A single interference identification method based on decision tree

Abstract

The application discloses a single interference identification method based on a decision tree, and comprises the following steps: determining a bandwidth feature and a time width feature if the energy of a radar signal is greater than or equal to a first preset threshold; determining first interference if the bandwidth feature is greater than or equal to a second preset threshold and the time width feature is less than a third preset threshold; determining second interference if the bandwidth feature is greater than or equal to the second preset threshold, the time width feature is greater than or equal to the third preset threshold, and the bandwidth feature is less than a fourth preset threshold; determining third interference, fourth interference or fifth interference according to at least part of data in the radar signal and a preset time window parameter if the bandwidth feature is greater than or equal to the second preset threshold, the time width feature is greater than or equal to the third preset threshold, and the bandwidth feature is greater than or equal to the fourth preset threshold; and determining sixth interference, seventh interference, eighth interference or ninth interference according to at least part of data in the radar signal, the time width feature and the bandwidth feature if the bandwidth feature is less than the second preset threshold.

Description

Technical Field

[0001] This invention belongs to the field of radar signal processing technology, specifically relating to a single interference identification method based on decision trees. Background Technology

[0002] In an increasingly complex electromagnetic environment, the battle between electronic jamming and anti-jamming is intensifying, its importance self-evident. Radar, as a primary device and carrier of modern electronic warfare, makes research into jamming and anti-jamming of radar signals particularly crucial. In actual anti-jamming operations, both sides first need to obtain the type of jamming the other is employing in order to take targeted anti-jamming measures. Therefore, the ability to utilize radar echo signals to identify the specific types of jamming they contain is a vital prerequisite for effective anti-jamming.

[0003] Most existing radar signal interference identification methods rely on machine learning or deep learning models for classification and identification. The main problem with these methods is the excessive computational cost, making real-time interference identification impossible, which is obviously extremely disadvantageous for radar. Furthermore, some interference identification methods have limited identification types or require specific conditions for identification, making them ineffective in real-world environments. In other words, existing interference identification methods suffer from insufficient category recognition, low accuracy, and poor real-time performance. Summary of the Invention

[0004] To address the aforementioned problems in related technologies, this invention provides a single interference identification method based on decision trees. The technical problem to be solved by this invention is achieved through the following technical solution:

[0005] This invention provides a single interference identification method based on decision trees, comprising:

[0006] Calculate the signal energy based on the received current radar echo signal;

[0007] When the signal energy is greater than or equal to a first preset threshold, it is determined that the current radar echo signal contains interference, and bandwidth characteristics and time width characteristics are determined based on the current radar echo signal.

[0008] When the bandwidth characteristic is greater than or equal to the second preset threshold and the time bandwidth characteristic is less than the third preset threshold, the interference is determined to be the first interference.

[0009] When the bandwidth characteristic is greater than or equal to the second preset threshold, the time width characteristic is greater than or equal to the third preset threshold, and the bandwidth characteristic is less than the fourth preset threshold, the interference is determined to be the second interference.

[0010] When the bandwidth feature is greater than or equal to the second preset threshold, the time width feature is greater than or equal to the third preset threshold, and the bandwidth feature is greater than or equal to the fourth preset threshold, the interference is determined to be the third interference, the fourth interference, or the fifth interference based at least on some data from the current radar echo signal, the preset time window parameter, and the fifth preset threshold.

[0011] When the bandwidth characteristic is less than the second preset threshold, the interference is determined to be the sixth interference, the seventh interference, the eighth interference, or the ninth interference based at least on some data from the current radar echo signal, the time width characteristic, the bandwidth characteristic, the preset noise, the preset sampling window parameters, and the sixth preset threshold.

[0012] In some embodiments, determining the bandwidth characteristics and time width characteristics based on the current radar echo signal includes:

[0013] The bandwidth of the signal is calculated based on the current radar echo signal to obtain the bandwidth characteristics;

[0014] The time-width feature is obtained by determining the reciprocal of the bandwidth feature.

