A method for extracting the number of asynchronous network stations for frequency hopping communication

Abstract

The present invention provides a method for extracting the number of asynchronous network stations for frequency hopping communication, relating to the technical field of frequency hopping communication and applicable to asynchronous network station frequency hopping systems. The method takes as input a set of frequency hopping descriptors for multiple network stations after de-noising, and outputs the number of network stations. First, a statistical analysis is performed on the input to obtain a statistical histogram of the dwell time of the frequency hopping signal. Then, the center dwell time (CenterLast) and the width (WidthLast) of the center dwell time are obtained. Frequency hopping descriptors that meet the judgment criteria are selected, and based on the new frequency hopping descriptors, a distribution histogram of the number of network stations is obtained through statistical analysis. The number of network stations corresponding to the maximum value is selected as the final output, which is used for subsequent sorting of networks with the same hopping rate. The present invention uses the dwell time of the frequency hopping signal to extract the number of network stations, offering advantages such as simplicity, efficiency, stability, and accuracy. Furthermore, determining the number of network stations before performing separation improves sorting accuracy, reduces computational complexity, and enhances system robustness.

Description

Technical Field

[0001] The present invention relates to the technical field of frequency hopping communication, in particular to a method for extracting the number of asynchronous network stations used in frequency hopping communication. Background Art

[0002] Frequency-hopping (FH) networks are easy to network and offer great flexibility, high spectrum utilization, and resistance to interception. With the rapid development of FH technology, the difficulty of FH station sorting is increasing. At the same time, new algorithms for sorting FH stations have been developed, such as TDOA (Time Difference of Arrival) FH sorting and independent component analysis (ICA) sorting.

[0003] As a key technology in frequency-hopping communications, station sorting is rapidly developing. Station sorting isolates target stations from complex electromagnetic environments. This technology includes single-station sorting and multi-station sorting, and is categorized as synchronous or asynchronous depending on whether they share a common time base. The primary challenge with asynchronous stations is isolating the target station from the complex signal. Only after the target station is isolated can detection and jamming of the specific target station be performed based on the frequency-hopping pattern.

[0004] There are two main methods for sorting frequency hopping asynchronous network stations: blind independent component sorting and clustering algorithms. The following are respectively introduced:

[0005] 1. The independent component blind sorting method first preprocesses the observed signal by removing the mean and whitening, and then performs ICA (Independent Component Analysis, ICA) processing, and finally obtains the separated signal to complete the network station sorting.

[0006] 2. The clustering algorithm evaluates the sample density by classifying the set of frequency hopping description words and calculating the distance between each pair of sample data. It then selects the initial cluster center in the area with higher density and finally completes the sorting of the network stations.

[0007] In summary, the scheme for sorting frequency-hopping asynchronous network stations should have the following characteristics:

[0008] 1. The accuracy of network station sorting is to use the sorted radio station signals to successfully detect and interfere with the received network station signals.

[0009] 2. The high efficiency of network station sorting means that in actual engineering applications, a large amount of data can be fed into the algorithm to obtain sorting results in a short time, which is convenient for real-time detection and interference of signals.

[0010] 3. The robustness of network station sorting is that in the actual electromagnetic environment, even if the intercepted frequency hopping radio network signal is accompanied by various interference signals and additional noise and incomplete data, different network station signals can be accurately sorted out.

[0011] Advantages and disadvantages of existing solutions: The importance of station sorting in electronic information confrontation is self-evident, and it has always been a hot topic in frequency hopping communication research. The above two methods each have their own advantages and disadvantages. The advantage of the independent component blind sorting method is that it only uses the intercepted multiple frequency hopping stations for blind sorting, and there is no need to extract the characteristics of the frequency hopping signal in advance; the disadvantage is that it has an incompleteness problem, and the blind source signal separation effect for four or more multi-stations is not good, and it will fail for some nonlinear mixed observation signals. The advantage of the clustering algorithm is that it can realize synchronous and asynchronous multi-station sorting, and use periodic clustering to sort different networking networks; then use DOA (Difference of Arrival) and power parameters to realize the sorting of synchronous radio stations; use time hopping and power parameters to realize the sorting of asynchronous radio stations; the disadvantage is that it relies on the accurate extraction of frequency hopping description words, and the computational complexity is higher than that of the present invention.

[0012] Aiming at the defects of the above existing solutions, the present invention proposes a method for extracting the number of asynchronous network stations used in frequency hopping communication. Summary of the Invention

[0013] The purpose of the present invention is to solve the problems existing in the prior art and provide a method for extracting the number of asynchronous network stations for frequency hopping communication.

