CN114513226A

CN114513226A - Method and device for estimating parameters of frequency hopping network station, frequency hopping monitoring equipment and storage medium

Info

Publication number: CN114513226A
Application number: CN202210160747.8A
Authority: CN
Inventors: 余昌学; 秦芦岩; 付磊
Original assignee: Guangzhou Huiruisitong Technology Co Ltd
Current assignee: Guangzhou Huiruisitong Technology Co Ltd
Priority date: 2022-02-22
Filing date: 2022-02-22
Publication date: 2022-05-17

Abstract

The disclosure provides a method and a device for estimating parameters of a frequency hopping network station, frequency hopping monitoring equipment and a storage medium, and relates to the technical field of mobile communication. The method comprises the following steps: performing signal effectiveness estimation on each line of data in the time-frequency diagram, and determining the number of signals of each line of data; determining the number of the frequency hopping network stations according to the product of the number of each signal in all the columns and the number of the columns with the same number of the signals; extracting effective signals from each row of data in the time-frequency diagram to obtain all effective signals in the time-frequency diagram; based on the number of the frequency hopping network stations, clustering all effective signals to obtain an effective signal set corresponding to each frequency hopping network station; and extracting parameters of effective signals contained in an effective signal set corresponding to each frequency hopping network station, and determining related parameters of each frequency hopping network station. Therefore, the accuracy of parameter estimation of the frequency hopping network station is improved when a complex broadband frequency hopping signal and a multi-frequency hopping network station are mixed.

Description

Method and device for estimating parameters of frequency hopping network station, frequency hopping monitoring equipment and storage medium

Technical Field

The present disclosure relates to the field of mobile communications technologies, and in particular, to a method and an apparatus for estimating parameters of a frequency hopping network station, a frequency hopping monitoring device, and a storage medium.

Background

In recent years, spread spectrum communication is widely applied in the fields of military, civil use and the like due to the advantages of unique low interception probability, strong anti-interference capability, high confidentiality and the like. Frequency hopping communication is one of the main means of spread spectrum communication, inherits various advantages of spread spectrum communication, and makes the communication mode widely adopted in military fields such as short-wave and ultra-short wave radio stations. In addition, the frequency hopping communication technology can also be applied to civil fields such as GSM (Global System for Mobile Communications), bluetooth, and unmanned aerial vehicles.

When using frequency hopping communication techniques, the frequency hopping signal parameters have to be estimated. And the frequency hopping signal parameter estimation is to estimate parameters such as the frequency hopping period, the hopping moment, the frequency hopping frequency set and the like of the extracted frequency hopping signal in real time. The frequency hopping period, hopping moment, frequency hopping frequency set and the like of the frequency hopping signal are characteristic parameters which are mainly estimated by the frequency hopping communication system. The short-time Fourier transform is one of the methods for solving the time domain and frequency domain calculation, the time domain precision and the frequency domain precision are in contradiction, but the calculation complexity is low, and cross term interference does not exist, so that the method is very suitable for analyzing frequency hopping signals. In addition, a spectrogram of STFT (Short-Time Fourier Transform) is used as a processing object, and a classical algorithm in the field of image processing is adopted to perform preliminary optimization such as interference elimination on a transformation result, so that the accuracy of parameter estimation can be improved.

Disclosure of Invention

The inventor finds that the related parameter estimation method of the frequency hopping signal is a simple tone frequency hopping signal when the simulation verification is carried out on the frequency hopping signal. For the complicated broadband frequency hopping signal and the frequency hopping signal of the multi-network station, the estimation of the parameters of the frequency hopping network station is not accurate, and the accuracy of the estimation of the parameters of the frequency hopping network station can be ensured only by further optimization processing.

The embodiment of the disclosure aims to provide a method and a device for estimating parameters of a frequency hopping network station, frequency hopping monitoring equipment and a storage medium, which can solve the problem that the estimation of the parameters of the frequency hopping network station is inaccurate for the existing complex broadband frequency hopping signals and the frequency hopping signals of multiple network stations.

In order to solve the above technical problem, a first aspect of the embodiments of the present disclosure provides the following technical solutions: a method of frequency hopping network station parameter estimation, the method comprising:

performing signal effectiveness estimation on each line of data in the time-frequency diagram, and determining the number of signals of each line of data;

determining the number of the frequency hopping network stations according to the product of the number of each signal in all the columns and the number of columns with the same number of signals;

extracting effective signals from each row of data in the time-frequency diagram to obtain all effective signals in the time-frequency diagram;

based on the number of the frequency hopping network stations, clustering all effective signals to obtain an effective signal set corresponding to each frequency hopping network station;

and extracting parameters of effective signals contained in an effective signal set corresponding to each frequency hopping network station, and determining related parameters of each frequency hopping network station.

In order to solve the above technical problem, a second aspect of the embodiments of the present disclosure provides the following technical solutions: an apparatus for hop-net-station parameter estimation, the apparatus comprising: the device comprises an estimation module, a network station number determination module, an extraction module, a clustering module and a determination module; wherein:

the estimation module is used for carrying out signal effectiveness estimation on each line of data in the time-frequency diagram and determining the number of signals of each line of data;

the network station number determining module is used for determining the number of the frequency hopping network stations according to the product of the number of each signal in all the columns and the number of the columns with the same number of the signals;

the extraction module is used for extracting effective signals from each row of data in the time-frequency diagram to obtain all the effective signals in the time-frequency diagram;

the clustering module is used for clustering all effective signals based on the number of the frequency hopping network stations to obtain an effective signal set corresponding to each frequency hopping network station;

the determining module is configured to perform parameter extraction on the effective signals included in the effective signal set corresponding to each of the frequency hopping network stations, and determine relevant parameters of each of the frequency hopping network stations.

In order to solve the above technical problem, a third aspect of the embodiments of the present disclosure provides the following technical solutions: a frequency hopping monitoring device, comprising: a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the computer program when executed by the processor implements the steps of the method for estimating parameters of a hop network station provided in the first aspect of the embodiments of the present disclosure.

In order to solve the above technical problem, a fourth aspect of the embodiments of the present disclosure provides the following technical solutions: a computer-readable storage medium, on which a program of a method for estimating parameters of a hop network station is stored, and when the program of the method for estimating parameters of a hop network station is executed by a processor, the steps of the method for estimating parameters of a hop network station provided in the first aspect of the embodiments of the present disclosure are implemented.