[0015] In some embodiments, the fifth preset threshold includes: a first sub-threshold and a second sub-threshold; the preset time window parameter includes: a preset number of time windows; determining the interference as a third, fourth, or fifth interference based at least some data from the current radar echo signal, the preset time window parameter, and the fifth preset threshold includes:

[0016] Determine the current signal mean based on the current radar echo signal;

[0017] The frequency domain range offset is determined based on the current radar echo signal and the current signal mean.

[0018] When the frequency domain offset is greater than or equal to the first sub-threshold, the interference is determined to be the third interference;

[0019] When the frequency domain offset is less than the first sub-threshold, the multi-time-window frequency domain offset is determined according to the preset number of time windows and the current radar echo signal.

[0020] Based on the relationship between the frequency domain skewness of the multi-time window and the second sub-threshold, the interference is determined to be either the fourth interference or the fifth interference.

[0021] In some embodiments, determining the current signal mean based on the current radar echo signal includes:

[0022] The current radar echo signal is digitally sampled to obtain a time-domain discrete signal;

[0023] The discrete-time signal is transformed to the frequency domain using the discrete Fourier transform to obtain the frequency domain signal;

[0024] The mean of the frequency domain signal is determined to obtain the mean of the current signal.

[0025] In some embodiments, determining the frequency domain range offset based on the current radar echo signal and the current signal mean includes:

[0026] Determine the current standard deviation based on the frequency domain signal and the mean of the current signal;

[0027] The frequency domain offset is determined based on the frequency domain signal, the current signal mean, and the current standard deviation.

[0028] In some embodiments, determining the multi-time-window frequency domain moment skewness based on the preset number of time windows and the current radar echo signal includes:

[0029] Using the preset number of time windows, a signal is selected from the frequency domain signal corresponding to the current radar echo signal to obtain a local signal;

[0030] Determine the mean of the local signal to obtain the current local mean;

[0031] The current local standard deviation is obtained based on the local signal and the current local mean.

[0032] The frequency domain moment skewness of the multi-time window is determined based on the local signal, the current local mean, and the current local standard deviation.

[0033] In some embodiments, the preset noise is preset time-domain noise; the sixth preset threshold includes: a third sub-threshold, a fourth sub-threshold, and a fifth sub-threshold; the preset sampling window parameters include: sampling window length and initial sampling position; determining the interference as a sixth, seventh, eighth, or ninth interference based at least some data from the current radar echo signal, the time-width characteristic, the bandwidth characteristic, the preset noise, the preset sampling window parameters, and the sixth preset threshold includes:

[0034] Based on the current radar echo signal and the time width characteristics, determine the time width interval signal;

[0035] The time-domain continuity coefficient is determined based on the time-width interval signal, the preset time-domain noise, and the indicator function.

[0036] When the time-domain continuity coefficient is less than the third sub-threshold, the interference is determined to be the sixth interference or the seventh interference based on the relationship between the bandwidth feature and the fourth sub-threshold.

[0037] When the time-domain continuity coefficient is greater than or equal to the third sub-threshold, the signal is sampled from the time-width interval signal according to the sampling window length and the initial sampling position;

[0038] The time-domain characteristics are determined based on the sampling window length, the sampled signal, and the peak value of the discrete-time signal.

[0039] Based on the relationship between the time-domain features and the fifth sub-threshold, the interference is determined to be either the eighth interference or the ninth interference.

[0040] In some embodiments, determining the time-width interval signal based on the current radar echo signal and the time-width characteristics includes:

[0041] Based on the current radar echo signal, a time-domain discrete signal is obtained;

[0042] Based on the time-width characteristics, a time-width interval signal is determined from the time-domain discrete signal.

[0043] In some embodiments, determining the time-domain characteristics based on the sampling window length, the sampled signal, and the peak value of the discrete-time signal includes:

[0044] The mean value of the sampled signal is determined based on the sampling window length and the sampled signal.

[0045] The difference between the mean and the peak value of the discrete-time signal is used as the time-domain feature.

[0046] In some embodiments, the first interference is smart noise interference, the second interference is noise frequency modulation interference, the third interference is comb spectrum interference, the fourth interference is frequency sweep interference, the fifth interference is broadband suppression interference, the sixth interference is full pulse forwarding interference, the seventh interference is partial pulse dense forwarding interference, the eighth interference is full pulse dense forwarding interference, and the ninth interference is intermittent sampling forwarding interference.

