A high-precision adaptive frequency hopping signal detection method, device and computer equipment

Abstract

The present application discloses a high-precision adaptive frequency hopping signal detection method, device and computer equipment, which relates to the field of radio monitoring technology. The present application adopts a method of detecting pulses line by line, which can realize the detection of frequency hopping signals of any frequency band and any rate, including the detection of multiple frequency hopping signals of different rates mixed together; in addition, the present application can accurately give the relevant parameters of the frequency hopping signal, including the signal strength of each hopping point, the frequency set of the frequency hopping signal, the frequency hopping rate, the duty cycle of the frequency hopping signal, etc. The present application is basically not affected by various interferences in the electromagnetic environment, and realizes high-precision detection in a variety of electromagnetic environments.

Description

Technical Field

[0001] The present application relates to the field of radio monitoring technology, and in particular to a high-precision adaptive frequency hopping signal detection method, device and computer equipment. Background Art

[0002] The development of radio technology and information communication has made frequency hopping communication a widely used communication method. This type of communication has two major characteristics: one is the low interception rate, especially the frequency hopping of broadband spectrum, which reduces the interception frequency of the interceptor's signal; the other is the enhanced reliability of data transmission. It is difficult for wireless communication to ensure that a certain frequency band will not be interfered with for a long time, and it is impossible to predict when interference will occur, let alone the shape and strength of the interference signal. At this time, frequency hopping communication plays a natural role in avoiding interference. If multi-frequency redundant data transmission is adopted, the reliability of data transmission can be further enhanced.

[0003] The widespread application of frequency hopping signals is a new topic for radio spectrum monitoring departments. How to know whether a user has used frequency hopping communication in a certain period of time, what is the frequency range of the frequency hopping signal, what is the frequency hopping frequency set and signal strength, whether it will affect the normal communication of other users in this frequency band, etc., all require spectrum monitoring departments to have technical means to monitor and collect evidence of frequency hopping signals, and better manage and maintain the rational use of radio spectrum by regularly or irregularly monitoring the spectrum occupancy in a certain area.

[0004] A good frequency hopping signal detection algorithm needs to solve the following three problems:

[0005] (1) Adaptability to any frequency band. Whether it is shortwave, ultra-shortwave, microwave, or higher frequency bands, frequency hopping signal detection can be performed without distinction;

[0006] (2) Adaptability to electromagnetic environment and signal strength. The so-called adaptability to electromagnetic environment means that the frequency band used by the frequency hopping signal may have strong interference, such as industrial interference, broadcast signals, public network signals, or users in a certain industry are using this frequency band. The detection algorithm is required to be as little or not affected by these factors as possible. The signal strength requirement is to be able to detect frequency hopping signals under low signal-to-noise ratio.

[0007] (3) Adaptability to frequency hopping rate and frequency hopping signal form. Generally speaking, the industry calls frequency hopping below 100 hops per second low-speed, 100-1000 hops per second medium-speed, and above 1000 hops per second high-speed. Frequency hopping signal form refers to the different signal envelopes and spectrum dispersions of different modulation methods, requiring the detection algorithm to be able to adapt to changes in various signal spectrum forms.

[0008] In addition, the integrity of the time-frequency structure of the frequency hopping signal, the accuracy of related parameters, etc. will also affect the accuracy and reliability of the detection algorithm. However, the existing frequency hopping signal detection technology cannot meet the above detection requirements. Summary of the invention

[0009] In order to reliably detect frequency hopping signals applicable to any frequency band, any frequency hopping rate and frequency hopping signal spectrum morphology, the present application proposes a high-precision adaptive frequency hopping signal detection method, device and computer equipment. The present application greatly adapts to and follows the changes in noise by detecting pulses line by line, does not make any a priori assumptions about the strength and morphology of the noise signal, and avoids interference noise on other spectral lines, thereby making it universal and highly adaptive.

[0010] On the one hand, the present application is implemented through the following technical solutions:

[0011] A high-precision adaptive frequency hopping signal detection method, the detection method comprising:

[0012] Divide the received I and Q data into blocks, and calculate the logarithmic amplitude spectrum of each frame of each data block to form a block two-dimensional logarithmic amplitude spectrum matrix;

[0013] Searching for pulses on each spectrum line in the block two-dimensional logarithmic amplitude spectrum matrix to form an original pulse set;

[0014] Merging adjacent pulses on the same spectral line in the original pulse set that meet the time continuity requirement, calculating and updating the pulse parameter group, forming an updated pulse set and constructing its pulse width histogram curve;

[0015] Searching for all local peak points on the pulse width histogram curve, and recording the positions and values ​​of all peak points exceeding a threshold;

[0016] According to the recorded parameters of each peak point, all pulses meeting the pulse width requirements are screened out from the updated pulse set to form a pulse subset corresponding to each peak point;

[0017] All pulses in each of the pulse subsets are sorted in ascending order according to the starting time, and the pulse with the strongest signal-to-noise ratio is selected from the pulses with the same starting time as the representative pulse at this time point, and all the representative pulses constitute a first updated pulse subset;

[0018] Sort all the pulses in each of the first update pulse subsets in ascending order according to the end time, select the pulse with the strongest signal-to-noise ratio from the pulses with the same end time as the representative pulse at this time point, and all the representative pulses constitute the second update pulse subset;

[0019] All pulses in each of the second update pulse subsets are selected according to a time succession relationship to generate a third update pulse subset, and it is determined whether the set is a frequency hopping signal according to a parameter value of the third update pulse subset.

