A synchronization acquisition method based on frequency hopping pulse combination

Abstract

The present application belongs to the field of communication technology, and particularly relates to a synchronization acquisition method based on frequency hopping pulse combination. A transmitter of the present application sends synchronization data by using multiple different frequency hopping frequencies, carries a synchronization sequence on each synchronization frequency, and a receiver adopts a parallel multi-path receiving structure to simultaneously receive multiple synchronization frequencies, each path performs down-conversion, filtering and down-sampling processing, then reduces the influence of interference on the synchronization signal through an adaptive interference suppression module, and finally completes synchronization acquisition in an interference environment through an adaptive combination decision module. Compared with the traditional synchronization acquisition method, the present method can significantly improve the synchronization acquisition probability of a frequency hopping communication system in different interference environments, and has strong application value.

Description

Technical Field

[0001] This invention belongs to the field of communication technology, and in particular relates to a synchronization acquisition method based on frequency hopping pulse combining. Background Technology

[0002] Modern wireless communication faces a complex and ever-changing electromagnetic environment, posing a severe challenge to the anti-interference capability of wireless communication waveforms. Hybrid direct sequence / fast frequency hopping (DS / FFH) communication systems, as one of the representatives of wireless communication systems, have excellent anti-interference, anti-interception, and confidentiality capabilities. However, the communication quality of frequency hopping communication systems is limited by the performance of synchronization acquisition in the interference environment. Therefore, how to improve the anti-interference and robustness of synchronization acquisition in frequency hopping communication is a key issue for frequency hopping anti-interference communication systems.

[0003] Traditional synchronization acquisition algorithms are mainly applicable to direct sequence spread spectrum systems. Scholars both domestically and internationally have proposed a series of schemes: 1) Multi-channel frequency domain parallel acquisition method, which simultaneously compensates the frequency of different branches of the received signal within a certain frequency range, improving the system's resistance to frequency offset; 2) Acquisition scheme based on incoherent / coherent accumulation, which improves the signal-to-noise ratio of the correlation peak by accumulating multiple pseudocode correlation values; 3) Scheme based on Partial Matched Filter-Fast Fourier Transform (PMF-FFT), which uses the Fourier transform results of segmented sequence correlation values ​​as the detection variable, reducing the impact of frequency offset on long synchronization sequences. However, the discontinuous phase introduced by frequency hopping communication systems severely degrades the performance of such methods.

[0004] Synchronization acquisition methods in frequency-hopping communication systems are mainly based on frequency-hopping patterns. Based on this, scholars both domestically and internationally have proposed a series of schemes: 1) Acquisition schemes based on Reed-Solomon (RS) decoding, which utilizes RS hard-decision decoding of frequency-hopping pulses to replace correlation operations, improving the noise immunity of synchronization acquisition; 2) Acquisition schemes based on two-level sequences, which jointly detect minimum shift keying (MSK) waveform sequences and frequency-hopping pattern sequences, improving performance in high dynamic environments; 3) Acquisition schemes based on binomial decision (BD), which utilizes the detection results of each frequency-hopping pulse to complete a binomial hard decision, exhibiting low computational complexity and good noise immunity. However, these methods do not model and analyze typical interferences, and their performance under different types of interference needs further improvement. Summary of the Invention

[0005] To improve synchronization acquisition performance in interference environments, this invention designs a synchronization acquisition method based on frequency hopping pulse combining. The transmitter uses multiple different frequency hopping points to send synchronization data, carrying a synchronization sequence at each frequency. The receiver employs a parallel multiplexer structure to simultaneously receive data from multiple synchronization points. Each channel undergoes down-conversion, filtering, and downsampling to become multiple baseband waveform samples. These multiple baseband waveform samples are then passed through an adaptive interference suppression module. This module performs adaptive time-domain interference suppression for typical time-domain interference such as impulse noise jamming (PNJ) and suppresses typical frequency-domain interference such as comb spectrum noise. The NoiseJamming (CSNJ) method performs adaptive frequency domain interference suppression to reduce the impact of time-domain or frequency-domain interference on the synchronization signal. Finally, the waveform samples after interference suppression are passed through an adaptive merging decision module to construct an adaptive acquisition decision metric and an adaptive acquisition decision threshold based on incoherent weighted merging, thus completing synchronization acquisition in the interference environment. In summary, this method reduces the impact of typical interference on the received synchronization signal through adaptive interference suppression and improves the signal-to-interference-plus-noise ratio of the acquisition decision metric through adaptive merging decision. Therefore, compared with traditional synchronization acquisition methods, this method has superior anti-interference and anti-noise performance.