Compared with the prior art, the method, the device, the frequency hopping monitoring equipment and the storage medium for estimating the parameters of the frequency hopping network station provided by the embodiment of the disclosure comprise the following steps: performing signal effectiveness estimation on each line of data in the time-frequency diagram, and determining the number of signals of each line of data; determining the number of the frequency hopping network stations according to the product of the number of each signal in all the columns and the number of the columns with the same number of the signals; extracting effective signals from each row of data in the time-frequency diagram to obtain all effective signals in the time-frequency diagram; based on the number of the frequency hopping network stations, clustering all effective signals to obtain an effective signal set corresponding to each frequency hopping network station; and extracting parameters of effective signals contained in an effective signal set corresponding to each frequency hopping network station, and determining related parameters of each frequency hopping network station. The method and the device have the advantages that the validity of each line of data is estimated, the number of the frequency hopping network stations is determined by the product of the number of each signal in all the lines and the number of the lines with the same number of the signals, the valid signals of each line of data are extracted, the number of the network stations and the valid signals can be accurately determined under the condition that the more complex broadband frequency hopping signals and the multi-frequency hopping network stations are mixed, and the accuracy of the parameter estimation of the frequency hopping network stations is improved.

Drawings

One or more embodiments are illustrated by way of example in the accompanying drawings, which correspond to the figures in which like reference numerals refer to similar elements and which are not to scale unless otherwise specified.

Fig. 1 is a schematic flowchart of a method for estimating parameters of a frequency hopping network station according to an embodiment of the present disclosure;

FIG. 2 is a schematic diagram of a binarized time-frequency diagram;

FIG. 3 is a detailed flowchart of step S1 in FIG. 1;

FIG. 4 is a detailed flowchart of step S2 in FIG. 1;

FIG. 5 is a detailed flowchart of step S3 in FIG. 1;

FIG. 6 is a detailed flowchart of step S4 in FIG. 1;

FIG. 7 is a detailed flowchart of step S5 in FIG. 1;

fig. 8 is a schematic structural diagram of a device for estimating parameters of a frequency hopping network station according to an embodiment of the present disclosure;

fig. 9 is a schematic structural diagram of a frequency hopping monitoring device according to an embodiment of the present disclosure.

Detailed Description

In order to make the technical solutions of the present disclosure better understood by those skilled in the art, the technical solutions of the embodiments of the present disclosure will be clearly and completely described below with reference to the drawings in the embodiments of the present disclosure, and it is obvious that the described embodiments are only some embodiments of the present disclosure, not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments disclosed herein without making any creative effort, shall fall within the protection scope of the present disclosure.

It should be noted that the terms "first," "second," and the like in the description and claims of the present disclosure and in the above-described drawings are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the disclosure described herein are capable of operation in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs. The terminology used in the description of the disclosure herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items.

In addition, technical features involved in different embodiments of the present disclosure described below may be combined with each other as long as they do not conflict with each other.

In the frequency hopping communication technology, a received frequency hopping signal is often subjected to short-time Fourier transform to obtain a time-frequency spectrogram, the spectrogram of the STFT is taken as a processing object, and a classical algorithm in the field of image processing is adopted to perform preliminary optimization such as interference elimination on a transformation result, so that the accuracy of parameter estimation can be improved.

The reception model of the frequency hopping signal can be expressed as:

wherein x (T) is the received signal, and the total time length of signal reception is T_sT is more than or equal to 0 and less than or equal to T at signal receiving moment_sAnd a is the amplitude value of the frequency hopping signal,

is a rectangular window, T is the frequency hopping signal period, T₀Is the start time of frequency hopping, f_kN-1 is a frequency hopping frequency point, N is the number of frequency hopping frequency points, and I is_i(t) is interference such as burst interference signal, fixed frequency interference signal, sweep frequency interference signal, etc., and n (t) is white Gaussian noise.

The STFT transform is defined as:

where x (t) is the input signal and w (t) is the time window function. STFT (t, f) is a two-dimensional vector, t representing time and f frequency.

In order to facilitate understanding of the technical solutions proposed by the present disclosure, the above inventive concepts of the present disclosure are described in more detail below with reference to the accompanying drawings and specific embodiments.

In a first aspect, please refer to fig. 1, which is a flowchart illustrating a method for estimating parameters of a frequency hopping network station according to an embodiment of the present disclosure. The embodiment of the disclosure provides a method for estimating parameters of a frequency hopping network station, which comprises the following steps:

s1, performing signal validity estimation on each line of data in the time-frequency diagram, and determining the number of signals of each line of data; the time-frequency graph is a binarization time-frequency graph obtained after interference removal processing and noise removal processing are carried out on an input signal;

s2, determining the number of the frequency hopping network stations according to the product of the number of each signal in all the columns and the number of the columns with the same number of the signals;

s3, extracting effective signals from each line of data in the time-frequency diagram to obtain all the effective signals in the time-frequency diagram;

s4, based on the number of the frequency hopping network stations, clustering all effective signals to obtain an effective signal set corresponding to each frequency hopping network station;

s5, performing parameter extraction on the effective signals included in the effective signal set corresponding to each hop netowrk station, and determining the relevant parameters of each hop netowrk station.

In this embodiment, the signal effectiveness estimation is performed on each line of data in the time-frequency diagram, so as to determine the number of signals in each line of data; determining the number of the frequency hopping network stations according to the product of the number of each signal in all the columns and the number of the columns with the same number of the signals; extracting effective signals from each row of data in the time-frequency diagram to obtain all effective signals in the time-frequency diagram; based on the number of the frequency hopping network stations, clustering all effective signals to obtain an effective signal set corresponding to each frequency hopping network station; and extracting parameters of effective signals contained in an effective signal set corresponding to each frequency hopping network station, and determining related parameters of each frequency hopping network station. Therefore, under the condition of more complex broadband frequency hopping signals and multi-frequency hopping network station mixing, the number of the network stations and effective signals can be accurately determined, and the accuracy of the parameter estimation of the frequency hopping network station is further improved.

In one embodiment, before step S1, the method further comprises: and acquiring the binaryzation time-frequency diagram after interference removal processing and noise removal processing. For clearly showing the binarized time-frequency diagram, please refer to fig. 2, which is a schematic diagram of the binarized time-frequency diagram. It should be understood by those skilled in the art that the binarized time-frequency diagram shown in fig. 2 is only a binarized time-frequency diagram obtained by converting a received signal in a specific case, and includes 3 broadband network stations and 2 monophonic network stations. The binarization time-frequency diagram is used for visually representing the time-frequency state of the signal, and different binarization time-frequency diagrams obtained by converting different signals at different moments are different.

In particular, the parameters of the hop net station include, but are not limited to, the hop time, the hop frequency, and the hop period of the hop net station.

Specifically, the time-frequency diagram is a two-dimensional matrix, and the longitudinal axis direction of the two-dimensional matrix is the column direction and corresponds to the frequency; the horizontal axis is the row direction and corresponds to time; the two-dimensional matrix is composed of a plurality of elements, and when the value of an element is 0, the position of the element is represented to have no signal; when the value of an element is 1, it indicates that the element is located with a signal, and the element is called a signal element. Each element has a row index and a column index, wherein the row index represents the frequency of the signal corresponding to the element, and the column index represents the time of the signal corresponding to the element.