[0020] In a second aspect, the present application proposes a high-precision adaptive frequency hopping signal detection device, the detection device comprising:

[0021] A calculation unit, wherein the calculation unit divides the received I and Q data into blocks and calculates the logarithmic amplitude spectrum of each frame of each data block to form a block two-dimensional logarithmic amplitude spectrum matrix;

[0022] A first search unit, wherein the first search unit searches for pulses on each spectrum line in the block two-dimensional logarithmic amplitude spectrum matrix to form an original pulse set;

[0023] A merging unit, wherein the merging unit merges adjacent pulses on the same spectral line in the original pulse set that meet the time continuity requirement, calculates and updates the pulse parameter group, forms an updated pulse set and constructs a pulse width histogram curve thereof;

[0024] A second search unit, the second search unit searches for all local peak points on the pulse width histogram curve, and records positions and values ​​of all peak points exceeding a threshold;

[0025] A first screening unit, wherein the first screening unit screens out all pulses meeting the pulse width requirement from the updated pulse set according to the recorded parameters of each peak point, to form a pulse subset corresponding to each peak point;

[0026] a second screening unit, wherein the second screening unit respectively sorts all the pulses in each of the pulse subsets according to the starting time from small to large, and selects the pulse with the strongest signal-to-noise ratio from the pulses with the same starting time as the representative pulse at this time point, and all the representative pulses constitute a first updated pulse subset;

[0027] a third screening unit, wherein the third screening unit respectively sorts all the pulses in each of the first update pulse subsets according to the end time from small to large, and selects the pulse with the strongest signal-to-noise ratio from the pulses with the same end time as the representative pulse at this time point, and all the representative pulses constitute the second update pulse subset;

[0028] a fourth screening unit, wherein the fourth screening unit selects all pulses in each of the second update pulse subsets according to a time succession relationship to generate a third update pulse subset,

[0029] And, an identification unit, wherein the identification unit determines whether the corresponding set is a frequency hopping signal according to the parameter value of each of the third update pulse subsets.

[0030] In a third aspect, the present application proposes a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above method when executing the computer program.

[0031] The present application proposes a high-precision adaptive frequency hopping signal detection method, device and computer equipment, which can detect frequency hopping signals of any frequency band and any rate, including multiple frequency hopping signals of different rates mixed together, by detecting pulses line by line. In addition, the present application can accurately give the relevant parameters of the frequency hopping signal, including the signal strength of each hopping point, the frequency set of the frequency hopping signal, the frequency hopping rate, the duty cycle of the frequency hopping signal, etc. The present application is basically not affected by various interferences in the electromagnetic environment, and realizes high-precision detection in a variety of electromagnetic environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] The drawings described herein are used to provide a further understanding of the embodiments of the present application, constitute a part of the present application, and do not constitute a limitation on the embodiments of the present application. In the drawings:

[0033] Figure 1 A flow chart of the detection method proposed in the embodiment of the present application;

[0034] Figure 2 This is a schematic diagram of the detection device proposed in the embodiment of the present application;

[0035] Figure 3 The following is an example of the detection result of a single-station frequency hopping signal implemented by the embodiment of the present application; wherein (a) represents the pulse width of the first frequency hopping set, the horizontal axis represents the hopping point number, and the vertical axis represents the pulse width of each hopping point; (b) represents the distance distribution diagram between adjacent hopping points of the first frequency hopping set, the horizontal axis represents the hopping point number, and the vertical axis represents the distance between adjacent hopping points; (c) represents the frequency (i.e., frequency count) distribution diagram of the first frequency hopping set, the horizontal axis represents the frequency value, and the vertical axis represents the number of occurrences of the corresponding frequency value;

[0036] Figure 4 This is an example of the detection results of a 100 hop / second signal in a multi-network station implemented by the embodiment of the present application, and the detection results of the other two frequency hopping signals are given in Table 2 and Table 3 respectively; Figure 4 In the figure, (a) represents the pulse width of a 100-hop / second signal, where the horizontal axis represents the hop number and the vertical axis represents the pulse width of each hop; (b) represents the distance distribution diagram between adjacent hops of a 100-hop / second signal, where the horizontal axis represents the hop number and the vertical axis represents the distance between adjacent hops; (c) represents the frequency (i.e., frequency count) distribution diagram of a 100-hop / second signal, where the horizontal axis represents the frequency value and the vertical axis represents the number of times the corresponding frequency value occurs. DETAILED DESCRIPTION

[0037] In order to make the objectives, technical solutions and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with examples and drawings. The illustrative implementation scheme of the present application and its description are only used to explain the present application and are not intended to limit the present application.

[0038] Embodiment 1: In order to realize frequency hopping signal detection of various frequency bands, various frequency hopping rates and frequency hopping signal spectrum forms, and reduce the influence of interference such as electromagnetic environment on detection accuracy, this embodiment proposes a high-precision adaptive frequency hopping signal detection method.

[0039] like Figure 1 As shown, the detection method proposed in this embodiment specifically includes the following steps:

[0040] Step 100, divide the received I and Q data into blocks, calculate the logarithmic amplitude spectrum of each frame of each data block, and form a block two-dimensional logarithmic amplitude spectrum matrix.

[0041] Specifically, step 100 may divide the received I and Q data into blocks according to preset parameters, calculate the logarithmic amplitude spectrum of each frame in each data block, and form a block two-dimensional logarithmic amplitude spectrum matrix.