[0006] To facilitate the description of the present invention, a synchronous capture pattern structure is first given, such as... Figure 1 As shown: The definition of the synchronization capture segment includes There are several synchronization frequencies, each of which is reused. Next, a total of Each frequency hopping pulse contains [number] frequency hopping pulses. The modulation symbols, together with the silent period samples, form a total of [number] modulation symbols. The nth symbol sample point, of which the nth symbol sample point is the nth symbol sample point. The symbol vector of a frequency-hopping pulse is represented as: The modulation symbol rate is Each frequency hopping pulse is up-converted to the corresponding frequency according to the defined synchronous capture frequency hopping pattern. Synchronous frequency points The oversampling factor of the received baseband waveform samples is .

[0007] like Figure 2 , Figure 3 , Figure 4 and Figure 5 As shown, the specific steps of the synchronization acquisition method based on frequency hopping pulse combining are as follows:

[0008] S1. Perform processing on the received waveform. Parallel downconversion, low-pass filtering, and downsampling processing are used to obtain... Roadbed strip waveform sample , ;

[0009] S2, Initialize sample point positions , ;

[0010] S3, Judgment Is this true? If so, for the synchronization frequency point? The baseband waveform sample points are defined by the current position. The waveform sample points and their preceding Composed of waveform samples: Otherwise, proceed to S7;

[0011] S4, to Perform time-domain or frequency-domain interference suppression and output the waveform samples after interference suppression. The specific interference suppression method is as follows:

[0012] S41. Determine if there is interference. If yes, proceed to S42; otherwise, define the noise parameters obtained through noise power estimation as follows: for the synchronization frequency point... Estimated average noise power ,make Enter S48;

[0013] S42. Determine if it is time-domain interference. If so, define the time-domain interference parameters obtained through interference detection as follows: for the synchronization frequency point , No. The time domain of each received pulse is set by the interference samples. , No. The average power of the interfered time-domain samples of the received pulses is The average power of the undisturbed time-domain samples is If not, proceed to S43; otherwise, define the interference as frequency domain interference, and define the frequency domain interference parameters obtained through interference detection as follows: for the synchronization frequency point The center frequency of the interfered frequency domain sample is The set of frequency domain samples that are interfered with is The bandwidth ratio of the interfered frequency domain samples is The average power of the interfered frequency domain samples is The average power of the uninterrupted frequency domain samples is Enter S44;

[0014] S43, Regarding synchronization frequency points The time-domain interference suppression matrix is ​​calculated based on the estimates of the time-domain interference parameters. Then, the temporal interference suppression matrix is ​​used. Calculate the sample points after time-domain interference suppression Enter S48;

[0015] S44, Regarding synchronization frequency points ,right Complete the waveform sample grouping, with each group having a length of [length missing]. , No. Each group is represented as ,in, and It is a positive integer. ;

[0016] S45, to Perform the following two processes simultaneously:

[0017] First approach: [Regarding] Perform time-domain windowing: ,in Window coefficient matrix: ,in For window coefficient;

[0018] right For each vector, do Point Discrete Fourier Transform: ,in The normalized DFT matrix;

[0019] Calculate the frequency domain interference suppression matrix based on the estimated frequency domain interference parameters: ;

[0020] Calculate the frequency domain samples after frequency domain interference suppression: ;

[0021] right Performing the inverse discrete Fourier transform yields ,in express The conjugate transpose, and then delayed. After obtaining the sample points, the time-domain sample points after frequency domain interference suppression of the first branch are obtained. ;

[0022] The second method: Delay After sampling, time-domain windowing is applied according to the first processing method. Point-based discrete Fourier transform, frequency domain interference suppression, The time-domain samples obtained by the inverse Discrete Fourier transform after frequency domain interference suppression in the second branch ;

[0023] S46. Accumulate the time-domain samples after frequency domain interference suppression obtained from the two branches in S45 to obtain the time-domain samples after 1 / 2 overlap windowing frequency domain interference suppression. ;

[0024] S47, Yes Perform sample point stitching: ;

[0025] S48. Synchronization frequency point After completing the adaptive interference suppression process, the final output waveform samples are generated. .

