the data frame (denoted as ). ); Step 7.1. Detect the validity of the first pulse width.

[0060] Select the pulse description word PDW1 generated in step 6 and check the recorded pulse width PW1 to determine if the pulse width is normal. In step 6, PW1=43 is within the pulse width range defined in step 1. If the pulse width of the first pulse is within the range, it is determined that the pulse width is normal.

[0061] Step 7.2. Determine the pulse reference amplitude in the data frame. .

[0062] Based on the judgment result of step 7.1, the current PW1=43 is normal, so the amplitude of the first pulse PA1=1.5577 is set as the reference amplitude of the current data frame pulse, that is... .

[0063] Step 8: Detect the overlap type of the first pulse in the current data frame.

[0064] Select the pulse description word PDW1 from the PDW generated in step 6, and determine whether the pulses overlap using the recorded pulse width PW1=43. Current Then compare PA1 with the reference pulse amplitude obtained in step 7. The absolute errors of the two are compared and found to be less than the amplitude deviation threshold in step 1. (Right now (This is because) the pulses did not overlap, and a standard pulse template was output at the corresponding position of the pulse in the first channel. The amplitude is equal to the reference pulse amplitude. .

[0065] Step 9: Pulse width overlap type separation.

[0066] Step 9.1 Calculate the amplitude of the pulse before and after the pulse and the pulse reference amplitude. Degree of difference.

[0067] Calculate the amplitude of the first half of the pulse and the amplitude of the second half of the pulse, and compare them with the pulse reference amplitude in the data frame obtained in step 7.2. The absolute degree of difference, and denoted as respectively. and The specific calculation method is as follows (since the first pulse does not overlap, the third pulse is used as an example); ; ; Step 9.2 Compare the amplitudes before and after the pulse with the pulse reference amplitude. The relative magnitude of the difference.

[0068] Based on the amplitude of the first half of the pulse and the pulse reference amplitude in step 9.1 difference and the amplitude of the second half of the pulse and the pulse reference amplitude difference Calculate the relative magnitude of the difference. ,in .

[0069] Step 9.3 Pulse separation output of pulse width overlap type.

[0070] The relative magnitude of the difference calculated in step 9.2 Determine the pulse output position. Specifically, because currently... If the value is less than or equal to 0, the standard pulse template is output at the position corresponding to the first half of the pulse in output channel 1. The amplitude is equal to the reference pulse amplitude. The output channel 2 should output a standard pulse template at the position corresponding to the latter half of the pulse. The amplitude is equal to the reference pulse amplitude. .

[0071] Step 10: Determine and separate the overlapping of other pulses.

[0072] Process the remaining PDWs (PDW2, ... PDW) output from step 6, excluding PDW1, using the same method as steps 8 and 9. 12 (where 12 is the number of pulses in the current data frame) to perform pulse overlap judgment and pulse overlap separation.

[0073] Step 11: Receive and process the next frame of data.

[0074] Receive the next frame of data and repeat steps 3 to 10 to perform overlapping signal separation processing on the next frame of data.

[0075] The embodiments of this application have been described above with reference to the accompanying drawings. Unless otherwise specified, the embodiments and features in the embodiments of this application can be combined with each other. This application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of this application.

Claims

1. A separation method applicable to Mode A / C airborne response pulse collision conditions, characterized in that: Includes the following steps: Step 1: Initialize system operating parameters; Step 2: Construct the A / C standard pulse template, denoted as... ; Step 3: Calculate the modulus of each received I and Q data frame to obtain the sequence; Step 4: Calculate the noise threshold for the current data frame; Step 5: Generate the first pulse descriptor in the current data frame; Step Six: Following the same processing flow as Step Five, generate all remaining pulse descriptors in the data frame sequentially to generate the pulse descriptor PDW={PDW1,PDW2,…,PDW} for the current data frame. Q }; Step 7: Determine the pulse reference amplitude in the data frame; Step 8: Detect the overlap type of the first pulse in the current data frame; Step 9: Separate pulse width overlap types; Step 10: Determine and separate overlapping pulses; Step 11: Receive and process the next frame of data.

2. The separation method applicable to Mode A / C airborne transponder pulse collision conditions according to claim 1, characterized in that: In step one, the system normalized sampling frequency, noise threshold expansion coefficient, pulse tolerance, standard pulse width, standard pulse width range, amplitude deviation threshold, and single frame data length are initialized and set respectively.

3. The separation method applicable to Mode A / C airborne transponder pulse collision conditions according to claim 1, characterized in that: Template in step two The elements in the array consist of binary symbols of 0 and 1, and their length is . , The first half of the elements consists of continuous elements. Composed of 1s, template The latter part of the elements is composed of consecutive elements. It consists of 0s.

4. The separation method applicable to Mode A / C airborne transponder pulse collision conditions according to claim 1, characterized in that: Step three specifically includes the following steps: Step S11: Receive a frame of I and Q data sequence of length L. , ; in , These represent the I-channel and Q-channel data corresponding to the nth time step in the current data frame sampled by the ADC; Step S12: Based on the data frame obtained in step S11, perform modulo operations point by point and denot it as... The calculation method is as follows: ， 。 5. The separation method applicable to Mode A / C airborne transponder pulse collision conditions according to claim 4, characterized in that: In step four, the modulo-calculated sequence obtained in step S12 is used. The noise threshold is calculated as follows: ,n=1,2,…,L; Where L is the length of the received data determined in step S11, This is the noise threshold expansion coefficient set in step one.