[0042] For example, the signal sampling rate is set to , each data block size is , the number of sampling points per frame is ,and ,in, Indicates the number of sampling points for FFT calculation. According to the above parameters, we can get:

[0043] Spectral resolution : ;

[0044] Number of frames per data block : ;in, Indicates taking an integer;

[0045] Perform FFT transformation and calculate the logarithmic amplitude spectrum of each frame in each data block to form a block two-dimensional logarithmic amplitude spectrum matrix: .in, Represents the logarithmic amplitude spectrum of the jth frame on the i-th spectral line.

[0046] Step 200, searching for pulses on each spectrum line in a block two-dimensional logarithmic amplitude spectrum matrix to form an original pulse set.

[0047] The step 200 specifically includes the following steps:

[0048] Step 201, calculate the frequency and background noise of each spectrum line. The specific calculation formula is as follows:

[0049] The frequency corresponding to the i-th spectral line for: ;

[0050] The noise floor of the i-th spectral line for: ;in, Represents a function for finding the average amplitude of all frames of the root spectrum line.

[0051] Step 202 : searching and recording pulses detected on all spectral lines according to the background noise of each spectral line and the preset minimum signal-to-noise ratio and minimum pulse width, to form an original pulse set.

[0052] Specifically, the jth pulse on the i-th spectral line It is expressed as:

[0053] ;in, represents the minimum signal-to-noise ratio, Indicates the minimum pulse width, They represent the starting frame number and ending frame number of the j-th pulse respectively.

[0054] The signal-to-noise ratio of the jth pulse on the i-th spectral line for: , thus obtaining the jth pulse representing the i-th spectral line The parameter groups are:

[0055] . Where q represents the spectral line number, Indicates pulse width.

[0056] Preferably, in this embodiment, the minimum pulse width can be set to 2, and the minimum signal-to-noise ratio can be set to 12. Any pulse should meet the requirements of being greater than the minimum signal-to-noise ratio and the minimum pulse width at the same time. Considering that the actual frequency hopping signal pulse width will not be less than 2 frames, this parameter setting is reasonable. In addition, the minimum pulse width is set to 2 because the superimposed noise may divide the signal pulse into multiple narrow pulse signals, and these narrow pulses can still be picked up at this time. It should be noted that the above setting is only a preferred setting and does not limit the minimum pulse width. In actual use, a suitable minimum pulse width can be set according to the characteristics of the detected signal.

[0057] The spectral line noise floor used in this embodiment is calculated using the above-mentioned calculation formula and is determined by the frame amplitude of each spectral line itself, that is, the noise floor size on each spectral line can be different, and the pulse level detected thereon changes accordingly with the noise floor of the corresponding spectral line, thereby avoiding the problem of ambiguity between signal pulses and noise floor levels on certain spectral lines caused by a single noise floor level, and the noise on other spectral lines will not affect the pulse detection on the current spectral line, thereby improving the detection accuracy.

[0058] The detection method proposed in this embodiment does not make any a priori assumptions about the intensity and shape of the noise signal, but calculates the background noise based on each spectral line, which greatly adapts to and follows the changes in noise, while avoiding noise interference on other spectral lines, thereby making this method more versatile and highly adaptable.

[0059] Step 300: merge adjacent pulses on the same spectral line in the original pulse set that meet the time continuity requirement, calculate and update the pulse parameter group, form an updated pulse set and construct its pulse width histogram curve.

[0060] The step 300 specifically includes the following steps:

[0061] Step 301, traverse all spectral lines, merge the pulses on the same spectral line whose adjacent pulse distance is less than or equal to the minimum distance into one pulse, and calculate and update the pulse parameter group.

[0062] The jth pulse on the i-th spectral line and the (j+1)th pulse The merging rules are:

[0063] if , then merge them into a new pulse ;in, The fifth parameter representing the (j+1)th pulse, i.e., the starting frame number; The sixth parameter representing the jth pulse, i.e., the end frame number; Indicates the minimum distance between adjacent pulses, preferably 5.

[0064] New Pulse The parameters are:

[0065] , indicating that the first and second parameters of the new pulse are the same as the corresponding parameters of the jth pulse;

[0066] , indicating that the third and fourth parameters of the new pulse are equal to the mean of the corresponding parameters of the two original adjacent pulses;

[0067] , indicating that the fifth parameter of the new pulse is the same as the corresponding parameter of the jth pulse;

[0068] , indicating that the sixth parameter of the new pulse is the same as the corresponding parameter of the (j+1)th pulse;

[0069] .

[0070] Considering that noise interference may split some signal pulses into multiple small pulses, this embodiment combines these pulses according to the temporal connection relationship of adjacent pulses on the same spectrum line to reduce the influence of noise and restore the original temporal characteristics of the pulses.

[0071] Step 302: Count the pulse width distribution histogram of each pulse in the combined pulse set to generate a pulse width histogram curve.

[0072] For example, the pulse parameter set after merging according to the above rules is expressed as:

[0073] ,in, represents the jth parameter value of the ith pulse.

[0074] Then the updated pulse set is , that is, it is composed of N pulses after merging, and the pulse width distribution histogram of these N pulses is counted to generate a pulse width histogram curve .

[0075] It should be noted that the pulse width statistical range should be appropriately expanded to both sides according to the number of signal pulse frames of the minimum and maximum frequency hopping rates to be detected.

[0076] Step 400, searching for all local peak points on the pulse width histogram curve, and recording the positions and values ​​of all peak points exceeding the threshold.

[0077] Assume that the pulse width statistical range is , then the i-th peak point of the histogram curve should satisfy the following formula:

[0078] ; Wherein, the pulse width is measured in frames as the minimum unit, w represents the pulse width of the ith peak point, and represents the histogram value of the corresponding point. It should be noted that the threshold in the above formula is set to 1 / 10 of the total number of pulses N, which is only an exemplary description and does not limit the threshold. In other optional implementations, the threshold can be determined according to the number of frequency hopping points.