[0026] S5, to Waveform samples after road interference suppression Perform incoherent merging and capture decision, and output the capture result;

[0027] S6. Determine if the capture result is 1. If so, then... Use this as the capture position for the synchronization header; otherwise, go to S7.

[0028] S7 , switch to S3.

[0029] Furthermore, the specific method of S5 is as follows:

[0030] S51. Determine if there is interference. If not, proceed to S52. Otherwise, further determine if the interference is time-domain interference. If yes, proceed to S53. Otherwise, consider the type of interference signal as frequency-domain interference and proceed to S54.

[0031] S52, Calculation without interference The pulse combining coefficient Enter S57;

[0032] S53, Calculating Time-Domain Interference The pulse combining coefficient Enter S57;

[0033] S54. Estimator of the autocovariance matrix of frequency domain interference. ;

[0034] S55. Calculate the estimator of the autocovariance matrix of the correlation peak. ;

[0035] S56, Calculating Frequency Domain Interference The pulse combining coefficient ;

[0036] S57, will After road interference suppression, the waveform samples are downsampled to baseband symbol-level samples and mapped to... A pulse vector, specifically based on the frequency hopping pattern. Downsampling Double mapping to pulse vectors The length of each vector is ;

[0037] S58, will Modulation symbol vector corresponding to the local sequence Correspondingly, normalized cross-correlation operations are performed to obtain... Cross-correlation values: ;

[0038] S59, will The decision metric is obtained by incoherently weighting and combining the cross-correlation values: ;

[0039] S510. Calculate the adaptive capture decision threshold: ,in The system's preset false alarm detection probability, It is the inverse function of the incomplete Gamma function;

[0040] S511, Judgment If the condition is met, the capture is considered complete and the capture result is marked as 1; otherwise, the capture is considered incomplete and the capture result is marked as 0.

[0041] S512, Output the capture result.

[0042] The beneficial effects of this invention are:

[0043] This invention designs a synchronization acquisition method based on frequency hopping pulse combining, which can improve synchronization acquisition performance in interference environments. The transmitter uses multiple different frequency hopping points to send synchronization data, carrying a synchronization sequence on each synchronization frequency point. The receiver adopts a parallel multiplexer structure to receive multiple synchronization frequencies simultaneously. Each channel undergoes downconversion, filtering, and downsampling processing. Then, an adaptive interference suppression module reduces the impact of interference on the synchronization signal. Finally, an adaptive combining decision module completes synchronization acquisition in interference environments. Compared with traditional synchronization acquisition methods, this method can significantly improve the synchronization acquisition probability of frequency hopping communication systems in different interference environments, and has strong application value. Attached Figure Description

[0044] Figure 1 This is a block diagram of the transmitter structure of the synchronization acquisition method based on frequency hopping pulse combining of the present invention;

[0045] Figure 2 This is a receiver structure block diagram of the synchronization acquisition method based on frequency hopping pulse combining according to the present invention;

[0046] Figure 3 This is a flowchart of the overall operation of the synchronization acquisition method based on frequency hopping pulse combining of the present invention;

[0047] Figure 4 This is a flowchart of the adaptive interference suppression workflow;

[0048] Figure 5 This is a flowchart of the adaptive merging decision process;

[0049] Figure 6 This is a schematic diagram comparing the acquisition performance of a specific embodiment of the present invention with that of a traditional synchronous acquisition method under interference-free single-path Rice channel;

[0050] Figure 7 This is a schematic diagram comparing the acquisition performance of a specific embodiment of the present invention with that of a traditional synchronous acquisition method under PNJ interference;

[0051] Figure 8 This is a schematic diagram comparing the acquisition performance of a specific embodiment of the present invention with that of a traditional synchronous acquisition method under CSNJ interference. Detailed Implementation

[0052] The technical solution of the present invention will now be described in detail with reference to the embodiments and accompanying drawings.