In one embodiment, as shown in fig. 3, the step S1 includes:

s11, acquiring signal elements in each column of data in the time-frequency diagram and a row index of each signal element; the signal elements are elements with a value of 1 in the time-frequency diagram.

S12, traversing the signal elements in each column of data by columns, and calculating first distance values of adjacent signal elements; the first distance value is an absolute value of a difference of row indices of the adjacent signal elements; when the first distance value is not larger than a first threshold value, determining that the adjacent signal elements belong to the same signal; determining that the adjacent signal elements belong to different signals when the first distance value is greater than a first threshold.

And S13, counting the number of signals in each column of data.

Specifically, one column in the time-frequency diagram is selected, a row index set of signal elements with element values equal to 1 on the current column is obtained and is marked as index _1, and N is used_iRepresenting the number of signals; when index _1 is null, it indicates that the column has no signal element, and the number of signals N is_i0; if index _1 ≠ null, it indicates that the column has signal element, and the number of signals N_iIs set to 1, i.e. N_i1. Where i is the column number. Traversing index _1, starting traversing from the 1 st row index, if the first distance value between the next row index and the current row index is less than or equal to a first threshold value, considering that the signal elements corresponding to the current row index and the next row index belong to the same signal, and continuing traversing; n if a first distance value between a next row index and a current row index is greater than a first threshold value_i＝N_iAnd +1, the number of the signals is added by one, and the traversal is continued by taking the next row index as a starting point until index _1 is traversed. And traversing each column in the time-frequency diagram according to the method, and counting the number of signals of data of each column.

As an example, if the data on a certain column is "001100100010000101" and the first threshold is 3, for example, it can be determined that there are 3 signals on this column, respectively, "11001", "1", "101".

In this embodiment, because the data is subjected to validity estimation when the column data of the time-frequency diagram is processed, the signal elements close to each other are regarded as the same signal, and the number of signals in each column is obtained, instead of directly judging the number of signals in each column according to the value in the time-frequency diagram, which is beneficial to reducing the influence of interference on the statistics of the number of signals.

In one embodiment, as shown in fig. 4, the step S2 includes:

s21, determining the number of columns with the same number of signals according to the number of each signal;

s22, multiplying the number of each signal by the corresponding column number to obtain the product result value of the number of each signal;

and S23, determining the number of the signals corresponding to the maximum product result value as the number of the frequency hopping network stations.

In particular, the statistics have the same number of signals N for all columns_iThe number of columns of (i.e. the number of signals N)_iThe number of occurrences of each column in the time-frequency diagram. Suppose that the set of the number of signals appearing in the time-frequency diagram is W ═ W₁,…,w_n]The number of columns, i.e., the number of occurrences, per number of signals is C ═ C₁,…,c_n]. Calculating W C ═ W₁c₁,…,w_nc_n]W is the number of hop-net stations corresponding to the maximum value of the multiplication result values of W × C.

In this embodiment, the number of frequency hopping network stations is determined by weighting the number of signals appearing in all the columns with the number of columns having the same number of signals. Therefore, the number of the frequency hopping network stations can be accurately determined when the multiple frequency hopping network stations are mixed.

The technical solution of step S2 is described in detail below with reference to a specific example.

As an example, if the numerical value on a certain column is "001100100010000101" and the first threshold value is 3, it may be determined that there are 3 signals on this column, respectively, "11001", "1", "101", according to step S1.

If the frequency bandwidth occupied by each element is 10KHz, the signal bandwidth of "11001" is 5 × 10KHz to 50KHz, "1" is 1 × 10KHz to 10KHz, and "101" is 3 × 10KHz to 30 KHz.

If the data in the time-frequency diagram has 10 rows, and the number of signals in 10 rows is (4, 2, 4, 3, 2, 1, 2, 3), then in 10 rows of data:

the number of signals is 4, and appears in 3 columns, and respectively appears in 1 st column, 3 rd column and 4 th column, and the product result value of weighted calculation is as follows: 4, 3-12;

the number of signals is 3, and appears in 2 columns, respectively in 5 th and 10 th columns, and the product result value of the weighted calculation is: 3 x 2 ═ 6;

the number of signals is 2, appears 4 times in 4 columns, respectively appears in 2 nd, 6 th, 7 th and 9 th columns, and the product result value of the weighted calculation is: 2 x 4 ═ 8;

the number of signals is 1 occurrence, in column 1, in column 8, weighted by the product result value of the calculation: 1-1.

Among the product result values of the above-described weighting calculation, the largest product result value is 12, and the number of corresponding signals is 4, and therefore, it is determined that the number of hop mesh stations is 4.

In this embodiment, in the prior art, since the signal is not effectively determined, that is, if a certain column has "0", two "1" adjacent to "0" are considered to belong to different signals, which is prone to generate erroneous determination, and is not beneficial to determining the broadband frequency hopping signal. When estimating the number of frequency hopping network stations, the prior art directly adopts the effective value with the largest occurrence number as the final effective value, that is, if the prior art is adopted to judge the above examples, the result with the number of frequency hopping network stations of 2 can be obtained, the result obtained by the method in the prior art may be different from the actual number of network stations, because the number of signals obtained by some columns of calculation is less than the actual number due to interference in a time-frequency diagram, and when counting the number of frequency hopping network stations, the number of occurrences of signals corresponding to the actual number of frequency hopping network stations is less, and the estimated number of frequency hopping network stations is smaller. The problem that the number of the estimated frequency hopping network stations is small can be solved by adopting a weighting method, because the number of the signals on each column is only possibly misjudged to be less and not misjudged to be more, the larger the value of the number of the signals is, the more credible the value of the number of the signals is, and the number of the signals can be used as a weight coefficient.

In an embodiment, in the step S3, the effective signal extraction is performed on each row of data in the time-frequency diagram, so as to obtain all the effective signals in the time-frequency diagram.

The definition of the effective signal is that the signal which is on the horizontal axis of a single frequency of the time-frequency diagram and lasts for a certain effective length along the time domain is defined as the minimum unit of the subsequent processing.

As shown in fig. 5, the step S3 includes:

s31, acquiring signal elements in each row of data in the time-frequency diagram and a column index of each signal element; the signal element is an element having a value of 1.

S32, traversing the signal elements in each row of data line by line, and calculating a second distance value of the adjacent signal elements; the second distance value is an absolute value of a difference of column indices of the adjacent signal elements; when the second distance value is not larger than a second threshold value, determining that the adjacent signal elements belong to the same signal; determining that the adjacent signal elements belong to different signals when the second distance value is greater than a second threshold.