[0079] Step 500 , based on the recorded parameters of each peak point, all pulses meeting the pulse width requirement are screened out from the updated pulse set to form a pulse subset corresponding to each peak point.

[0080] For example, the i-th peak point The pulse width search range is ; then from the pulse set The pulse subset that meets the pulse width range of the i-th peak point is selected and recorded as , indicating that A pulse composition.

[0081] Since the pulse width of any frequency hopping signal is not a single value but varies within a certain range, in order to adapt to such changes, this embodiment searches within a certain pulse width range.

[0082] In the case of multiple peak points, the sum of the decomposed peak point pulse subsets may be greater than or equal to the total pulse number N. In particular, for peak points that are close to each other on the histogram curve, their pulse width coverage ranges may partially overlap.

[0083] Step 600, sort all pulses in each pulse subset according to the starting time from small to large, select the pulse with the strongest signal-to-noise ratio from the pulses with the same starting time as the representative pulse at this time point, and all representative pulses constitute the first updated pulse subset.

[0084] The process of forming each first update pulse subset in step 600 specifically includes the following steps:

[0085] Step 601, sort the pulses in the pulse subset from small to large according to the value of the starting frame number, which can be expressed as:

[0086] , Indicates that the pulse subset The pulses in are sorted from small to large according to the value of their fifth parameter (i.e., the starting frame number); Indicates the arrangement of the fifth parameter value from small to large. express The elements of Position in the sequence.

[0087] Step 602: group the sorted pulses with the same values ​​into a group, select the pulse with the largest signal-to-noise ratio as the representative pulse of this group, and all the representative pulses constitute the first updated pulse subset after screening. ,in, .

[0088] For a frequency hopping signal of a certain specific rate, at each specific moment, at most one frequency hopping signal starting point is allowed to appear, and the starting points of frequency hopping signals of different rates are not mutually exclusive and can be the same.

[0089] Step 700, sort all pulses in each first update pulse subset according to the end time from small to large, select the pulse with the strongest signal-to-noise ratio from the pulses with the same end time as the representative pulse at this time point, and all representative pulses constitute the second update pulse subset.

[0090] The process of forming each second update pulse subset in step 700 specifically includes the following steps:

[0091] Step 701, sort all pulses in the first update pulse subset according to the value of the end frame number from small to large, which can be expressed as:

[0092] , Indicates that the first update pulse subset The pulses in are sorted from small to large according to the value of their sixth parameter (i.e., the end frame number); Indicates the arrangement of the sixth parameter value from small to large. express The elements of Position in the sequence.

[0093] Step 702: group the sorted pulses with the same values ​​into a group, select the pulse with the largest signal-to-noise ratio as the representative pulse of this group, and all the representative pulses constitute the second updated pulse subset after screening. ,in, .

[0094] Step 800: Select all pulses in each second update pulse subset according to the time succession relationship to generate a third update pulse subset, and determine whether the set is a frequency hopping signal according to the parameter value of the third update pulse subset.

[0095] The step 800 of generating the third update pulse subset and determining whether the set is a frequency hopping signal according to the parameter value of the third update pulse subset specifically includes the following steps:

[0096] Step 801, define and initialize the pulse distance two-dimensional matrix

[0097] .

[0098] Step 802, according to the order of each pulse in the second updated pulse subset, the distance difference between the current pulse and all subsequent pulses is calculated in sequence, and the calculation formula is:

[0099] ;

[0100] Step 803, searching and determining a pulse that is in a time-continuous relationship with the current pulse, the searching method includes:

[0101] First, sort all the distance differences from the current pulse from small to large:

[0102] ;in, Indicates the arrangement of element values ​​from small to large. express The position of each element of in the second update pulse subset;

[0103] Then, select all elements whose values ​​are less than or equal to the maximum difference distance from the sort, and the total number of elements is recorded as E. There are three cases at this time:

[0104] E=0, in this case, keep the current pulse and change the pulse number to , indicating that there is no pulse in the subsequent pulses that is temporally continuous with the current pulse j;

[0105] E=1, in this case, keep the current pulse and change the pulse number to , Corresponding sequence The position number of the pulse with the smallest value in the , that is, the pulse number that is time-continuous with the current pulse j is k, ;

[0106] E>1, in this case, the current pulse is retained, and a pulse with the largest signal-to-noise ratio is selected from the E pulses as the pulse that is temporally continuous with the current pulse, and the pulse number is changed to k.

[0107] Step 804, return to step 803, continue searching to determine the pulse that has a time-continuous relationship with the new pulse, until the search of all pulses in the second updated pulse subset is completed, and a third updated pulse subset is generated. ,in, .

[0108] It should be noted that step 804 can determine whether to end the loop by judging the value of the pulse number k. , then the pulse corresponding to the pulse number k is taken as the current pulse (i.e., the value j=k) to continue the next search to determine the pulse that has a time-continuous relationship with the current pulse, and so on to form the third updated pulse subset by screening pulses according to the time-continuous relationship.

[0109] In this embodiment, the unit of the maximum distance between temporally adjacent pulses is a frame. Two signal pulses greater than this value can be regarded as discontinuous in time. The reasons for this phenomenon include: (1) one or more frequency hopping point signals are completely or partially lost; (2) the frequency hopping signal is originally transmitted intermittently, that is, the existence of a distance greater than the maximum distance is a characteristic of the signal itself, not a problem of signal detection.