[0053] Taking a frequency-hopping communication system using MSK modulation and PNJ / CSNJ interference as examples, synchronization acquisition in an interference environment is performed. First, the synchronization acquisition pattern structure is given, such as... Figure 1 As shown: The definition of the synchronization capture segment includes There are several synchronization frequencies, each of which is reused. Next, a total of Each frequency hopping pulse contains [number] frequency hopping pulses. The modulation symbols, together with the silent period samples, form a total of [number] modulation symbols. The nth symbol sample point, of which the nth symbol sample point is the nth symbol sample point. The symbol vector of a frequency-hopping pulse is represented as: The modulation symbol rate is Each frequency hopping pulse is up-converted to the corresponding frequency according to the defined synchronous capture frequency hopping pattern. Synchronous frequency points The oversampling factor of the received baseband waveform samples is ;

[0054] like Figure 2 , Figure 3 , Figure 4 and Figure 5 As shown, the specific steps of the synchronization acquisition method based on frequency hopping pulse combining are as follows:

[0055] S1. Perform processing on the received waveform. Parallel downconversion, low-pass filtering, and downsampling processing are used to obtain... Roadbed strip waveform sample , ;

[0056] S2, Initialize sample point positions , ;

[0057] S3, Judgment Is this true? If so, for the synchronization frequency point? The baseband waveform sample points are defined by the current position. The waveform sample points and their preceding Composed of waveform samples: Otherwise, proceed to S7;

[0058] S4, to Perform time-domain or frequency-domain interference suppression and output the waveform samples after interference suppression. The specific interference suppression method is as follows:

[0059] S41. Determine if there is interference. If yes, proceed to S42; otherwise, define the noise parameters obtained through noise power estimation as follows: for the synchronization frequency point... Estimated average noise power ,make Enter S48;

[0060] S42. Determine if it is time-domain interference. If so, define the time-domain interference parameters obtained through interference detection as follows: for the synchronization frequency point , No. The time domain of each received pulse is set by the interference samples. , No. The average power of the interfered time-domain samples of the received pulses is The average power of the undisturbed time-domain samples is If not, proceed to S43; otherwise, define the interference as frequency domain interference, and define the frequency domain interference parameters obtained through interference detection as follows: for the synchronization frequency point The center frequency of the interfered frequency domain sample is The set of interfered frequency domain samples is The bandwidth ratio of the interfered frequency domain samples is The average power of the interfered frequency domain samples is The average power of the uninterrupted frequency domain samples is Enter S44;

[0061] S43, Regarding synchronization frequency points Calculate based on the estimated time-domain interference parameters The time-domain interference suppression matrix for each frequency-hopping pulse: ,in For the first The time-domain interference suppression matrix of frequency hopping pulses, where Then, the temporal interference suppression matrix is ​​used. Calculate the sample points after time-domain interference suppression Enter S48;

[0062] S44, Regarding synchronization frequency points ,right Complete the waveform sample grouping, with each group having a length of [length missing]. ,in, , No. Each group is represented as ,in, ;

[0063] S45, to Perform the following two processes simultaneously:

[0064] First approach: [Regarding] Perform time-domain windowing: ,in Here is the Hamming window coefficient matrix: ,in The coefficient of the Hamming window;

[0065] right For each vector, do Point Discrete Fourier Transform: ,in The normalized DFT matrix is ​​defined as follows: ;

[0066] Calculate the frequency domain interference suppression matrix based on the estimated frequency domain interference parameters: ,in ;

[0067] Calculate the frequency domain samples after frequency domain interference suppression: ;

[0068] right Performing the inverse discrete Fourier transform yields ,in express The conjugate transpose of is defined as Finally, delay. After obtaining the sample points, the time-domain sample points after frequency domain interference suppression of the first branch are obtained. ;

[0069] The second method: Delay After sampling, time-domain windowing is applied according to the first processing method. Point-based discrete Fourier transform, frequency domain interference suppression, The time-domain samples obtained by the inverse Discrete Fourier transform after frequency domain interference suppression in the second branch ;

[0070] S46. Accumulate the time-domain samples after frequency domain interference suppression obtained from the two branches in S45 to obtain the time-domain samples after 1 / 2 overlap windowing frequency domain interference suppression. ;

[0071] S47, Yes Perform sample point stitching: ;

[0072] S48. Synchronization frequency point After completing the adaptive interference suppression process, the final output waveform samples are generated. .