And S33, obtaining all effective signals in the time-frequency diagram according to the signals of each row of data.

Illustratively, the second distance value is an absolute value of a difference of column indices of adjacent signal elements (having a value of 1). Setting a second threshold value to be 4, and determining that the adjacent signal elements belong to the same signal when the second distance value is not greater than 4; determining that the neighboring signal elements belong to different signals when the second distance value is greater than 4. The embodiment judges whether two signal elements belong to the same signal according to whether the distance between the two signal elements is greater than the threshold value, and can effectively identify the signal in each row of data.

In a specific embodiment, step S33 includes:

s331, acquiring signals of each row of data, and calculating the effective length of each signal; the effective length is the absolute value of the difference of the column indices of the signal elements at the two endpoints of the signal.

And S332, when the effective length of the signal is larger than a third threshold value, determining that the signal is an effective signal.

And S333, counting to obtain all effective signals in the time-frequency diagram.

Illustratively, the third threshold is set to 4, and when the effective length of the signal is greater than 4, the signal is determined to be an effective signal.

If the data for a row is "1010000101010000011".

Determining that the adjacent signal elements belong to the same signal according to the condition that the second distance value is not greater than 4; when the second distance value is greater than 4, determining that the adjacent signal elements belong to different signals; it is possible to obtain: this row has 3 signals, respectively: 101. 10101, 11.

In the above 3 signals (101, 10101, 11) in the row, only if the effective length of the signal is 10101 is greater than 4, the signal 10101 is determined to be a valid signal, and the valid signal is retained; the effective length of signals 101 and 11, which are considered to be interfering signals, is less than 4, and is discarded. The present embodiment further eliminates the influence of interference by determining whether a signal is a valid signal or an interference signal according to whether the effective length of the signal is greater than a third threshold.

In one embodiment, as shown in fig. 6, the step S4 includes:

s41, obtaining the length value set of the effective signals, wherein the length value set of the effective signals is the set of all the effective length values of the effective signals.

Specifically, the method comprises the following steps:

set the length value set of the valid signal to be T:

T＝[T₁,..T_i,.,T_L]

wherein, T_iIs the effective length of the ith valid signal, L is the number of valid signals, i ≦ L.

S42, traversing each effective length value in the length value set, and calculating the length difference value of each two effective length values.

Specifically, the length difference T of every two effective length values:

T＝|T_i-T_j| (3)

wherein, T_iAnd T_jRespectively representing the ith and jth effective length values.

S43, when the length difference is not larger than a fourth threshold, determining that the length difference is the same-class signal difference of the corresponding effective length value;

setting a fourth threshold value as th _ cluster;

when the effective length value T of an effective signal_iWith the length value T of another active signal_jWhen the length difference value T satisfies the following formula (4), the effective length value T is obtained_iAnd T_jI.e. the difference in length of said difference in length greater than a fourth threshold is not taken as the effective length value T_iThe like signal difference.

T＝|T_i-T_j|≤th_cluster (4)

Effective length value T of effective signal_iWith the length value T of another active signal_jWhen the formula (4) is satisfied, the signals are considered to be signals of the same type, namely, signals under the same frequency hopping network station, otherwise, the signals are not. Namely: and comparing the difference between the length values of the two effective signals with a fourth threshold, and when the difference between the length values of the two effective signals is not more than the fourth threshold th _ cluster, considering the two effective signals to be signals under the same frequency hopping network station, so as to obtain the difference value of the similar signals of each effective length value.

S44, determining the weight of each effective length value according to each effective length value and the related signal difference value of the same type.

In a particular embodiment, the weight is proportional to the effective length value and the weight is inversely proportional to the absolute value of the homogeneous signal difference.

Illustratively, for each valid messageNumber length value T_iSetting the corresponding initial weight value W_i＝0。

Obtaining effective signal length value T_iThe effective length value of the effective signal and the difference value of the same kind of signal are utilized to update the weight value W according to the formula (5)_i：

W_i＝W_i+2*(th_cluster-|T_i-T_j|)+0.01*T_i (5)

And records the index [ i ] of the valid signal₁,...,i_ci](including itself).

Specifically, assuming that it is determined that the signals under the same hop network station as the effective signal a have an effective signal B and an effective signal C, respectively, that is, the difference between the effective length value Ta corresponding to the effective signal a and the effective length value Tb corresponding to the effective signal B, and the difference between the effective length value Ta corresponding to the effective signal a and the effective length value Tc corresponding to the effective signal C both satisfy formula (4), the weight of the effective length value Ta is:

W_a＝2*(th_cluster-|T_a-T_b|)+0.01*T_a+2*(th_cluster-|T_a-T_c|)+0.01*T_a

after each effective signal in the length value set T of the effective signal is judged, a weight value set W ═ W corresponding to the length set T of the effective signal is obtained₁,...,W_L]W in the set of weights_iFor a corresponding effective length T_iThe weight of (c).

S45, determining a clustering reference length value according to the weight of the effective length value in the length value set, and clustering by taking the effective signal corresponding to the clustering reference length value as a clustering reference signal; and obtaining an effective signal set corresponding to each frequency hopping network station until the clustering times are equal to the number of the frequency hopping network stations.

Specifically, according to the weight of the effective length value in the length value set, the maximum value W of the weight value in the weight value set W is determined_mThe effective length value of the corresponding effective signal is determined as a clustering reference length value, i.e.

Taking the weight value set W ═ W₁,...,W_L]Maximum value W of medium weight value_mDetermining the effective length value T corresponding to the effective length value_mThe effective signal corresponding to the clustering reference length value is used as a clustering reference signal for clustering; and obtaining an effective signal set corresponding to each frequency hopping network station until the clustering times are equal to the number of the frequency hopping network stations. It should be noted that after each clustering is completed, the weight values corresponding to the effective signals that have been clustered are deleted from the weight value set W, and then the maximum value W is determined from the deleted weight value set W_m', determining its corresponding effective length value T_m' is clustering reference length value, and then clustering is carried out, and so on.

The weight value W_iThe length difference of two similar effective signals and the length value of the effective signals are related, the weight is in direct proportion to the effective length value, and the weight is in inverse proportion to the difference of the similar signals. When the effective signal length is longer, the occurrence frequency of the effective signal with shorter length is less in the same time, and at the moment, the effective length value of the effective signal is incorporated into the weight value calculation, so that when the long-period signal and the short-period signal appear together, the long-period signal can be clustered, and the long-period signal cannot be clustered due to the fact that the number of the effective signals corresponding to the long-period signal is less.