[0110] The maximum distance needs to be determined by considering the characteristics of the frequency hopping signal to be detected. Generally, the duty cycle of the frequency hopping signal is between 50% and 100%. In extreme cases, each frequency hopping signal point has a signal for only 1 / 2 of the time period, which is 5ms for 100 hops per second. For such a signal, the maximum distance needs to be set to at least the number of frames corresponding to more than 5ms as the maximum distance parameter between adjacent pulses.

[0111] Step 805: extract parameters from each third update pulse subset, and determine whether the third update pulse subset is a frequency hopping signal according to the parameter values. Specifically, this embodiment uses the four parameters of the frequency hopping point signal-to-noise ratio, the ratio of the points with the largest signal-to-noise ratio, the maximum distance between adjacent pulses, and the number of the points with the largest distance to determine whether each third update pulse subset is a frequency hopping signal.

[0112] The step 805 specifically includes:

[0113] Calculate the i-th third update pulse subset The ratio of the number of pulse points whose signal-to-noise ratio is greater than the signal-to-noise ratio of the frequency hopping point to the total number of pulse points is recorded as ;

[0114] Count the third update pulse subset of the i-th The number of pulse points whose distance between adjacent pulse points is greater than the maximum distance between adjacent pulses is recorded as ;

[0115] if Greater than or equal to the ratio of large signal-to-noise ratio points and If the number of points is less than or equal to the maximum distance, the third update pulse subset of i is determined. It is a frequency hopping signal, otherwise it is not a frequency hopping signal.

[0116] Since a minimum signal-to-noise ratio parameter (i.e. ), this parameter is set relatively low, considering the complexity of the electromagnetic environment and the role of interference noise, and the detection signal entrance needs to be opened larger. If it is set too high here, the frequency hopping signal points that are interfered with in some local time periods or frequency bands will be excluded, and all subsequent detection steps cannot make up for this loss. After filtering in the above-mentioned multiple steps, the third updated pulse subset is generally a mixture of frequency hopping signals and non-frequency hopping signals. Therefore, it is necessary to determine whether it is a frequency hopping signal point set. At this time, the algorithm can require the frequency hopping signal point to have a slightly higher signal-to-noise ratio, and the number of high signal-to-noise ratio points to account for a certain proportion, that is, the signal-to-noise ratio of the frequency hopping point and the ratio of the large signal-to-noise ratio point. Of course, the setting of the ratio of large signal-to-noise ratio points also includes allowing the signal-to-noise ratio of some frequency hopping signal points to be appropriately lower, and includes accepting some isolated non-frequency hopping signal pulses with time-frequency characteristics similar to the frequency hopping signal points to enter the pulse set, but it is necessary to limit the proportion of such signal points in the total number of pulse points.

[0117] Generally, the time of each frequency hopping point of the frequency hopping signal is continuous. Therefore, the two parameters of the maximum distance between adjacent pulses and the maximum distance point number are set in this embodiment to take into account that the detection algorithm may miss some frequency hopping signal points, so that the detected frequency hopping signal point set has multiple time breakpoints, and also includes the phenomenon that the frequency hopping signal itself is allowed to have some time discontinuities. Once such a situation occurs, it can still be determined to be a frequency hopping signal and a frequency hopping signal point set is given.

[0118] Furthermore, the detection method proposed in this embodiment also includes:

[0119] Step 900, calculate and output relevant parameters of the frequency hopping signal.

[0120] The step 900 specifically includes:

[0121] Step 901, calculate the average signal strength of the frequency hopping point set (that is, the set determined as the frequency hopping signal), and the calculation formula is: , Indicates calculating the average value of the third parameter (i.e. pulse signal-to-noise ratio) of all pulses in the frequency hopping point set as the average signal strength of the frequency hopping signal .

[0122] Step 902, obtain the frequency set of the frequency hopping signal of the frequency hopping point set, the specific method is: according to the second parameter (i.e., frequency) of all pulses in the frequency hopping point set, sort them from small to large, and the frequency sets with different values ​​constitute the frequency set of this frequency hopping point set, and record this frequency set as .

[0123] Step 903, obtaining the frequency hopping rate and the frequency hopping signal duty cycle parameters. The specific method includes: calculating the average duration of all pulses in the frequency hopping point set, and the calculation formula is: , Indicates calculating the average value of the 7th parameter of all pulses in the frequency hopping point set as the average duration ; Calculate the start time difference of adjacent pulses in the frequency hopping point set, count the distribution of these differences, and set the start time difference variable to , the time difference distribution variable is , then: ,variable About Histogram curve; Search and determine the maximum value position point in the time difference distribution, and then select the second maximum value position point from the adjacent left and right positions. The maximum value and position point are recorded as (a1, a2), and the second maximum value and position point are recorded as (b1, b2), then:

[0124] The optimal distance parameter of the i-th frequency hopping point set:

[0125] ;

[0126] The frequency hopping rate of the i-th frequency hopping point set: ,in, Indicates taking an integer;

[0127] The duty cycle of the frequency hopping signal of the i-th frequency hopping point set: .

[0128] At this point, the four parameter sets of the frequency hopping point set are obtained as follows: , respectively represent the average signal strength of the frequency hopping signal, the frequency set of the frequency hopping signal, the frequency hopping rate and the duty cycle of the frequency hopping signal.

[0129] The detection method proposed in this embodiment can not only automatically and accurately search and determine whether there is a frequency hopping signal through the above steps, but also automatically provide a set of frequency hopping signal parameters related thereto once a frequency hopping signal of a certain rate is detected.