[0014] To achieve the above-mentioned purpose, the present invention is implemented through the following technical solutions:

[0015] A method for extracting the number of asynchronous network stations for frequency hopping communication comprises the following steps:

[0016] S1, read the frequency hopping description word set of the frequency hopping signal after noise removal, and determine whether the set is empty. If the determination result is yes, end the algorithm; if the determination result is no, execute step S2;

[0017] S2. Perform statistical analysis to obtain a statistical histogram of the dwell time of the frequency hopping signal;

[0018] S3. Obtain the center dwell time CenterLast and the width WidthLast of the center dwell time;

[0019] S4, brush and select the frequency hopping description word that meets the judgment conditions;

[0020] S5. Perform statistical analysis to obtain a distribution histogram of the number of network stations;

[0021] S6. Based on the network station number distribution histogram obtained in step S5, the network station number corresponding to the maximum value is output as the result;

[0022] S7, perform subsequent sorting of stations with the same jumping speed.

[0023] Preferably, the frequency hopping description word set in step S1 is a set of parameters such as carrier frequency, arrival time, and dwell time used to describe the frequency hopping signal in frequency hopping communication; wherein, the carrier frequency of the frequency hopping signal refers to the center frequency of the signal; the arrival time refers to the time when the signal arrives; the dwell time refers to the length of time the signal stays at a certain frequency; the frequency hopping period is the time interval for the frequency hopping signal to switch to the next frequency; the hopping rate is the inverse of the frequency hopping period, and therefore, the dwell time can reflect the frequency change speed of the frequency hopping signal, that is, the hopping rate.

[0024] Preferably, the method for obtaining the center residence time in step S3 is: traverse all elements in the set and find the residence time with the largest number of occurrences. If it can be found, assign it to the center residence time CenterLast; if it cannot be found, exit the algorithm.

[0025] Preferably, the method for obtaining the width WidthLast of the center dwell time in step S3 includes the following steps:

[0026] S31, calculating the average dwell time of all frequency hopping signals;

[0027] S32. Calculate the standard deviation of the dwell time of all frequency hopping signals;

[0028] S33, the width of the center dwell time WidthLast is the difference between the mean and the standard deviation to the sum of the mean and the standard deviation;

[0029] S34, select the frequency hopping description word that meets the conditions and execute step S31;

[0030] Steps S31 to S34 are iterated twice to obtain a suitable width WidthLast of the center dwell time.

[0031] Preferably, the method for selecting the frequency hopping description words that meet the judgment conditions in step S4 is: according to the center dwell time CenterLast and the width WidthLast of the center dwell time obtained in step S3, the frequency hopping description words of the frequency hopping signal that meet the conditions are screened out from the original set of frequency hopping signal description words, and a new set is formed.

[0032] Preferably, obtaining the distribution histogram of the number of network stations in step S5 includes the following steps:

[0033] S51, selecting a frequency hopping signal of a certain type of network station (having the same frequency hopping signal dwell time);

[0034] S52, counting the number of frequency hopping signals with different hopping times that appear within the dwell time of the frequency hopping signal of this type of network station;

[0035] S53. Traverse the set to obtain a distribution histogram of the number of network stations.

[0036] Compared with the prior art, the beneficial effects of the present invention are:

[0037] 1. Improve sorting accuracy: After determining the number of stations, the signal separation for each station will be more accurate. Compared with blind separation when the number of stations is uncertain, the signal can be processed in a targeted manner after the number of stations is determined, avoiding incorrect separation.

[0038] Second, reduced computational complexity: By categorizing stations with the same hopping rate based on their center dwell time and then performing same-hopping rate sorting, the computational effort required to separate the signals of each station is reduced. This reduces computational complexity compared to blind separation, which requires processing all signals.

[0039] 3. Improve system robustness: After determining the number of network stations, the system can be prevented from overreacting to interference signals such as noise, thereby improving the robustness of the system.

[0040] The dwell time of a frequency-hopping signal is a key characteristic of frequency-hopping signals, accurately reflecting its periodicity and thus effectively distinguishing between different network station signals. Compared to other characteristics, the dwell time of a frequency-hopping signal exhibits greater stability and robustness, making it adaptable to diverse frequency-hopping systems and channel environments. The dwell time of a frequency-hopping signal can be extracted using simple statistical analysis methods, requiring minimal computational and hardware resources and offering high efficiency and reliability. The dwell time of a frequency-hopping signal can be combined with other characteristics, such as arrival time, to further enhance the accuracy and robustness of sorting.