[0047] The present invention has the following beneficial technical effects:

[0048] The interference identification method provided by this invention only requires simple data calculation and numerical comparison to determine a variety of different interference types without involving a large number of complex calculations. At the same time, it can improve the accuracy, real-time performance and reliability of identification. Therefore, it can not only provide timely and highly reliable identification of various types of interference, but also increase the range of radar interference identification.

[0049] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0050] Figure 1 A flowchart of a single interference identification method based on decision tree provided in an embodiment of the present invention;

[0051] Figure 2 A flowchart illustrating an exemplary single interference identification method based on a decision tree, provided in an embodiment of the present invention;

[0052] Figure 3 A time-domain schematic diagram illustrating nine exemplary single interference types provided for embodiments of the present invention;

[0053] Figure 4 A schematic diagram of the spectrum of nine exemplary single interference types provided for embodiments of the present invention;

[0054] Figure 5 A schematic diagram illustrating the calculation results of whether or not a radar echo signal contains interference, provided for an embodiment of the present invention;

[0055] Figure 6 A schematic diagram illustrating the calculation results of the bandwidth characteristics of radar echo signals containing nine different types of interference, provided as an embodiment of the present invention.

[0056] Figure 7 A schematic diagram illustrating the calculation results of the time-domain continuity coefficient of radar echo signals containing interference 1 to interference 4, provided as an embodiment of the present invention;

[0057] Figure 8 A schematic diagram illustrating the calculation results of the time-domain characteristics of radar echo signals containing interference 2 to interference 3, provided as an embodiment of the present invention;

[0058] Figure 9 A schematic diagram illustrating the calculation results of the time-width characteristics of radar echo signals containing interference 5 to interference 9, provided as an embodiment of the present invention;

[0059] Figure 10 A schematic diagram illustrating the calculation results of the frequency domain moment skewness of radar echo signals containing interference 7 to interference 9, provided as an embodiment of the present invention;

[0060] Figure 11 This is an exemplary schematic diagram illustrating the calculation results of the multi-time window frequency domain moment skewness of radar echo signals containing interference 7 to interference 8, provided as an embodiment of the present invention. Detailed Implementation

[0061] The present invention will be further described in detail below with reference to specific embodiments, but the implementation of the present invention is not limited thereto.

[0062] In the description of this invention, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0063] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. In addition, those skilled in the art can combine and integrate the different embodiments or examples described in this specification.

[0064] Although the invention has been described herein in conjunction with various embodiments, those skilled in the art will understand and implement other variations of the disclosed embodiments by reviewing the accompanying drawings, disclosure, and appended claims in carrying out the claimed invention. In the claims, the word "comprising" does not exclude other components or steps, and "a" or "an" does not exclude a plurality. A single processor or other unit can implement several functions listed in the claims. While different dependent claims may recite certain measures, this does not mean that these measures cannot be combined to produce good results.

[0065] Figure 1 This is a flowchart of a single interference identification method based on decision trees provided in an embodiment of the present invention, as shown below. Figure 1 As shown, the method includes the following steps:

[0066] S101. Calculate the signal energy based on the received current radar echo signal.

[0067] Here, the current radar echo signal is the radar echo signal received at the current moment.

[0068] Here, let the current radar echo signal be S. r (t), by digitally sampling it, the resulting discrete sequence (time-domain discrete signal) is X, where X = (x1, x2, ..., x n Let n be the number of sampling points. The principle for calculating signal energy is as follows:

[0069]

[0070] S102. When the signal energy is greater than or equal to the first preset threshold, determine that the current radar echo signal contains interference, and determine the bandwidth characteristics and time width characteristics based on the current radar echo signal.

[0071] Here, if the signal energy is less than or equal to the first preset threshold, it is determined that there is no interference and the identification ends; otherwise, it is determined that there is interference.

[0072] Here, the first preset threshold can be set according to actual needs.

[0073] In some embodiments, the bandwidth of the current radar echo signal can be calculated based on the current radar echo signal to obtain the bandwidth feature; and the reciprocal of the bandwidth feature can be used as the time width feature.