In this embodiment, all the effective signals are clustered based on the number of the frequency hopping network stations, so as to obtain an effective signal set corresponding to each frequency hopping network station. In the clustering process, only the effective signals are used as basic units, the effective length values of the effective signals are used as features for clustering, and the basic units are easy to extract; and the reference length value of each clustering is determined by adopting a weighting mode, so that the problems that the broadband of the broadband network platform is wider, a single network platform cannot be detected easily, and long-period signals are few in occurrence frequency and difficult to detect can be solved effectively.

In an alternative embodiment, as shown in fig. 7, the step S5 includes:

s51, sequencing the effective signals under the same frequency hopping network station according to the starting time, and determining the frequency hopping time of each frequency hopping network station;

s52, determining the frequency hopping frequency of each frequency hopping network station according to the frequency of the effective signal corresponding to each frequency hopping moment under the same frequency hopping network station;

and S53, determining the frequency hopping period of each frequency hopping network station according to the center time of each frequency hopping time under the same frequency hopping network station.

Each valid signal is assigned to a corresponding hop net station through clustering based on the valid lengths of the valid signals. For a single hop-net station, estimating hop-net station parameters may be implemented according to the 3 attributes of the active signal involved, the hop-net station parameters including: frequency hopping period, frequency hopping frequency, and frequency hopping time.

Setting an initial hop period T₁The calculation formula of (2) is as follows:

in the above equation, Δ t is the time resolution of the time-frequency diagram. The start time index set, the end time index set and the frequency index set of the effective signal contained in each frequency hopping network station are respectively marked as

Wherein L is_nIs the number of valid signals contained by the nth hop station.

In an alternative embodiment, the step 51 comprises:

and S511, summarizing the starting time corresponding to the effective signals under the same frequency hopping network station to obtain a starting time index set S. It should be noted that, if there are multiple hop mesh stations in the time-frequency diagram, multiple start time index sets, end time index sets, and frequency index sets are obtained accordingly.

S512, sequencing the initial time index set according to time sequence to obtain a sequenced initial time index set.

Specifically, the start time index set S is ordered according to time sequence to obtain an ordered start time index set

S513, differentiating the sorted initial time index sets to obtain a first differential result set.

Specifically, the sorted start time index set is set

Carrying out difference to obtain a first difference result

And S514, deleting the starting time corresponding to the differential value from the sorted starting time index set to obtain the frequency hopping time of each frequency hopping network station when the differential value in the first differential result set does not meet the frequency hopping time error condition.

Judging whether the first difference result S 'meets the error condition of the frequency hopping time, and if the first difference result S' meets the error condition of the frequency hopping time, obtaining the frequency hopping time of each frequency hopping net station; otherwise, when the difference value in the first difference result set does not meet the error condition of the frequency hopping time, deleting the starting time corresponding to the difference value.

In particular, for the element S in the first difference result S_i': if mod(s)_i′/T₁,1)>0.2 and mod(s)_i′/T₁,1)<0.8, description

The (i + 1) th element in (b) is an interference signal, which is rejected. Where mod (A/B,1) denotes A divided by B and truncating the integer part leaves only the fractional part. Furthermore, if s_i' is interference, s ' is ignored '_i+1Does not perform the above determination, and considers that the (i + 2) th element is a valid signal. And obtaining the starting time corresponding to the differential value when the error condition of the frequency hopping time is met in the first differential result set, and obtaining the frequency hopping time of each frequency hopping net station.

By way of illustration, there is illustrated: for example, if there are 8 active signals, the start time index set S of a particular hop-net station is [1,10,20,20,40,25,5,10 ].

The frequency hopping signal period is T obtained by the above equation (6)₁Time resolution was 10 x.

Reordering the start time indexes in the order from small to large to obtain a set of ordered start time indexes

Set the sorted start time indexes

After the difference is made, a first difference result S' is obtained as [4,5,0,10,0,5,15]。

For the element S in S_i', calculate mod(s)_i′/T₁,1)＝[0.4,0.5,0,0,0,0.5,0.5]Consider mod(s)_i′/T₁1) if the 1 st and 6 th elements in the result satisfy the error condition of the frequency hopping time, the sorted initial time index set

2, 7 elements [5 ]]、[25]And if the difference value is an interference signal, the interference signal needs to be removed, so that the starting time corresponding to the difference value when the error condition of the frequency hopping time is met is obtained in the first difference result set, and the frequency hopping time of each frequency hopping network station is obtained.

In an alternative embodiment, the step 52 includes:

s521, judging whether the number of effective signals corresponding to the frequency hopping time under the same frequency hopping network station is greater than one.

For a frequency hopping moment, a plurality of valid signals may be included, and interference rejection is required.

S522, when the number of the effective signals corresponding to a frequency hopping moment is more than one, judging the same type of signals according to the frequency of all the effective signals corresponding to the frequency hopping moment according to a frequency threshold.

If some absolute values are smaller than the preset frequency threshold, the corresponding two frequencies belong to the same type of signals, and the number of the signals which are owned by each frequency and similar to the frequency is recorded as N_iI 1.. M, M is the number of valid signals included at the current hopping time. Find the maximum value N among N_maxSelecting N_maxAnd selecting the corresponding frequency as a reserved frequency to form a frequency set f, and rejecting the frequency set f.

Illustratively, for example, the set of frequencies of the active signal contained at a single hopping instant is [300,310,290,350,400 ]. If the frequency threshold is set to be 20, the number of the same type of effective signals corresponding to each effective signal is [3,3,3,1,1], a signal with the number of the same type of effective signals being 3, that is [300,310,290], that is, the extracted [300,310,290] is selected as the reserved frequency, and a frequency set f is formed. [350,400] are interference frequencies to be rejected.

In one case, when the number of the same type of effective signals corresponding to a plurality of effective signals at a single frequency hopping time is 1, that is, each frequency is different from other frequencies and belongs to the same type, in this case, the difference between each frequency and the frequencies of all the effective signals of the network station is calculated, and then an absolute value is obtained, if the absolute value is smaller than a configured set frequency threshold, the corresponding two frequencies are considered to belong to the same type, and the number of the frequencies owned by each frequency and the same type of frequencies is recorded as J_iI 1.. M, M is the number of valid signals. Find the maximum value J among J_max，J_i1, M equals J_maxAnd selecting the corresponding frequency as a reserved frequency to form a frequency set f, and rejecting the frequency set f.

As an example, for example, the frequency set of valid signals included in a single frequency hopping time instant is [300,350,450], the frequency threshold is set to 20, the number of valid signals of the same type corresponding to each valid signal is [1,1,1], the frequency set of valid signals of the entire frequency hopping network station is [100,300,450,350,310,200,320,400,500,200,400], the frequency threshold is set to 20, the number of signals of the same type corresponding to each signal at this time instant is [3,1,1], a signal of the same type number of signals is [3 ], that is, [300] is taken as a reserved frequency, and [350,450] is an interference frequency to be removed.