[0073] S5, to Waveform samples after road interference suppression Perform incoherent merging and capture decision, and output the capture result;

[0074] S6. Determine if the capture result is 1. If so, then... Use this as the capture position for the synchronization header; otherwise, go to S7.

[0075] S7 , switch to S3.

[0076] Furthermore, the specific method of S5 is as follows:

[0077] S51. Determine if there is interference. If not, proceed to S52. Otherwise, further determine if the interference is time-domain interference. If yes, proceed to S53. Otherwise, consider the type of interference signal as frequency-domain interference and proceed to S54.

[0078] S52, Calculation without interference The pulse combining coefficient Located at frequency point The The merging coefficient corresponding to each pulse is: Enter S57;

[0079] S53, Calculating Time-Domain Interference The pulse combining coefficient Located at frequency point The The merging coefficient corresponding to each pulse is: Enter S57;

[0080] S54. Estimator of the autocovariance matrix of frequency domain interference. For frequency points The elements of the matrix estimator of the autocovariance moments of frequency domain interference are ,in Represents the row index of the matrix. Indicates the column index of the matrix;

[0081] S55. Calculate the estimator of the autocovariance matrix of the correlation peak. For frequency points Estimator of the autocovariance matrix of the correlation values for Downsampling of all rows and columns A matrix composed of multiples, where ,in , express Circular shift of diagonal elements a diagonal matrix;

[0082] S56, Calculating Frequency Domain Interference The pulse combining coefficient Located at frequency point The The merging coefficient corresponding to each pulse is: ;

[0083] S57, will After road interference suppression, the waveform samples are downsampled to baseband symbol-level samples and mapped to... A pulse vector, specifically based on the frequency hopping pattern. Downsampling Double mapping to pulse vectors The length of each vector is ;

[0084] S58, will Modulation symbol vector corresponding to the local sequence Correspondingly, normalized cross-correlation operations are performed to obtain... Cross-correlation values: ;

[0085] S59, will The decision metric is obtained by incoherently weighting and combining the cross-correlation values: ;

[0086] S510. Calculate the adaptive capture decision threshold: The system's preset false alarm detection probability is , It is the inverse function of the incomplete Gamma function;

[0087] S511, Judgment If the condition is met, the capture is considered complete and the capture result is marked as 1; otherwise, the capture is considered incomplete and the capture result is marked as 0.

[0088] S512, Output the capture result.

[0089] Figure 6 To compare the acquisition probability and false alarm probability performance of this implementation method with that of the traditional BD-based synchronization acquisition method in a single-path Ricean channel (Ricean factor 15dB, Doppler shift 5467Hz), the horizontal axis represents the normalized symbol signal-to-noise ratio. The vertical axis represents the capture probability. and false alarm probability Initial frequency offset selection and Two scenarios, with 10 simulation iterations. 4 Simulation results show that, with an initial frequency offset of 10kHz, the traditional method... The acquisition probability reaches 95% at the same time, and the synchronous acquisition method of the present invention, suitable for low signal-to-noise ratio environments, can achieve this. It achieves a 95% correct acquisition probability, thus outperforming the traditional method by approximately 1.1 dB at a 95% acquisition probability; similarly, at an initial frequency offset of 50 kHz, the traditional method... The acquisition probability reaches 95% at the same time, and the synchronous acquisition method of the present invention, suitable for low signal-to-noise ratio environments, can achieve this. The method achieves a 95% correct acquisition probability, thus outperforming traditional methods by approximately 1.1 dB at the same acquisition probability of 95%. Because the method of this invention utilizes an incoherent merging method to significantly improve the signal-to-noise ratio of the acquisition decision metric, its synchronous acquisition performance is superior to traditional synchronous acquisition methods when the initial frequency offset is the same.