[0074] Here, we can consider the time-domain discrete signal X = (x1, x2, ..., x...). n Performing a Discrete Fourier Transform on the signal yields the frequency domain signal F = (f1, f2, ..., f...). m ), where m is the length of the discrete Fourier transform; then, the bandwidth of the frequency domain signal F is calculated to obtain the bandwidth characteristics.

[0075] S103. When the bandwidth characteristic is greater than or equal to the second preset threshold and the time bandwidth characteristic is less than the third preset threshold, the interference is determined to be the first interference.

[0076] In this embodiment of the invention, the interference types that can be determined include: first interference, second interference, third interference, fourth interference, fifth interference, sixth interference, seventh interference, eighth interference, and ninth interference.

[0077] In some embodiments, the first interference is smart noise interference (ISRJ noise modulation), the second interference is noise frequency modulation interference, the third interference is comb spectrum interference, the fourth interference is frequency sweep interference, the fifth interference is broadband suppression interference, the sixth interference is full pulse forwarding interference, the seventh interference is partial pulse dense forwarding interference, the eighth interference is full pulse dense forwarding interference, and the ninth interference is intermittent sampling forwarding interference.

[0078] Here, both the second and third preset thresholds can be set according to actual needs.

[0079] S104. When the bandwidth characteristic is greater than or equal to the second preset threshold, the time-width characteristic is greater than or equal to the third preset threshold, and the bandwidth characteristic is less than the fourth preset threshold, the interference is determined to be the second interference.

[0080] Here, the fourth preset threshold can be set according to actual needs.

[0081] S105. When the bandwidth characteristic is greater than or equal to the second preset threshold, the time width characteristic is greater than or equal to the third preset threshold, and the bandwidth characteristic is greater than or equal to the fourth preset threshold, the interference is determined to be the third interference, the fourth interference, or the fifth interference based at least on some data from the current radar echo signal, the preset time window parameters, and the fifth preset threshold.

[0082] In some embodiments, the fifth preset threshold includes: a first sub-threshold and a second sub-threshold; the preset time window parameter includes: a preset number of time windows.

[0083] Here, the preset number of time windows can be 3 to 5, which can be set according to actual needs. The first sub-threshold and the second sub-threshold can also be set according to actual needs.

[0084] In some embodiments, the above-mentioned S105 can be implemented by S1051 to S1055:

[0085] S1051. Determine the current signal average value based on the current radar echo signal.

[0086] Here, the current radar echo signal can be digitally sampled to obtain a discrete-time signal; the discrete-time signal can be transformed to the frequency domain using a discrete Fourier transform to obtain a frequency-domain signal; the mean of the frequency-domain signal can be determined to obtain the mean of the current signal. For example, when the frequency-domain signal is F = (f1, f2, ..., f... m When calculating f1, f2, ..., f, calculate... m The mean of the signal is obtained by taking the mean of the current signal.

[0087] S1052. Determine the frequency domain range offset based on the current radar echo signal and the current signal mean.

[0088] Here, the current standard deviation can be determined based on the frequency domain signal and the current signal mean; the frequency domain offset can be determined based on the frequency domain signal, the current signal mean, and the current standard deviation.

[0089] For example, the frequency domain offset can be calculated using formula (2):

[0090]

[0091] Where, x j Let f(j) be the j-th discrete signal value of the frequency domain signal, where j is an integer greater than 0 (for example, when the frequency domain signal is F = (f1, f2, ..., fj)). m-1 ,f m When x j f1, f2, ..., f m-1 or f m ), μ is the current signal mean, σ is the current standard deviation, and E[.] is the mean function.

[0092] S1053. When the frequency domain offset is greater than or equal to the first sub-threshold, the interference is determined to be the third interference.

[0093] S1054. When the frequency domain offset is less than the first sub-threshold, determine the multi-time-window frequency domain offset based on the preset number of time windows and the current radar echo signal.

[0094] Here, a preset number of time windows can be used to select a signal from the frequency domain signal F obtained from the current radar echo signal to obtain a local signal; the mean of the local signal is determined to obtain the current local mean; the current local standard deviation is obtained based on the local signal and the current local mean; and the frequency domain moment skewness of the multi-time window is determined based on the local signal, the current local mean, and the current local standard deviation.