[0041] In summary, using the dwell time of the frequency hopping signal to extract the number of network stations has the advantages of simplicity, efficiency, stability, and accuracy. Moreover, determining the number of network stations before separation can improve the accuracy of sorting, reduce computational complexity, and improve system robustness. It is an effective strategy for network station sorting. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 Schematic diagram of the flow of the method for extracting the number of asynchronous network stations for frequency hopping communication of the present invention;

[0043] Figure 2 The histogram of the dwell time statistics of the frequency hopping signal of 600 frequency hopping description words of 5 network stations;

[0044] Figure 3The histogram of the dwell time statistics of the frequency hopping signal of 600 frequency hopping description words of 5 network stations;

[0045] Figure 4 The histogram of the number of stations for 5 stations and 600 frequency hopping signals. DETAILED DESCRIPTION

[0046] Below in conjunction with specific embodiment, further set forth the present invention.Should be understood that these embodiments are only used to illustrate the present invention and are not used in limiting the scope of the present invention.In addition, should be understood that after reading the content taught by the present invention, those skilled in the art can make various changes or modifications to the present invention, and these equivalent forms fall equally within the scope limited by the application.

[0047] See also Figures 1 to 4 In this embodiment, through the experimental test of 600 frequency hopping description word sets of 5 network stations of a domestic radio station, it is concluded that Figures 2 to 4 , Figure 2 The horizontal axis represents the dwell time of the frequency hopping signal, and the vertical axis represents the frequency of the dwell time of each frequency hopping signal; Figure 3 The middle vertical axis represents the frequency of the dwell time of each frequency hopping signal. It can be seen that the dwell time of the frequency hopping signal is mainly concentrated in 149~153; Figure 4 The horizontal axis represents the number of online stations, and the vertical axis represents the frequency of each online station number.

[0048] The method for extracting the number of asynchronous network stations for frequency hopping communication in this embodiment includes the following steps:

[0049] S1, read the frequency hopping description word set of the frequency hopping signal after noise removal, and determine whether the set is empty. If the determination result is yes, end the algorithm; if the determination result is no, execute step S2;

[0050] S2. Perform statistical analysis to obtain a statistical histogram of the dwell time of the frequency hopping signal;

[0051] S3. Obtain the center dwell time CenterLast and the width WidthLast of the center dwell time;

[0052] S4, brush and select the frequency hopping description word that meets the judgment conditions;

[0053] S5. Perform statistical analysis to obtain a distribution histogram of the number of network stations;

[0054] S6. Based on the network station number distribution histogram obtained in step S5, the network station number corresponding to the maximum value is output as the result;

[0055] S7, perform subsequent sorting of stations with the same jumping speed.

[0056] In this embodiment, the frequency hopping description word set in step S1 is a set of parameters such as the carrier frequency, arrival time, and dwell time used to describe the frequency hopping signal in frequency hopping communication; wherein the carrier frequency of the frequency hopping signal refers to the center frequency of the signal; the arrival time refers to the time when the signal arrives; the dwell time refers to the length of time the signal stays at a certain frequency; the frequency hopping period is the time interval for the frequency hopping signal to switch to the next frequency; and the hopping rate is the inverse of the frequency hopping period. Therefore, the dwell time can reflect the frequency change speed of the frequency hopping signal, that is, the hopping rate.

[0057] In this embodiment, the method for obtaining the center residence time in step S3 is specifically: traverse all elements in the set and find the residence time with the largest number of occurrences. If it can be found, it is assigned to the center residence time CenterLast; if it cannot be found, the algorithm is exited.

[0058] In this embodiment, the method for obtaining the width WidthLast of the center dwell time in step S3 specifically includes the following steps:

[0059] S31, calculating the average dwell time of all frequency hopping signals;

[0060] S32. Calculate the standard deviation of the dwell time of all frequency hopping signals;

[0061] S33, the width of the center dwell time WidthLast is the difference between the mean and the standard deviation to the sum of the mean and the standard deviation;

[0062] S34, select the frequency hopping description word that meets the conditions and execute step S31;

[0063] Steps S31 to S34 are iterated twice to obtain a suitable width WidthLast of the center dwell time.

[0064] In this embodiment, the method of selecting the frequency hopping description words that meet the judgment conditions in step S4 is specifically as follows: based on the center dwell time CenterLast and the center dwell time width WidthLast obtained in step S3, the frequency hopping description words of the frequency hopping signal that meet the conditions are screened out from the original set of frequency hopping signal description words, and a new set is formed.