And S523, determining the frequency hopping frequency of each frequency hopping network station by taking the frequency average value of the effective signals with the largest number of the same type of signals as the frequency of the effective signal corresponding to the frequency hopping time.

Specifically, the frequency average value of the effective signal with the largest number of similar signals is used as the frequency of the effective signal corresponding to the frequency hopping time, and the frequency hopping frequency of each frequency hopping network station is determined. The frequency of the effective signal corresponding to the frequency hopping moment is calculated according to the formula (7):

in the above formula, f_iThe frequency is the ith frequency in the interference-removed frequency set contained in the current frequency hopping moment, and N is the number of frequencies in the interference-removed frequency set contained in the current frequency hopping moment.

The embodiment eliminates the interference under the condition that a plurality of effective signals exist at a single frequency hopping moment, and further improves the accuracy of parameter estimation.

Further, the center time of the effective signal corresponding to the frequency hopping time is calculated according to the formula (8):

wherein t is_iThe central time of the effective signal corresponding to the ith frequency in the interference-removed frequency set contained in the current frequency hopping time, and N is the number of the frequencies in the interference-removed frequency set contained in the current frequency hopping time.

In an alternative embodiment, the step 53 comprises:

and S531, differentiating the center time corresponding to each frequency hopping time under the same frequency hopping network station to obtain a second differential result set.

And S532, in the combination of the obtained second difference results, eliminating the difference value larger than a fifth threshold value to obtain a third difference result set.

Specifically, if the difference value in the second difference result set is greater than the fifth threshold, it indicates that the frequency hopping time is lost or an interference signal is mixed between two frequency hopping times, so that the difference value greater than the fifth threshold needs to be removed from the obtained second difference result to obtain a third difference result set.

And S533, averaging the difference values in the third difference result set to obtain the frequency hopping period of the frequency hopping network station.

The frequency hopping period calculated by the present embodiment is more accurate.

In this embodiment, relevant parameters of each hop mesh station are determined according to effective signals contained in each hop mesh station, and in the process of calculating parameters of the hop mesh stations, the condition of hop missing or interference introduction can be judged, so that the accuracy of estimation at the hop time and the accuracy of a hop period are improved; interference introduced in the clustering process can be eliminated, and the accuracy of the frequency corresponding to the frequency hopping moment is improved.

It should be noted that the frequency hopping time, the frequency hopping frequency, and the frequency hopping period of each hop mesh station are calculated from the start time index set, the end time index set, and the frequency index set of the corresponding valid signal under the hop mesh station.

According to the step S532, a hopping frequency set can be obtained for each hop mesh station. But some of the frequencies are repeated, and an initial frequency hopping frequency set needs to be extracted from the repeated frequencies.

In an alternative embodiment, step S523 includes: for a frequency hopping network station, taking the frequency average value of the effective signals with the largest number of the same type signals as the frequency of the effective signals corresponding to the frequency hopping time;

and performing initial frequency hopping frequency set estimation on a frequency hopping frequency set of each frequency hopping time under one frequency hopping network station to obtain an initial frequency hopping frequency set so as to determine the frequency hopping frequency of the frequency hopping network station.

The initial frequency hopping frequency set estimation is used for deleting the frequency which repeatedly appears in the frequency hopping frequency set, and the specific process is as follows:

(1) for a hop mesh station, the resulting set of hopping frequencies is hop _ freq _ get.

(2) The error range freq _ range of the frequency estimation is set.

(3) A value of freq _ buffer storing hop _ freq _ get is set as an initial value.

(4) And (3) subtracting the first value of the freq _ buffer from all the subsequent values in sequence to obtain an absolute value as a frequency error, recording a frequency value when the frequency error is less than or equal to freq _ range, and recording the index of the frequency value.

(5) After the first comparison is completed, averaging and recording the recorded frequency values, deducting the recorded frequency values according to the recorded indexes, reducing the length of the freq _ buffer, using the freq _ buffer as a new freq _ buffer, and continuing the processes (4) and (5) until the freq _ buffer is empty.

(6) The final number of times of comparison is the number N _ hop _ freq _ group of the frequency hopping frequency set, and the corresponding averaged frequency sequence is the initial frequency hopping frequency set hop _ freq _ group.

Based on the same concept, as shown in fig. 8, a second aspect of the embodiments of the present disclosure provides a device for estimating parameters of a frequency hopping network station, where the device is applied to the method for estimating parameters of a frequency hopping network station in any of the embodiments, and the device includes: the device comprises an estimation module 10, a net station number determination module 20, an extraction module 30, a clustering module 40 and a determination module 50; wherein:

the estimation module 10 is configured to perform signal validity estimation on each line of data in the time-frequency diagram, and determine the number of signals in each line of data;

the network station number determining module 20 is configured to determine the number of frequency hopping network stations according to a product of the number of each signal in all the columns and the number of columns with the same number of signals;

the extraction module 30 is configured to extract an effective signal from each row of data in the time-frequency diagram, and acquire all effective signals in the time-frequency diagram;

the clustering module 40 is configured to cluster all effective signals based on the number of the frequency hopping network stations to obtain an effective signal set corresponding to each frequency hopping network station;

the determining module 50 is configured to perform parameter extraction on the effective signals included in the effective signal set corresponding to each of the frequency hopping network stations, and determine the relevant parameters of each of the frequency hopping network stations.

In particular, the estimation module 10 is specifically configured to:

acquiring signal elements in each line of data in a time-frequency diagram and a row index of each signal element; the signal elements are elements with a value of 1 in the time-frequency diagram;

traversing the signal elements in each column of data according to columns, and calculating first distance values of adjacent signal elements; the first distance value is an absolute value of a difference of row indices of the adjacent signal elements; when the first distance value is not larger than a first threshold value, determining that the adjacent signal elements belong to the same signal; determining that the adjacent signal elements belong to different signals when the first distance value is greater than a first threshold;

and counting the number of signals in each column of data.

The network station number determining module 20 is specifically configured to:

determining the number of columns with the same number of signals according to the number of each signal;

multiplying the number of each signal by the corresponding column number to obtain a product result value of the number of each signal;

and determining the number of signals corresponding to the maximum product result value as the number of the frequency hopping network stations.

The extraction module 30 includes:

the line index acquisition unit is used for acquiring signal elements in each line of data in the time-frequency diagram and a column index of each signal element; the signal element is an element with a value of 1;

the traversal judging unit is used for traversing the signal elements in each row of data line by row and calculating a second distance value of the adjacent signal elements; the second distance value is an absolute value of a difference of column indices of the adjacent signal elements; when the second distance value is not larger than a second threshold value, determining that the adjacent signal elements belong to the same signal; determining that the adjacent signal elements belong to different signals when the second distance value is greater than a second threshold;

and the effective signal acquisition unit is used for acquiring all effective signals in the time-frequency diagram according to the signals of each row of data.

