Radar radiation source parameter matching identification method based on expert rule

Abstract

The invention discloses a radar radiation source parameter matching identification method based on expert rules. The method comprises the following steps: S1, establishing a target identification library; s2, setting expert rules; s3, setting a matching rule; s4, acquiring to-be-identified data to form a target to-be-identified library; s5, feature parameter matching degree calculation; s6, calculating the signal pattern matching confidence coefficient; s7, repeating the step S5 and the step S6 until all the signal styles complete the calculation of the matching degree and the matching confidence; s8, sorting signal styles; and S9, outputting a matching result. According to the method, the advantages of electronic reconnaissance backbone'experts' can be played, recognition rules and strategies for key targets are combed, a target recognition method based on the expert rules is formed, recognition parameters are customized in a personalized mode, recognition elements are added, the recognition process is remodeled, the original non-0, namely 1 judgment standard is broken, the recognition matching probability is closer to the reality, and the recognition efficiency is improved. And the recognition efficiency is improved on the premise of improving the recognition accuracy.

Description

Technical Field

[0001] The present invention relates to the technical field of radar radiation source identification, in particular to a parameter matching identification method for radar radiation source based on expert rules. Background Art

[0002] Parameter matching algorithms are widely used in radar emitter model identification and play an important role. Conventional parameter matching algorithms often only perform matching calculations on a few important radar emitter characteristic parameters, such as carrier frequency type, repetition interval type, pulse width type, carrier frequency value, repetition interval value, and pulse width value. The matching results are often either 0 or 1, which greatly reduces the recognition accuracy of the matching algorithm.

[0003] Expert rules are a method for target recognition based on expert rules, synthesizing the years of electronic target recognition experience of domain experts and leveraging the expertise of key electronic reconnaissance personnel. This method leverages the expertise of key personnel in electronic reconnaissance to develop rules and strategies for identifying key targets. This method primarily draws on knowledge of radar signal design and radar attribute design, as well as the correlation between known radar signals and attributes. It also integrates accumulated knowledge and experience in identifying radar emitters to construct inference rules for radar signal recognition. Using computer software, it accurately and rapidly infers information such as radar structure, purpose, and model. The key is to rationally transform the domain experts' database of expertise and experience into a target recognition database. This database must be maintained throughout the expert system's operation to ensure the accuracy of the rules and facts contained in the knowledge base.

[0004] The content in the target recognition library is an objective description of specific facts in the field, including the feature types and feature parameters of different signal styles under different radar modes, as well as the weight of each feature value in the signal recognition and the matching tolerance of each numerical feature parameter. Summary of the Invention

[0005] The purpose of the present invention is to overcome the shortcomings of the existing matching algorithm in terms of low recognition efficiency. The experience of core electronic reconnaissance experts is formed into recognition rules, and these rules are integrated into the matching algorithm through computer technology to form a target recognition method based on expert rules. The recognition parameters are customized, the recognition elements are added, and the recognition process is reshaped. The recognition efficiency is improved while the recognition accuracy is improved. The specific technical solutions are as follows:

[0006] A radar emitter parameter matching and identification method based on expert rules, the method comprising the following steps:

[0007] S1. Establish target recognition library

[0008] Establish a target recognition library based on radar radiation source signal pattern data, and the target recognition library is used to record radar radiation source signal patterns;

[0009] S2. Setting Expert Rules

[0010] Setting expert rule parameters formed by expert experience into the target recognition library;

[0011] S3. Set matching rules

[0012] The matching rules include feature parameter type and feature parameter matching threshold;

[0013] S4. Obtain the data to be identified to form a target database to be identified

[0014] According to the characteristic parameter type matching principle set in step S3, the target to be identified library consisting of signal patterns that meet the matching principle is screened in the target identification library;

[0015] S5. Calculation of characteristic parameter matching degree

[0016] According to the tolerance of each characteristic parameter set in the target recognition library, the characteristic parameter of each signal pattern in the target to be recognized library is matched with the characteristic parameter of the signal to be recognized to obtain the matching degree of each characteristic parameter in the signal pattern;

[0017] S6. Signal pattern matching confidence calculation

[0018] Calculate the matching confidence between each signal pattern in the target to be identified library and the signal to be identified based on the recognition weights of each feature parameter set in the target identification library;

[0019] S7, repeating steps S5 and S6 until the calculation of matching degree and matching confidence is completed for all signal patterns;

[0020] S8. Signal style sorting

[0021] Record the matching confidence of each signal pattern in the target to-be-identified library with the signal pattern to be identified, and sort all signal patterns from high to low according to the signal pattern matching confidence;

[0022] S9. Matching result output

[0023] According to the matching threshold set in the matching principle in S3, the signal pattern results that meet the matching threshold requirements are output.