[0095] For example, formula (3) can be used to calculate the multi-time window frequency domain offset:

[0096]

[0097] Among them, y j For the j-th discrete signal value in the local signal (e.g., when the local signal is F1 = (f1, f2, f3, f4), y j (where f1, f2, f3 or f4), μ1 is the current local mean, and σ1 is the current local standard deviation.

[0098] S1055. Based on the relationship between the frequency domain moment skewness of the multi-time window and the second sub-threshold, the interference is determined to be either the fourth or fifth interference.

[0099] Here, when the skewness of the multi-time window frequency domain moment is greater than or equal to the second sub-threshold, it is determined to be frequency sweep interference, while when the skewness of the multi-time window frequency domain moment is less than the second sub-threshold, it is determined to be comb spectrum interference.

[0100] S106. When the bandwidth characteristic is less than the second preset threshold, the interference is determined to be the sixth interference, the seventh interference, the eighth interference, or the ninth interference based at least on some data from the current radar echo signal, time width characteristic, bandwidth characteristic, preset noise, preset sampling window parameters, and the sixth preset threshold.

[0101] Here, the preset noise can be preset time-domain noise. The preset sampling window parameters can include: sampling window length and initial sampling position.

[0102] Here, the sixth preset threshold includes: the third sub-threshold, the fourth sub-threshold, and the fifth sub-threshold; and the third sub-threshold, the fourth sub-threshold, and the fifth sub-threshold can all be set according to actual needs.

[0103] In some embodiments, the above-mentioned S106 can be implemented by S1061 to S1066:

[0104] S1061. Determine the signal within the time width interval based on the current radar echo signal and time width characteristics.

[0105] Here, a discrete time-domain signal can be obtained based on the current radar echo signal. Based on the time-width characteristics, the time-width interval can be determined from the discrete time-domain signal, and the signal value within the time-width interval can be used as the time-width interval signal.

[0106] Here, the discrete-time signal corresponds to multiple time-domain points. The midpoint of these time-domain points can be taken as the midpoint of the time-width interval, and starting from the midpoint of the time-width interval, points are taken to the left and right respectively. t+1 consecutive time-domain points are obtained by taking t+1 consecutive time-domain points. The interval formed by these t+1 consecutive time-domain points is taken as the time-width interval, where t represents the time-width feature. The signal values ​​corresponding to these t+1 consecutive time-domain points constitute the time-width interval signal.

[0107] S1062. Determine the time-domain continuity coefficient based on the time-width interval signal, the preset time-domain noise, and the indicator function.

[0108] For example, the time-domain continuity coefficient can be calculated using formula (4):

[0109]

[0110] Where Ι(.) is the indicator function, N is the preset time-domain noise, T is the time-width interval, k is each time-domain point within the time-width interval, and x k Let be the signal value at the k-th time-domain point.

[0111] S1063. When the time domain continuity coefficient is less than the third sub-threshold, the interference is determined to be the sixth or seventh interference based on the relationship between the bandwidth characteristics and the fourth sub-threshold.

[0112] Here, when the time domain continuity coefficient is less than the third sub-threshold and the bandwidth feature is greater than or equal to the fourth sub-threshold, it is the seventh interference; when the time domain continuity coefficient is less than the third sub-threshold and the bandwidth feature is less than the fourth sub-threshold, it is the sixth interference.

[0113] S1064. When the time domain continuity coefficient is greater than or equal to the third sub-threshold, the signal is sampled from the time-width interval signal according to the sampling window length and the initial sampling position.

[0114] Here, the sampling window length can be determined specifically based on the sampling rate of the received signal; the initial sampling position can be any time point in the signal within the time-width interval.

[0115] S1065. Determine the time-domain characteristics based on the sampling window length, the sampled signal, and the peak value of the discrete-time signal.

[0116] Here, the mean of the sampled signal can be determined based on the sampling window length and the sampled signal; the difference between the mean and the peak value of the discrete-time signal is used as the time-domain feature.