The valid signal acquisition unit is specifically configured to:

acquiring signals of each row of data, and calculating the effective length of each signal; the effective length is an absolute value of a difference of column indices of second signal elements at two endpoints of the signal;

when the effective length of the signal is larger than a third threshold value, determining the signal as an effective signal;

and counting to obtain all effective signals in the time-frequency diagram.

The clustering module 40 is specifically configured to:

acquiring a length value set of the effective signals, wherein the length value set of the effective signals is a set of effective length values of all the effective signals;

traversing each effective length value in the length value set, and calculating the length difference value of each two effective length values;

when the length difference is smaller than a fourth threshold, determining that the length difference is a similar signal difference of a corresponding effective length value;

determining a weight for each said effective length value based on each said effective length value and a related signal difference of the same type;

determining a clustering reference length value according to the weight of the effective length value in the length value set, and clustering by taking an effective signal corresponding to the clustering reference length value as a clustering reference signal; and obtaining an effective signal set corresponding to each frequency hopping network station until the clustering times are equal to the number of the frequency hopping network stations.

Wherein the weight is proportional to the effective length value and the weight is inversely proportional to the absolute value of the homogeneous signal difference.

The determination module 50 includes:

the frequency hopping time calculation unit is used for sequencing effective signals under the same frequency hopping network station according to the starting time and determining the frequency hopping time of each frequency hopping network station;

the frequency hopping frequency calculation unit is used for determining the frequency hopping frequency of each frequency hopping network station according to the frequency of the effective signal corresponding to each frequency hopping moment under the same frequency hopping network station;

and the frequency hopping cycle calculation unit is used for determining the frequency hopping cycle of each frequency hopping network station according to the center time of each frequency hopping time under the same frequency hopping network station.

The frequency hopping time calculation unit is specifically configured to:

summarizing the starting time corresponding to the effective signals under the same frequency hopping network station to obtain a starting time index set;

sequencing the initial time index set according to time sequence to obtain a sequenced initial time index set;

differentiating the sorted initial time index sets to obtain a first differential result set;

and deleting the starting time corresponding to the differential value from the sorted starting time index set to obtain the frequency hopping time of the frequency hopping network station when the differential value in the first differential result set does not meet the frequency hopping time error condition.

The frequency hopping frequency calculation unit is specifically configured to:

judging whether the number of effective signals corresponding to the frequency hopping time under the same frequency hopping network station is greater than one;

when the number of the effective signals corresponding to a frequency hopping moment is more than one, judging the same type of signals according to the frequency of all the effective signals corresponding to the frequency hopping moment by a frequency threshold;

and determining the frequency hopping frequency of the frequency hopping network station by taking the frequency average value of the effective signals with the largest number of the same kind of signals as the frequency of the effective signal corresponding to the frequency hopping time.

The frequency hopping cycle calculation unit is specifically configured to:

differentiating the center time corresponding to each frequency hopping time under the same frequency hopping network station to obtain a second differential result set;

in the obtained second difference result combination, eliminating a difference value larger than a fifth threshold value to obtain a third difference result set;

and averaging the difference values in the third difference result set to obtain the frequency hopping period of the frequency hopping network station.

In the embodiment, the estimation module is used for carrying out signal effectiveness estimation on each line of data in the time-frequency diagram, and the number of signals of each line of data is determined; the network station number determining module determines the number of frequency hopping network stations according to the product of the number of each signal in all the columns and the number of the columns with the same number of the signals; the extraction module extracts effective signals of each row of data in the time-frequency diagram to obtain all the effective signals in the time-frequency diagram; the clustering module clusters all effective signals based on the number of the frequency hopping network stations to obtain an effective signal set corresponding to each frequency hopping network station; the determining module extracts parameters of effective signals contained in an effective signal set corresponding to each frequency hopping network station and determines related parameters of each frequency hopping network station. The method and the device have the advantages that the validity of each line of data is estimated, the number of the frequency hopping network stations is determined by the product of the number of each signal in all the lines and the number of the lines with the same number of the signals, the valid signals of each line of data are extracted, the number of the network stations and the valid signals can be accurately determined under the condition that the more complex broadband frequency hopping signals and the multi-frequency hopping network stations are mixed, and the accuracy of the parameter estimation of the frequency hopping network stations is improved.

It should be noted that the embodiments of the apparatus and the method for estimating parameters of a frequency hopping network station belong to the same concept, and specific implementation processes thereof are described in detail in the embodiments of the method, and technical features in the embodiments of the method are correspondingly applicable in the embodiments of the apparatus for estimating parameters of a frequency hopping network station, which are not described herein again.

Further, based on the same concept, a third aspect of the embodiments of the present disclosure provides a frequency hopping monitoring device, as shown in fig. 9, where the frequency hopping monitoring device 900 includes: a memory 902, a processor 901 and one or more computer programs stored in the memory 902 and executable on the processor 901, wherein the memory 902 and the processor 901 are coupled together by a bus system 903, and the one or more computer programs are executed by the processor 901 to implement the steps of the method for estimating parameters of a hop network station provided in the first aspect of the embodiment of the present disclosure.

The method disclosed in the foregoing embodiment of the present disclosure may be applied to the processor 901, or implemented by the processor 901. The processor 901 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be implemented by instructions in the form of hardware integrated logic circuits or software in the processor 901. The processor 901 may be a general purpose processor, a DSP, or other programmable logic device, discrete gate or transistor logic device, discrete hardware components, or the like. The processor 901 may implement or perform the methods, steps and logic blocks disclosed in the embodiments of the present disclosure. A general purpose processor may be a microprocessor or any conventional processor or the like. The steps of the method disclosed in the embodiments of the present disclosure may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software modules may be located in a storage medium located in the memory 902, and the processor 901 reads the information in the memory 902 and performs the steps of the foregoing method in combination with the hardware thereof.