[0065] In this embodiment, obtaining the distribution histogram of the number of network stations in step S5 specifically includes the following steps:

[0066] S51, selecting a frequency hopping signal of a certain type of network station (having the same frequency hopping signal dwell time);

[0067] S52, counting the number of frequency hopping signals with different hopping times that appear within the dwell time of the frequency hopping signal of this type of network station;

[0068] S53. Traverse the set to obtain a distribution histogram of the number of network stations.

[0069] The asynchronous station number extraction method for frequency-hopping communication in this embodiment separates the signals of each station after determining the number of stations, resulting in more accurate signal separation. Compared to blind separation without an accurate number of stations, determining the number of stations allows for targeted signal processing, avoiding erroneous separations. Furthermore, by categorizing stations with the same hopping rate based on their center dwell time and then performing same-rate sorting, the computational complexity required to separate the signals of each station is reduced. This reduces computational complexity compared to blind separation, which requires processing all signals. Furthermore, determining the number of stations prevents the system from overreacting to interfering signals such as noise, thereby improving system robustness.

[0070] The dwell time of a frequency-hopping signal is a key characteristic of frequency-hopping signals, accurately reflecting its periodicity and thus effectively distinguishing between different network station signals. Compared to other characteristics, the dwell time of a frequency-hopping signal exhibits greater stability and robustness, making it adaptable to diverse frequency-hopping systems and channel environments. The dwell time of a frequency-hopping signal can be extracted using simple statistical analysis methods, requiring minimal computational and hardware resources and offering high efficiency and reliability. The dwell time of a frequency-hopping signal can be combined with other characteristics, such as arrival time, to further enhance the accuracy and robustness of sorting.

Claims

1. A method for extracting the number of asynchronous network stations for frequency hopping communication, characterized in that: The steps include: S1, read the frequency hopping description word set of the frequency hopping signal after noise removal, and determine whether the set is empty. If the determination result is yes, end the algorithm; if the determination result is no, execute step S2; S2. Perform statistical analysis to obtain a statistical histogram of the dwell time of the frequency hopping signal; S3. Obtain the center dwell time CenterLast and the width WidthLast of the center dwell time; S4, brush and select the frequency hopping description word that meets the judgment conditions; S5. Perform statistical analysis to obtain a distribution histogram of the number of network stations; Obtaining the distribution histogram of the number of network stations includes the following steps: S51, selecting a frequency hopping signal of a network station having the same frequency hopping signal dwell time; S52, counting the number of frequency hopping signals with different hopping times that appear within the dwell time of the frequency hopping signal of this type of network station; S53, traverse the set to obtain a distribution histogram of the number of network stations; S6. Based on the network station number distribution histogram obtained in step S5, the network station number corresponding to the maximum value is output as the result; S7, perform subsequent sorting of stations with the same jumping speed.

2. The method for extracting the number of asynchronous network stations for frequency hopping communication according to claim 1, wherein: The frequency hopping description word set in step S1 is a set of parameters used to describe the carrier frequency, arrival time, and dwell time of the frequency hopping signal in frequency hopping communication; among them, the carrier frequency of the frequency hopping signal refers to the center frequency of the signal; the arrival time refers to the time when the signal arrives; the dwell time refers to the length of time the signal stays at a certain frequency; the frequency hopping period is the time interval for the frequency hopping signal to switch to the next frequency; the hopping rate is the inverse of the frequency hopping period, so the dwell time can reflect the frequency change speed of the frequency hopping signal, that is, the hopping rate.

3. The method for extracting the number of asynchronous network stations for frequency hopping communication according to claim 1, wherein: The method for obtaining the center residence time in step S3 is: traverse all elements in the set and find the residence time with the largest number of occurrences. If it can be found, it is assigned to the center residence time CenterLast; if it cannot be found, the algorithm is exited.

4. The method for extracting the number of asynchronous network stations for frequency hopping communication according to claim 1, wherein: The method for obtaining the width WidthLast of the center dwell time in step S3 includes the following steps: S31, calculating the average dwell time of all frequency hopping signals; S32. Calculate the standard deviation of the dwell time of all frequency hopping signals; S33, the width of the center dwell time WidthLast is the difference between the mean and the standard deviation to the sum of the mean and the standard deviation; S34, select the frequency hopping description word that meets the conditions and execute step S31; Steps S31 to S34 are iterated twice to obtain a suitable width WidthLast of the center dwell time.

5. The method for extracting the number of asynchronous network stations for frequency hopping communication according to claim 1, wherein: The method for selecting the frequency hopping description words that meet the judgment conditions in step S4 is: based on the center dwell time CenterLast and the center dwell time width WidthLast obtained in step S3, the frequency hopping description words of the frequency hopping signal that meet the conditions are screened out from the original set of frequency hopping signal description words, and a new set is formed.

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