[0117] For example, time-domain features can be calculated using formulas (5) and (6):

[0118]

[0119] N2 = max(X) - M (6);

[0120] Where A is the sampling window length, z is each time-domain point in the sampled signal, and x z Let X be the signal value at the z-th time-domain point, M be the mean of the sampled signal, and max(X) be the peak value of the discrete-time signal.

[0121] S1066. Based on the relationship between the temporal characteristics and the fifth sub-threshold, determine whether the interference is the eighth or ninth interference.

[0122] Here, when the time domain feature is greater than or equal to the fifth sub-threshold, it is the eighth interference, and when the time domain feature is less than the fifth sub-threshold, it is the ninth interference.

[0123] For example, Figure 2 A flowchart of the interference identification method provided by the present invention is shown below. Figure 2 As shown, for the current radar echo signal, when the calculated signal energy is less than the first preset threshold, it is determined that there is no interference and the identification ends. When the calculated signal energy is greater than or equal to the first preset threshold, the bandwidth characteristic and time width characteristic are calculated. When the bandwidth characteristic is greater than or equal to the second preset threshold and the time width characteristic is less than the third preset threshold, it is identified as interference 5. When the time width characteristic is greater than or equal to the third preset threshold and the bandwidth characteristic is less than the fourth preset threshold, it is identified as interference 6. When the bandwidth characteristic is greater than or equal to the fourth preset threshold, the frequency domain range skewness is calculated, and when the frequency domain range skewness is greater than or equal to the first sub-threshold, it is identified as interference 9. When the frequency domain range skewness is less than the first sub-threshold, the multi-time window frequency domain range skewness is calculated, and when the multi-time window frequency domain range skewness is greater than or equal to the second sub-threshold, it is identified as interference 8. When the multi-time window frequency domain range skewness is less than the second sub-threshold, it is identified as interference 7. When the bandwidth characteristic is less than the second preset threshold, the time-domain continuity coefficient is calculated. If the time-domain continuity coefficient is less than the third sub-threshold and the bandwidth characteristic is greater than or equal to the fourth sub-threshold, it is identified as interference 4. If the bandwidth characteristic is less than the fourth sub-threshold, it is identified as interference 1. When the time-domain continuity coefficient is greater than or equal to the third sub-threshold, the time-domain characteristic is calculated. If the time-domain characteristic is greater than or equal to the fifth sub-threshold, it is identified as interference 2. If the time-domain characteristic is less than the fifth sub-threshold, it is identified as interference 3. Figure 2 Interference 1 is full-pulse relay interference, interference 2 is full-pulse dense relay interference, interference 3 is ISRJ interference, interference 4 is partial-pulse dense relay interference, interference 5 is smart noise (ISRJ noise modulation) interference, interference 6 is noise frequency modulation interference, interference 7 is broadband suppression interference, interference 8 is frequency sweep interference, and interference 9 is comb spectrum interference.

[0124] The interference identification method provided by this invention only requires simple data calculations and numerical comparisons to determine various types of interference, without involving a large amount of complex calculations. It simultaneously improves the accuracy, real-time performance, and reliability of the identification, thus providing timely and highly reliable identification for multiple types of interference and expanding the range of radar interference identification. Furthermore, the interference identification method provided by this invention can identify composite interference and is suitable for the reliable identification of both suppression and deception interference.

[0125] The following is passed Figures 3 to 10 The effectiveness of the interference identification method provided by the present invention will be further explained.

[0126] Figure 3 and Figure 4 They are respectively Figure 2 Exemplary time-domain and frequency-domain plots of nine types of interference signals are provided. To evaluate the recognition accuracy of the interference recognition method of the present invention, 1000 samples were selected for both signals without interference and signals containing each type of interference, and the recognition accuracy in a statistical sense was calculated.

[0127] First, by utilizing the signal energy of radar echo signals, it is possible to accurately identify whether radar echo signals contain interference. The energy is calculated for radar echo signals containing the nine types of interference mentioned above and those without interference. A reasonable threshold is then selected, and the results are used for reference. Figure 5 It can be seen that the final statistical accuracy rate for identifying interference-free systems is 100%.