It is to be understood that the memory 902 of the disclosed embodiments may be either volatile memory or nonvolatile memory, and may include both volatile and nonvolatile memory. Among them, the nonvolatile Memory may be a Read-Only Memory (ROM), a Programmable Read-Only Memory (PROM), an Erasable Programmable Read-Only Memory (EPROM), an Electrically Erasable Programmable Read-Only Memory (EEPROM), a magnetic Random Access Memory (FRAM), a magnetic Random Access Memory (Flash Memory) or other Memory technologies, a Compact disc Read-Only Memory (CD-ROM), a Digital Versatile Disc (DVD), or other optical disc storage, magnetic cartridge, magnetic tape, magnetic Disk storage, or other magnetic storage devices; volatile Memory can be Random Access Memory (RAM), and by way of exemplary and not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Static Random Access Memory (SSRAM), Dynamic Random Access Memory (DRAM), Synchronous Dynamic Random Access Memory (SDRAM), Double Data Rate Synchronous Dynamic Random Access Memory (DDRSDRAM), Double Data Rate Synchronous Random Access Memory (ESDRAM), Synchronous Link Dynamic Random Access Memory (SLDRAM), Direct Memory bus Random Access Memory (DRRAM). The memories described in the embodiments of the present disclosure are intended to comprise, without being limited to, these and any other suitable types of memory.

It should be noted that the embodiments of the frequency hopping monitoring device and the embodiments of the method belong to the same concept, and specific implementation processes thereof are described in the embodiments of the method, and technical features in the embodiments of the method are correspondingly applicable in the embodiments of the frequency hopping monitoring device, which is not described herein again.

In an exemplary embodiment, a fourth aspect of the embodiments of the present disclosure provides a computer storage medium, specifically a computer readable storage medium, for example, the memory 902 stores a computer program, where the computer storage medium stores one or more programs of a method for estimating parameters of a hop network station, and the one or more programs of the method for estimating parameters of a hop network station are executed by the processor 901 to implement the steps of the method for estimating parameters of a hop network station provided in the first aspect of the embodiments of the present disclosure.

It should be noted that, the program embodiment of the method for estimating parameters of a frequency hopping network station on the computer-readable storage medium and the method embodiment belong to the same concept, and the specific implementation process is described in detail in the method embodiment, and the technical features in the method embodiment are applicable to the embodiments of the computer-readable storage medium, which are not described herein again.

It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.

Finally, it should be noted that: the above examples are only intended to illustrate the technical solutions of the present disclosure, not to limit them; within the idea of the present disclosure, also technical features in the above embodiments or in different embodiments may be combined, steps may be implemented in any order, and there are many other variations of the different aspects of the present disclosure as described above, which are not provided in detail for the sake of brevity; although the present disclosure has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present disclosure.

Claims

1. A method for estimating parameters of a frequency hopping network station, the method comprising:

determining the number of the frequency hopping network stations according to the product of the number of each signal in all the columns and the number of the columns with the same number of the signals;

2. The method of claim 1, wherein the signal effectiveness estimation is performed on each line of data in the time-frequency diagram, and the number of signals in each line of data is determined; the method comprises the following steps:

traversing the signal elements in each column of data by column, and calculating a first distance value of adjacent signal elements; the first distance value is an absolute value of a difference of row indices of the adjacent signal elements;

when the first distance value is not larger than a first threshold value, determining that the adjacent signal elements belong to the same signal;

determining that the adjacent signal elements belong to different signals when the first distance value is greater than a first threshold;

and counting the number of signals in each column of data.

3. The method of claim 1 or 2, wherein the number of hop netlists is determined by multiplying the number of each signal in all the columns by the number of columns having the same number of signals; the method comprises the following steps:

4. The method according to claim 1, wherein the effective signal extraction is performed on each row of data in the time-frequency diagram to obtain all effective signals in the time-frequency diagram; the method comprises the following steps:

acquiring signal elements in each row of data in the time-frequency diagram and a column index of each signal element; the signal element is an element with a value of 1;

traversing the signal elements in each row of data line by row, and calculating a second distance value of the adjacent signal elements; the second distance value is an absolute value of a difference of column indices of the adjacent signal elements;

when the second distance value is not larger than a second threshold value, determining that the adjacent signal elements belong to the same signal;

determining that the adjacent signal elements belong to different signals when the second distance value is greater than a second threshold;

and obtaining all effective signals in the time-frequency diagram according to the signals of each row of data.

5. The method of claim 4, wherein obtaining all valid signals in the time-frequency diagram according to the signals of each row of data comprises:

acquiring signals of each row of data, and calculating the effective length of each signal; the effective length is an absolute value of a difference of column indices of signal elements at two endpoints of the signal;

and counting to obtain all effective signals in the time-frequency diagram.

6. The method of claim 1, wherein the clustering is performed on all valid signals based on the number of hop netowrk stations to obtain a valid signal set corresponding to each hop netowrk station; the method comprises the following steps:

obtaining a length value set of the effective signals, wherein the length value set of the effective signals is a set of effective length values of all the effective signals;

when the length difference is not larger than a fourth threshold, determining that the length difference is the same-class signal difference of the corresponding effective length value;

determining a weight for each effective length value based on each effective length value and a related signal difference of the same type;

determining a clustering reference length value according to the weight of an effective length value corresponding to each effective length value in the length value set, and clustering by taking an effective signal corresponding to the clustering reference length value as a clustering reference signal; and obtaining an effective signal set corresponding to each frequency hopping network station until the clustering times are equal to the number of the frequency hopping network stations.

7. The method of claim 6 wherein said weight is proportional to said effective length value and wherein said weight is inversely proportional to the absolute value of said homogeneous signal difference.

8. The method according to claim 1, wherein the parameters of the effective signals included in the effective signal set corresponding to each hop networkable are extracted to determine the relevant parameters of each hop networkable; the method comprises the following steps:

sequencing effective signals under the same frequency hopping network station according to the starting time, and determining the frequency hopping time of each frequency hopping network station;

determining the frequency hopping frequency of each frequency hopping network station according to the frequency of the effective signal corresponding to each frequency hopping moment under the same frequency hopping network station;

and determining the frequency hopping period of each frequency hopping network station according to the central time of each frequency hopping time under the same frequency hopping network station.

9. The method of claim 8, wherein the valid signals under the same hop net station are sorted according to a start time to determine a hop time of each hop net station; the method comprises the following steps:

10. The method according to claim 8, wherein the hopping frequency of each hop mesh station is determined according to the frequency of the valid signal corresponding to each hop time under the same hop mesh station; the method comprises the following steps:

11. The method of claim 8, wherein the hop period of each hop mesh station is determined according to a center time of each hop time under the same hop mesh station; the method comprises the following steps:

12. An apparatus for hop-net-station parameter estimation, the apparatus comprising: the device comprises an estimation module, a network station number determination module, an extraction module, a clustering module and a determination module; wherein:

13. A frequency hopping monitoring device, comprising: memory, processor and computer program stored on the memory and executable on the processor, which when executed by the processor implements the steps of the hop network station parameter estimation method of any of the above claims 1 to 11.

14. A computer-readable storage medium, characterized in that the computer-readable storage medium stores thereon a program of a hop-net-station parameter estimation method, which when executed by a processor, implements the steps of the hop-net-station parameter estimation method of any one of claims 1 to 11.