[0130] Based on the same technical concept as above, this embodiment also proposes a high-precision adaptive frequency hopping signal detection device, such as Figure 2 As shown, the detection device comprises:

[0131] The calculation unit divides the received I and Q data into blocks and calculates the logarithmic amplitude spectrum of each frame of each data block to form a block two-dimensional logarithmic amplitude spectrum matrix.

[0132] A first search unit searches for pulses on each spectrum line in a block two-dimensional logarithmic amplitude spectrum matrix to form an original pulse set.

[0133] A merging unit is used to merge adjacent pulses on the same spectral line in the original pulse set that meet the time continuity requirement, calculate and update the pulse parameter group, form an updated pulse set and construct its pulse width histogram curve.

[0134] The second search unit searches for all local peak points on the pulse width histogram curve and records the positions and values ​​of all peak points exceeding a threshold.

[0135] The first screening unit selects all pulses meeting the pulse width requirement from the updated pulse set according to the peak point parameters to form a pulse subset corresponding to the peak point.

[0136] The second screening unit sorts the pulses in each pulse subset according to the starting time from small to large, selects the pulse with the strongest signal-to-noise ratio from the pulses with the same starting time as the representative pulse of this time point, and all the representative pulses constitute the first updated pulse subset.

[0137] The third screening unit sorts all the pulses in each first update pulse subset according to the end time from small to large, selects the pulse with the strongest signal-to-noise ratio from the pulses with the same end time as the representative pulse of this time point, and all the representative pulses constitute the second update pulse subset.

[0138] A fourth screening unit selects all pulses in each second update pulse subset according to a time succession relationship to generate a third update pulse subset.

[0139] and an identification unit, wherein the identification unit determines whether the corresponding set is a frequency hopping signal according to the parameter value of each third update pulse subset.

[0140] Furthermore, the detection system proposed in this embodiment also includes:

[0141] An output unit calculates and outputs relevant parameters of the frequency hopping signal.

[0142] It should be noted that the specific implementation process of each module unit of the system proposed in this embodiment is the same as the steps in the above method, and will not be repeated here.

[0143] Embodiment 2: This embodiment adopts the frequency hopping signal detection technology proposed in the above embodiment to detect single-network frequency hopping signals and multi-network frequency hopping signals, as follows:

[0144] (1) Single-network frequency hopping signal detection. The detection results are shown in Table 1 and Figure 3 shown.

[0145] Table 1 Partial detection results of single-network 200 hop / s signal

[0146]

[0147] Table 1 shows the frequency and location of some jump points, the duration, and the signal strength and noise level of the jump points. Figure 3 The detection results of all jump points in a certain period of time are given, where Figure 3 The time difference between adjacent jump points shown in Figure (b) can better demonstrate the detection performance. Figure 3 As can be seen from Figure (b), the time differences of three jump points are greater than the average value, indicating that there is a phenomenon of missing jump points between these three time points, resulting in inconsistent time differences between adjacent jump points. The reasons for the loss of jump points will not be analyzed here. Figure 3 The middle (c) figure shows the frequency of occurrence of each frequency in this time period.

[0148] (2) Detection of frequency hopping signals of multiple stations. This embodiment gives the detection results of frequency hopping signals of three stations in the same frequency band. Table 2 gives the detection results of signals of multiple stations with 10 hops / second, and Table 3 gives the detection results of signals of multiple stations with 50 hops / second. Figure 4 The test results of 100 hops / second in multiple networks are given.

[0149] Table 2 Partial detection results of multi-network 10 hop / second signals

[0150]

[0151] Table 3 Partial detection results of multi-network 50 hop / second signals

[0152]

[0153] Tables 2 and 3 both give the frequency and location of some jump points, the duration, and the signal strength and noise level of the jump points. Figure 4 The detection results of all jump points in a certain period of time are given, among which Figure 4 As can be seen from Figure (b), the time difference between two jump points is greater than the average, indicating that there is a phenomenon of missing jump points between these two time points. Figure 4 The middle (c) figure shows the frequency of occurrence of each frequency in this time period.

[0154] It can be seen from the actual measurement results of a large amount of air interface data that the frequency hopping signal detection technology proposed in this embodiment can detect frequency hopping signals of any frequency band and any rate, including multiple frequency hopping signals of different rates mixed together; it can accurately give the relevant parameters of the frequency hopping signal, including the signal strength of each hopping point, the frequency set of the frequency hopping signal, the frequency hopping rate, the duty cycle of the frequency hopping signal, the start and end time of each hopping point, the time connection relationship of each hopping point, etc. The accuracy of these parameters helps to improve the detection quality of frequency hopping signals in complex electromagnetic environments.

[0155] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0156] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0157] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0158] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0159] The specific implementation methods described above further illustrate the purpose, technical solutions and beneficial effects of the present application in detail. It should be understood that the above description is only the specific implementation method of the present application and is not intended to limit the scope of protection of the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application should be included in the scope of protection of the present application.