[0090] The time-domain interference parameters are set as follows: Considering broadband Gaussian-distributed PNJ interference, its start time is aligned with the frequency-hopping pulse, the interference pulse period is the same as the frequency-hopping pulse period, and the time-domain interference ratio of each interference pulse is... That is, 32 out of 65 symbols in a frequency-hopping pulse are interfered with; under this parameter, Figure 7 The performance of this embodiment and the traditional BD-based synchronization acquisition method under PNJ interference is compared; where the horizontal axis represents the signal-to-interference ratio of the received sample. The vertical axis represents the capture probability. and false alarm probability The number of simulations was 10. 4 Simulation results show that, with an initial frequency offset of 10kHz, the normalized symbol signal-to-noise ratio is... At that time, traditional methods were The acquisition probability reaches 95% at the same time, and the synchronous acquisition method of the present invention, suitable for environments with strong interference and low signal-to-noise ratio, can achieve this. The method achieves a 95% correct acquisition probability, thus outperforming the traditional method by approximately 2.2 dB at a 95% acquisition probability. The method of this invention reduces the impact of temporal interference samples through an adaptive interference suppression module and jointly optimizes the design of the synchronous acquisition method under temporal interference suppression. Therefore, under the same initial frequency offset and signal-to-noise ratio, the anti-temporal interference performance of the synchronous acquisition method of this invention is superior to that of the traditional synchronous acquisition method.

[0091] The frequency domain interference parameters are set as follows: Considering CSNJ interference affecting all 8 synchronization frequencies, the interference bandwidth factor for each affected frequency is 0.2, meaning that 1MHz of bandwidth within a 5MHz bandwidth of each frequency is interfered with; under these parameters, Figure 8 To compare the acquisition probability and false alarm probability performance of this implementation method with that of the traditional BD-based synchronous acquisition method under CSNJ interference, simulation parameters and... Figure 7 The simulation parameters were set the same; simulation results show that, with an initial frequency offset of 10kHz, the normalized symbol signal-to-noise ratio is [value missing]. At that time, traditional methods were The acquisition probability reaches 95% at that time, and the synchronous acquisition method of the present invention, suitable for environments with strong interference and low signal-to-noise ratio, achieves this. The method achieves a 95% correct acquisition probability, thus outperforming the traditional method by approximately 0.5 dB at a 95% acquisition probability. The method of this invention reduces the impact of frequency domain interference samples through an adaptive interference suppression module and jointly optimizes the design of the synchronous acquisition method under frequency domain interference suppression. Under the same frequency offset and the same signal-to-noise ratio, the anti-frequency domain interference performance of the synchronous acquisition method of this invention is superior to that of the traditional synchronous acquisition method.