[0128] If interference is identified in the radar echo signal, the time-width characteristics are calculated for the radar echo signal containing the above nine types of interference. The results are referenced. Figure 6 From left to right, these are interferences 1 through 9. Figure 6 As can be seen, by reasonably selecting the threshold, interference 1 to interference 4 and interference 5 to interference 9, interference 1 and interference 4, and interference 6 and interference 7 to interference 9 can be effectively identified. Statistically, their identification accuracies are as follows: 99.8% for interference 1 to interference 4 and 100% for interference 5 to interference 9; 100% for interference 1 and interference 4; and 100% for interference 6 and interference 7 to interference 9.

[0129] After the above identification process, if the radar echo signal is determined to contain interference 1 to interference 4, then the time-domain continuity coefficients are calculated for the radar echo signals containing interference 1 to interference 4, and the results are referenced. Figure 7 It can be seen that selecting an appropriate threshold can effectively identify interference 1 and interference 4, as well as interference 2 and interference 3, and the recognition accuracy is 100% in a statistical sense.

[0130] If, based on the above identification process, it is determined that the radar signal contains interference 2 or interference 3, then the time-domain characteristics can be calculated, and the results can be referenced. Figure 8 It can be seen that selecting an appropriate threshold can effectively identify interference 2 or interference 3, and the statistical accuracy rates are 96.8% for interference 2 and 99.7% for interference 3.

[0131] The time-width characteristics of radar echo signals containing interference 5 to interference 9 were calculated, and the results were referenced. Figure 9 It can be seen that selecting an appropriate threshold can effectively identify interference 5 and interferences 6 to 9, and the recognition accuracy is 100% in a statistical sense.

[0132] Calculate the frequency domain moment skewness of the radar echo signals containing interference 7 to 9, and refer to the results. Figure 10 It can be seen that selecting an appropriate threshold can effectively identify interference 9 and interferences 7 to 8, and the statistical accuracy of identification is 100%.

[0133] After the above process, if interference 7 or interference 8 is identified in the radar echo signal, then the multi-time window frequency domain moment skewness is calculated. Figure 11 (Partial sampling frequency domain offset), results refer to Figure 11 It can be seen that selecting an appropriate threshold can effectively identify interference 7 and interference 8, and the statistical accuracy rates are 99% for interference 7 and 100% for interference 8.

[0134] The above description, in conjunction with specific preferred embodiments, provides a further detailed explanation of the present invention. It should not be construed that the specific implementation of the present invention is limited to these descriptions. For those skilled in the art, various simple deductions or substitutions can be made without departing from the concept of the present invention, and all such modifications and substitutions should be considered within the scope of protection of the present invention.