Claims

1. A high-precision adaptive frequency hopping signal detection method, characterized in that: The detection method comprises: Divide the received I and Q data into blocks, and calculate the logarithmic amplitude spectrum of each frame of each data block to form a block two-dimensional logarithmic amplitude spectrum matrix; Searching for pulses on each spectrum line in the block two-dimensional logarithmic amplitude spectrum matrix to form an original pulse set; Merging adjacent pulses on the same spectral line in the original pulse set that meet the time continuity requirement, calculating and updating the pulse parameter group, forming an updated pulse set and constructing its pulse width histogram curve; Searching for all local peak points on the pulse width histogram curve, and recording the positions and values ​​of all peak points exceeding a threshold; According to the recorded parameters of each peak point, all pulses meeting the pulse width requirements are screened out from the updated pulse set to form a pulse subset corresponding to each peak point; All pulses in each of the pulse subsets are sorted in ascending order according to the starting time, and the pulse with the strongest signal-to-noise ratio is selected from the pulses with the same starting time as the representative pulse at this time point, and all the representative pulses constitute a first updated pulse subset; Sort all the pulses in each of the first update pulse subsets in ascending order according to the end time, select the pulse with the strongest signal-to-noise ratio from the pulses with the same end time as the representative pulse at this time point, and all the representative pulses constitute the second update pulse subset; Selecting all pulses in each of the second update pulse subsets according to a time succession relationship to generate a third update pulse subset, and determining whether the set is a frequency hopping signal according to a parameter value of the third update pulse subset; The determining, according to the parameter value of the third update pulse subset, whether the set is a frequency hopping signal specifically includes: Calculating the ratio of the number of pulse points whose signal-to-noise ratio is greater than the signal-to-noise ratio of the frequency hopping point in the third updated pulse subset to the total number of pulse points; Counting the number of pulse points in the third updated pulse subset whose distance between adjacent pulse points is greater than the maximum distance between adjacent pulses; If the ratio of the number of pulse points with a signal-to-noise ratio greater than the signal-to-noise ratio of the frequency hopping point to the total number of pulse points is greater than or equal to the large signal-to-noise ratio point ratio and the number of pulse points with a distance between adjacent pulse points greater than the maximum distance between adjacent pulses is less than or equal to the number of maximum distance points, then it is determined that the third updated pulse subset is a frequency hopping signal, otherwise it is not a frequency hopping signal.

2. A high-precision adaptive frequency hopping signal detection method according to claim 1, characterized in that: The method of dividing the received I and Q data into blocks and calculating the logarithmic amplitude spectrum of each frame of each data block includes: According to the preset signal sampling rate, data block size, number of sampling points per frame and constraint conditions, the number of frames per data block is determined, thereby realizing data segmentation; At the same time, the spectrum resolution is determined according to the signal sampling rate and the number of FFT sampling points, the data block is transformed by FFT, and the logarithmic amplitude spectrum of each frame in each data block is calculated.

3. A high-precision adaptive frequency hopping signal detection method according to claim 1, characterized in that: The forming process of the original pulse set includes: Calculate the frequency and background noise of each spectrum line in the block two-dimensional logarithmic amplitude spectrum matrix; wherein the frequency of the spectrum line is calculated according to the spectrum resolution, and the background noise of the spectrum line is the average value of all frame amplitude spectra of the corresponding spectrum line; According to the background noise of each spectral line and the preset minimum signal-to-noise ratio and minimum pulse width, the pulses detected on all spectral lines are searched and recorded to form an original pulse set and determine a pulse parameter group characterizing the pulses; wherein the pulse parameter group includes seven parameters, namely: spectral line number, spectral line frequency, pulse signal-to-noise ratio, background noise of spectral line, start frame number, end frame number, and pulse width.

4. A high-precision adaptive frequency hopping signal detection method according to claim 3, characterized in that: The step of merging adjacent pulses on the same spectral line in the original pulse set that meet the time continuity requirement, calculating and updating the pulse parameter group, forming an updated pulse set and constructing its pulse width histogram curve specifically includes: Traverse all spectral lines in the original pulse set, merge the pulses whose adjacent pulse distances on the same spectral line are less than the minimum distance into one pulse, and calculate and update the pulse parameter group; wherein, the merging rule is: if the distance between the original pulse and its subsequent adjacent pulse is less than or equal to the minimum distance, merge the two pulses into one new pulse; the pulse parameter group updating rule of the new pulse is: the spectral line number and the spectral line frequency of the new pulse are respectively the same as the corresponding parameters of the original pulse, the pulse signal-to-noise ratio and the background noise of the spectral line of the new pulse are respectively equal to the mean of the corresponding parameters of the original pulse and its adjacent pulses, the starting frame number of the new pulse is the same as the corresponding parameter of the original pulse, and the ending frame number of the new pulse is the same as the corresponding parameter of the adjacent pulse; the pulse width of the new pulse is equal to the ending frame number of the new pulse minus the starting frame number of the new pulse plus 1; The pulse width distribution histogram of each pulse in the combined pulse set is statistically analyzed to generate a pulse width histogram curve.

5. The high-precision adaptive frequency hopping signal detection method according to claim 1, characterized in that: The forming process of the first update pulse subset includes: Sort all the pulses in the pulse subset in ascending order according to the values ​​of the starting frame numbers; The sorted pulses with exactly the same values ​​are grouped together, and the pulse with the largest signal-to-noise ratio is selected as the representative pulse of the group. All representative pulses constitute a first updated pulse subset.

6. A high-precision adaptive frequency hopping signal detection method according to claim 1, characterized in that: The forming process of the second update pulse subset includes: Sort all pulses in the first update pulse subset in ascending order according to the values ​​of the end frame numbers; The sorted pulses with exactly the same values ​​are grouped together, and the pulse with the largest signal-to-noise ratio is selected as the representative pulse of the group. All representative pulses constitute the second updated pulse subset.