Claims

1. A synchronization acquisition method based on frequency hopping pulse combining, characterized in that, Define a synchronous capture segment containing There are several synchronization frequencies, each of which is reused. Next, a total of Each frequency hopping pulse contains [number] frequency hopping pulses. The modulation symbols, together with the silent period samples, form a total of [number] modulation symbols. The nth symbol sample point, of which the nth symbol sample point is the nth symbol sample point. The symbol vector of a frequency-hopping pulse is represented as: The modulation symbol rate is Each frequency hopping pulse is up-converted to the corresponding frequency according to the defined synchronous capture frequency hopping pattern. Synchronous frequency points The oversampling factor of the received baseband waveform samples is ; The synchronous acquisition method includes the following steps: S1. Perform processing on the received waveform. Parallel downconversion, low-pass filtering, and downsampling processing are used to obtain... Roadbed strip waveform sample , ; S2, Initialize sample point positions , ; S3, Judgment Is this true? If so, for the synchronization frequency point? The baseband waveform sample points are defined by the current position. The waveform sample points and their preceding Composed of waveform samples: Otherwise, proceed to S7; S4, to Perform time-domain or frequency-domain interference suppression and output the waveform samples after interference suppression. The specific interference suppression method is as follows: S41. Determine if there is interference. If yes, proceed to S42; otherwise, define the noise parameters obtained through noise power estimation as follows: for the synchronization frequency point... The estimated average noise power is ,make Enter S48; S42. Determine if it is time-domain interference. If so, define the time-domain interference parameters obtained through interference detection as follows: for the synchronization frequency point , No. The time domain of each received pulse is set by the interference samples. , No. The average power of the interfered time-domain samples of the received pulses is The average power of the undisturbed time-domain samples is If not, proceed to S43; otherwise, define the interference as frequency domain interference, and define the frequency domain interference parameters obtained through interference detection as follows: for the synchronization frequency point The center frequency of the interfered frequency domain sample is The set of frequency domain samples that are interfered with is The bandwidth ratio of the interfered frequency domain samples is The average power of the interfered frequency domain samples is The average power of the uninterrupted frequency domain samples is Enter S44; S43, Regarding synchronization frequency points The time-domain interference suppression matrix is ​​calculated based on the estimates of the time-domain interference parameters. Then, the temporal interference suppression matrix is ​​used. Calculate the sample points after time-domain interference suppression Enter S48; S44, Regarding synchronization frequency points ,right Complete the waveform sample grouping, with each group having a length of [length missing]. , No. Each group is represented as ,in, and It is a positive integer. ; S45, to Perform the following two processes simultaneously: First approach: [Regarding] Time-domain windowing is performed to obtain ,in Window coefficient matrix: ,in For window coefficient; right For each vector, do Point Discrete Fourier Transform: ,in The normalized DFT matrix; Calculate the frequency domain interference suppression matrix based on the estimated frequency domain interference parameters: ; Calculate the frequency domain samples after frequency domain interference suppression: ; right Performing the inverse discrete Fourier transform yields ,in express The conjugate transpose, and then delayed. After obtaining the sample points, the time-domain sample points after frequency domain interference suppression of the first branch are obtained. ; The second method: Delay After sampling, time-domain windowing is applied according to the first processing method. Point-based discrete Fourier transform, frequency domain interference suppression, The time-domain samples obtained by the inverse Discrete Fourier transform after frequency domain interference suppression in the second branch ; S46. Accumulate the time-domain samples after frequency domain interference suppression obtained from the two branches in S45 to obtain the time-domain samples after 1 / 2 overlap windowing frequency domain interference suppression. ; S47, Yes Perform sample point stitching: ; S48. Synchronization frequency point After completing the adaptive interference suppression process, the final output waveform samples are generated. ; S5, to Waveform samples after road interference suppression Perform incoherent merging and capture decision, and output the capture result; S6. Determine if the capture result is 1. If so, then... Use this as the capture position for the synchronization header; otherwise, go to S7. S7 , switch to S3.

2. The synchronization acquisition method based on frequency hopping pulse combining according to claim 1, characterized in that, The specific method for S5 is as follows: S51. Determine if there is interference. If not, proceed to S52. Otherwise, further determine if the interference is time-domain interference. If yes, proceed to S53. Otherwise, consider the type of interference signal as frequency-domain interference and proceed to S54. S52, Calculation without interference The pulse combining coefficient Located at frequency point The The merging coefficient corresponding to each pulse is: Enter S57; S53, Calculating Time-Domain Interference The pulse combining coefficient Located at frequency point The The merging coefficient corresponding to each pulse is: Enter S57; S54. Estimator of the autocovariance matrix of frequency domain interference. For frequency points The elements of the matrix estimator of the autocovariance moments of frequency domain interference are ,in Represents the row index of the matrix. Indicates the column index of the matrix; S55. Calculate the estimator of the autocovariance matrix of the correlation peak. For frequency points Estimator of the autocovariance matrix of the correlation values for Downsampling of all rows and columns A matrix composed of multiples, where ,in , express Circular shift of diagonal elements a diagonal matrix; S56, Calculating Frequency Domain Interference The pulse combining coefficient Located at frequency point The The merging coefficient corresponding to each pulse is: ; S57, will After road interference suppression, the waveform samples are downsampled to baseband symbol-level samples and mapped to... A pulse vector, specifically based on the frequency hopping pattern. Downsampling Double mapping to pulse vectors The length of each vector is ; S58, will Modulation symbol vector corresponding to the local sequence Correspondingly, normalized cross-correlation operations are performed to obtain... Cross-correlation values: ; S59, will The decision metric is obtained by incoherently weighting and combining the cross-correlation values: ; S510. Calculate the adaptive capture decision threshold: ,in The system's preset false alarm detection probability, It is the inverse function of the incomplete Gamma function; S511, Judgment If the condition is met, the capture is considered complete and the capture result is marked as 1; otherwise, the capture is considered incomplete and the capture result is marked as 0. S512, Output the capture result.

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