Claims

1. A single interference identification method based on decision trees, characterized in that, include: Calculate the signal energy based on the received current radar echo signal; When the signal energy is greater than or equal to a first preset threshold, it is determined that the current radar echo signal contains interference, and bandwidth characteristics and time width characteristics are determined based on the current radar echo signal. When the bandwidth characteristic is greater than or equal to the second preset threshold and the time bandwidth characteristic is less than the third preset threshold, the interference is determined to be the first interference. When the bandwidth characteristic is greater than or equal to the second preset threshold, the time width characteristic is greater than or equal to the third preset threshold, and the bandwidth characteristic is less than the fourth preset threshold, the interference is determined to be the second interference. When the bandwidth feature is greater than or equal to the second preset threshold, the time width feature is greater than or equal to the third preset threshold, and the bandwidth feature is greater than or equal to the fourth preset threshold, the interference is determined to be the third interference, the fourth interference, or the fifth interference based at least on some data from the current radar echo signal, the preset time window parameter, and the fifth preset threshold. The fifth preset threshold includes: a first sub-threshold and a second sub-threshold; the preset time window parameter includes: a preset number of time windows; When the bandwidth characteristic is less than the second preset threshold, the interference is determined to be a sixth, seventh, eighth, or ninth interference based at least on a portion of the data from the current radar echo signal, the time width characteristic, the bandwidth characteristic, the preset noise, the preset sampling window parameters, and the sixth preset threshold; the preset noise is a preset time domain noise; the sixth preset threshold includes a third sub-threshold, a fourth sub-threshold, and a fifth sub-threshold; the preset sampling window parameters include the sampling window length and the initial sampling position. The step of determining whether the interference is a third, fourth, or fifth type of interference based at least on a portion of the data from the current radar echo signal, preset time window parameters, and a fifth preset threshold includes: Determine the current signal mean based on the current radar echo signal; The frequency domain range offset is determined based on the current radar echo signal and the current signal mean. When the frequency domain offset is greater than or equal to the first sub-threshold, the interference is determined to be the third interference; When the frequency domain offset is less than the first sub-threshold, the multi-time-window frequency domain offset is determined according to the preset number of time windows and the current radar echo signal. Based on the relationship between the frequency domain skewness of the multi-time window and the second sub-threshold, the interference is determined to be either the fourth interference or the fifth interference; The step of determining the interference as a sixth, seventh, eighth, or ninth interference based at least on a portion of the data from the current radar echo signal, the time-width characteristic, the bandwidth characteristic, preset noise, preset sampling window parameters, and a sixth preset threshold includes: Based on the current radar echo signal and the time width characteristics, determine the time width interval signal; The time-domain continuity coefficient is determined based on the time-width interval signal, the preset time-domain noise, and the indicator function. When the time-domain continuity coefficient is less than the third sub-threshold, the interference is determined to be the sixth interference or the seventh interference based on the relationship between the bandwidth feature and the fourth sub-threshold. When the time-domain continuity coefficient is greater than or equal to the third sub-threshold, the signal is sampled from the time-width interval signal according to the sampling window length and the initial sampling position; The mean value of the sampled signal is determined based on the sampling window length and the sampled signal. The difference between the mean and the peak value of the discrete-time signal is used as a time-domain feature. Based on the relationship between the temporal features and the fifth sub-threshold, the interference is determined to be either the eighth interference or the ninth interference. Among them, the first interference is smart noise interference, the second interference is noise frequency modulation interference, the third interference is comb spectrum interference, the fourth interference is frequency sweep interference, the fifth interference is broadband suppression interference, the sixth interference is full pulse forwarding interference, the seventh interference is partial pulse dense forwarding interference, the eighth interference is full pulse dense forwarding interference, and the ninth interference is intermittent sampling forwarding interference.

2. The single interference identification method based on decision tree according to claim 1, characterized in that, The step of determining the bandwidth and time width characteristics based on the current radar echo signal includes: The bandwidth of the signal is calculated based on the current radar echo signal to obtain the bandwidth characteristics; The time-width feature is obtained by determining the reciprocal of the bandwidth feature.

3. The single interference identification method based on decision tree according to claim 1, characterized in that, Determining the current signal mean based on the current radar echo signal includes: The current radar echo signal is digitally sampled to obtain a time-domain discrete signal; The discrete-time signal is transformed to the frequency domain using the discrete Fourier transform to obtain the frequency domain signal; The mean of the frequency domain signal is determined to obtain the mean of the current signal.

4. The single interference identification method based on decision tree according to claim 3, characterized in that, The step of determining the frequency domain range offset based on the current radar echo signal and the current signal mean includes: Determine the current standard deviation based on the frequency domain signal and the mean of the current signal; The frequency domain offset is determined based on the frequency domain signal, the current signal mean, and the current standard deviation.

5. The single interference identification method based on decision tree according to claim 1, characterized in that, The step of determining the frequency domain moment skewness of multiple time windows based on the preset number of time windows and the current radar echo signal includes: Using the preset number of time windows, a signal is selected from the frequency domain signal corresponding to the current radar echo signal to obtain a local signal; Determine the mean of the local signal to obtain the current local mean; The current local standard deviation is obtained based on the local signal and the current local mean. The frequency domain moment skewness of the multi-time window is determined based on the local signal, the current local mean, and the current local standard deviation.

6. The single interference identification method based on decision tree according to claim 5, characterized in that, The step of determining the time-width interval signal based on the current radar echo signal and the time-width characteristics includes: Based on the current radar echo signal, a time-domain discrete signal is obtained; Based on the time-width characteristics, a time-width interval signal is determined from the time-domain discrete signal.

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