7. A high-precision adaptive frequency hopping signal detection method according to claim 1, characterized in that: The generating of the third update pulse subset specifically includes: According to the order of each pulse in the second updated pulse subset, sequentially calculating the distance difference between the current pulse and all subsequent pulses; Searching to determine a pulse that is in a temporal continuity relationship with the current pulse, the searching method comprising: Sort all the calculated distance differences from small to large; Select all elements whose values ​​are less than or equal to the maximum difference distance from the sorting, and record the total number of elements; at this time, if the total number of elements is equal to 0, keep the current pulse and change the pulse number to the next pulse number; if the total number of elements is equal to 1, keep the current pulse and change the pulse number to the pulse number corresponding to the minimum value in the sorting; if the total number of elements is greater than 1, keep the current pulse, select the pulse with the largest signal-to-noise ratio from all elements as the pulse that is time-continuous with the current pulse, and change the pulse number to the pulse number with the largest signal-to-noise ratio; Determine the new current pulse according to the changed pulse number, return to the previous step to continue searching for and determining the pulse that is time-connected with the new current pulse, until the search for all pulses in the second update pulse subset is completed, and all the searched pulses constitute the third update pulse subset.

8. A high-precision adaptive frequency hopping signal detection method according to any one of claims 1 to 7, characterized in that: The detection method further comprises: Calculate and output the relevant parameters of the frequency hopping signal.

9. A high-precision adaptive frequency hopping signal detection method according to claim 8, characterized in that: The relevant parameter calculation process of the frequency hopping signal includes: Calculating an average signal strength of a set determined to be a frequency hopping signal, wherein the average signal strength is an average value of pulse signal-to-noise ratios of all pulses in the set; Obtain a frequency hopping signal frequency set, specifically sorting the frequencies of all pulses in the set from small to large, and frequency sets with different values ​​constitute the frequency hopping signal frequency set; Get the frequency hopping rate and duty cycle of the frequency hopping signal.

10. A high-precision adaptive frequency hopping signal detection method according to claim 9, characterized in that: The process of acquiring the frequency hopping rate and the duty cycle of the frequency hopping signal includes: Calculate the average duration of all pulses in the set, where the average duration is the average value of the pulse widths of all pulses in the set; Calculating the start time difference of adjacent pulses in the set, and obtaining a time difference distribution by statistics, wherein the start time difference is the difference of the pulse start frame numbers of adjacent pulses, and the time difference distribution is a histogram curve about the start time difference; Searching to determine the maximum value position point in the time difference distribution, then selecting the second maximum value position point from the left and right adjacent positions, and recording the maximum value and position point as well as the second maximum value and position point; According to the maximum value and position point and the second maximum value and position point, the optimal distance of the set is obtained, and the frequency hopping rate is calculated by combining the signal sampling rate and the number of sampling points per frame; The duty cycle of the frequency hopping signal is calculated according to the average duration and the optimal distance.

11. A high-precision adaptive frequency hopping signal detection device, characterized in that: The detection device comprises: A calculation unit, wherein the calculation unit divides the received I and Q data into blocks and calculates the logarithmic amplitude spectrum of each frame of each data block to form a block two-dimensional logarithmic amplitude spectrum matrix; A first search unit, wherein the first search unit searches for pulses on each spectrum line in the block two-dimensional logarithmic amplitude spectrum matrix to form an original pulse set; A merging unit, wherein the merging unit merges adjacent pulses on the same spectral line in the original pulse set that meet the time continuity requirement, calculates and updates the pulse parameter group, forms an updated pulse set and constructs a pulse width histogram curve thereof; A second search unit, the second search unit searches for all local peak points on the pulse width histogram curve, and records positions and values ​​of all peak points exceeding a threshold; A first screening unit, wherein the first screening unit screens out all pulses meeting the pulse width requirement from the updated pulse set according to the recorded parameters of each peak point, to form a pulse subset corresponding to each peak point; a second screening unit, wherein the second screening unit respectively sorts all the pulses in each of the pulse subsets according to the starting time from small to large, and selects the pulse with the strongest signal-to-noise ratio from the pulses with the same starting time as the representative pulse at this time point, and all the representative pulses constitute a first updated pulse subset; a third screening unit, wherein the third screening unit respectively sorts all the pulses in each of the first update pulse subsets according to the end time from small to large, and selects the pulse with the strongest signal-to-noise ratio from the pulses with the same end time as the representative pulse at this time point, and all the representative pulses constitute the second update pulse subset; a fourth screening unit, wherein the fourth screening unit selects all pulses in each of the second update pulse subsets according to a time succession relationship to generate a third update pulse subset, and, an identification unit, wherein the identification unit determines whether the corresponding set is a frequency hopping signal according to the parameter value of each of the third update pulse subsets; and determines whether the set is a frequency hopping signal according to the parameter value of the third update pulse subset, specifically including: Calculating the ratio of the number of pulse points whose signal-to-noise ratio is greater than the signal-to-noise ratio of the frequency hopping point in the third updated pulse subset to the total number of pulse points; Counting the number of pulse points in the third updated pulse subset whose distance between adjacent pulse points is greater than the maximum distance between adjacent pulses; If the ratio of the number of pulse points with a signal-to-noise ratio greater than the signal-to-noise ratio of the frequency hopping point to the total number of pulse points is greater than or equal to the large signal-to-noise ratio point ratio and the number of pulse points with a distance between adjacent pulse points greater than the maximum distance between adjacent pulses is less than or equal to the number of maximum distance points, then it is determined that the third updated pulse subset is a frequency hopping signal, otherwise it is not a frequency hopping signal.

12. A high-precision adaptive frequency hopping signal detection device according to claim 11, characterized in that: The detection device also includes: An output unit calculates and outputs relevant parameters of the frequency hopping signal.

13. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 10 are implemented.

Images