6. The separation method applicable to Mode A / C airborne transponder pulse collision conditions according to claim 5, characterized in that: Step five specifically includes the following steps: Step S21: Use the modulo-calculated sequence obtained in step S12 Starting from the first sample point in the data frame, check each sample point to see if its position is a rising edge of a pulse. If the i-th sample data... The previous continuation The mean of the data samples is denoted as . Less than the i-th sample data The following continuation The mean of the data samples is denoted as . And the current data point Exceeding the noise threshold determined in step 4 ,Right now , Then the position of the i-th sample data is determined as the position of the rising edge of the first pulse, and it is output as the TOA result of the first pulse, denoted as TOA1; in, and The calculation method is as follows: ， ； , , ； Step S22: Determine the first falling edge of the pulse in the data frame and label it TOE1; Using the modulo-calculated sequence obtained in step S12 Starting from the first sample point in the data frame, check each sample point to see if its position is a rising edge of a pulse. If the i-th sample data... The previous continuation The mean of the data samples is denoted as . Greater than the i-th sample data The following continuation The mean of the data samples is denoted as . And the current data point Exceeding the noise threshold determined in step 4 ,Right now , Then, the position of the i-th sample data is determined as the position of the falling edge of the first pulse, and it is output as the TOE result of the first pulse, denoted as TOE1; where, and The calculation method is as follows: ， ； , ； Step S23: Determine the width of the first pulse in the data frame and denot it as PW1; The pulse width can be calculated based on the values ​​of pulse TOA1 and TOE1 obtained from steps S21 and S22. The first pulse width PW1 is calculated as PW1 = TOA1 - TOE1 + 1. Step S24: Determine the amplitude of the first pulse in the data frame, denoted as PA1, and the amplitude of the first half of the first pulse, denoted as PA2. The amplitude of the second half is denoted as ; Step S25: The first pulse descriptor PDW1 in the current data frame; Using the first pulse rising edge TOA1, the first pulse falling edge TOE1, the first pulse width PW1, and the first pulse amplitude PA1 obtained in steps S21-S25, the first pulse description word PDW1 is constructed. The data construction method of PDW1 is as follows: PDW1={TOA1, TOE1, PW1, PA1, ... , } 7. A separation method applicable to Mode A / C airborne transponder pulse collision conditions according to claim 5, characterized in that: Step S24 specifically includes the following steps: Step S241: Determine the location of the candidate sample data within the pulse. Based on the pulses TOA1 and TOE1 detected in steps S21 and S22, respectively, use them as the start and end positions of the pulse signal selection interval, and take their midpoint as the data sample reference point. The method for obtaining this reference point is as follows: ,in Indicates rounding down; Based on this, the positions of the P-1 sample data points before and the P sample data points after the reference sample point are selected as the pulse amplitude positions to calculate the sample data interval. The calculation method is as follows: ; Step S242: Determine the amplitude of the first pulse in the data frame. Calculate the amplitude PA1 of the first pulse based on the data corresponding to the sample data interval determined in step S241. The calculation method is as follows: ; Step S243: Determine the amplitude of the first half pulse of the first pulse in the data frame. and the amplitude of the second half of the first pulse in the data frame The methods for obtaining the results are as follows: , .

8. The separation method applicable to Mode A / C aviation response pulse collision conditions according to claim 1, characterized in that: Step seven specifically includes the following steps: Step S31: Select the pulse description word PDW1 generated in step six and check the recorded pulse width PW1 to determine if the pulse width is normal. If PW1 is within the pulse width range defined in step one... If the pulse width is within the range, the pulse width of the first pulse is determined to be normal; otherwise, the pulse width of the first pulse is determined to be abnormal. Step S32: Determine the pulse reference amplitude in the data frame According to the determination result of step S31, if the width of the first pulse is abnormal, then the amplitude of the first half of the pulse in PDW1 will be adjusted. Set as pulse reference amplitude, i.e. If the first pulse is normal, then the amplitude PA1 of the first pulse is set as the reference amplitude of the current data frame pulse, that is... .

9. The separation method applicable to Mode A / C airborne transponder pulse collision conditions according to claim 1, characterized in that: Step eight includes selecting the pulse description word PDW1 in the PDW generated in step six and determining whether the pulses overlap by recording the pulse width PW1. If PW1 exceeds the pulse width range defined in step one If the pulse overlap type is determined to be pulse width overlap, proceed to step nine for further processing; otherwise, compare PA1 with the reference pulse amplitude obtained in step seven. Compare; If the absolute error between the two is less than the amplitude deviation threshold in step 1 If the pulses do not overlap, a standard pulse template will be output at the corresponding position in the first channel. The amplitude is equal to the reference pulse amplitude. Conversely, if the pulse overlap type is determined to be pulse amplitude overlap, a standard pulse template is output at the corresponding position of PDW1 in channel 2. The amplitude is equal to the reference pulse amplitude. Then proceed to step ten.

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