[0024] Each signal pattern of the radar radiation source signal pattern in step S1 includes:

[0025] Carrier type, carrier value, carrier weight, carrier tolerance;

[0026] Repeat interval type, repeat interval value, repeat interval weight, repeat interval tolerance;

[0027] Pulse width type, pulse width value, pulse width weight, pulse width tolerance;

[0028] Sweep type, sweep value, sweep weight, and sweep tolerance;

[0029] PRI reference value, PRI reference weight, PRI reference tolerance

[0030] Modulation type, modulation type weight;

[0031] Pulse group conversion time weight, pulse group conversion time tolerance;

[0032] Duty cycle value, duty cycle weight, duty cycle tolerance;

[0033] Intra-pulse modulation type weight;

[0034] Modulation bandwidth tolerance;

[0035] Symbol width value, symbol width weight, symbol width tolerance;

[0036] Identify the threshold.

[0037] The expert rules described in step S2 are specific to different radar emitter signals. The weight values of the characteristic parameters are not fixed. The weights and tolerances of the characteristic parameters of each signal pattern of each radar can be set independently. The expert rules are reflected in the characteristic parameters of each signal pattern during the identification process. The characteristic parameters of each signal pattern of the radar emitter need to be set.

[0038] The expert rules in step S2 include:

[0039] The weight of carrier frequency in matching and identification, and the tolerance of carrier frequency in the matching and identification process;

[0040] The weight of pulse width in matching and identification, and the tolerance of pulse width in the matching and identification process;

[0041] The weight of repeated intervals in matching and identification, and the tolerance of repeated intervals in the matching and identification process;

[0042] The weight of the PRI reference value in matching and identification, and the tolerance of the PRI reference value in the matching and identification process;

[0043] The weight of the sweep in matching and identification, and the tolerance of the sweep in the matching and identification process;

[0044] The weight of pulse group conversion time in matching and identification, and the tolerance of pulse group conversion time in the matching and identification process;

[0045] The weight of duty cycle in matching and identification, and the tolerance of duty cycle in the matching and identification process;

[0046] The weight of the intra-pulse modulation type in matching identification;

[0047] Tolerance of modulation bandwidth in the matching identification process;

[0048] The weight of code element width in matching and recognition, and the tolerance of code element width in the matching and recognition process;

[0049] Identify the threshold.

[0050] Each characteristic parameter type set in step S3 adopts a one-vote veto system;

[0051] Furthermore, the one-vote veto means that if a certain characteristic parameter type of the signal pattern to be identified is inconsistent with the corresponding characteristic parameter type of the signal pattern in the target recognition library, the signal pattern is considered to be unmatched and no further matching degree calculation and signal pattern matching confidence calculation are required.

[0052] Furthermore, the characteristic parameter matching threshold in step S3 is a sign of whether the signal pattern in the target to-be-identified library matches the signal to be identified successfully. If the signal pattern matching confidence exceeds the matching threshold, it is considered that the signal pattern matches the signal to be identified successfully.

[0053] The characteristic parameters include: single parameter, range parameter, multi-value parameter, multi-interval parameter,

[0054] Furthermore, the calculation of the parameter matching degree of the single parameter, multi-value parameter, and multi-interval parameter adopts the 3σ criterion, where σ is the tolerance;

[0055] in:

[0056] The matching calculation formula for the single parameter input is as follows:

[0057]

[0058] Where kmax and kmin are the maximum and minimum values of the characteristic parameters in the recognition library, x is a certain characteristic parameter value, and x0 is the middle value between the maximum and minimum values of the characteristic parameters in the recognition library.

[0059] The multi-value parameter matching degree calculation is first based on the single-value matching degree P i , let the single value matching threshold be P0, and count P i The single-value matching degree of ≥P0 is summed up, and the multi-parameter matching degree P is calculated according to the following formula:

[0060]

[0061] Where P0 is the single parameter matching threshold set by the user, and m is the number of parameters in the multi-value parameter library to be identified.

[0062] The multi-interval parameter matching calculation first calculates the single value matching degree P based on the range parameter. i , let the single range matching threshold be P0, and count P i The single range matching degree of ≥P0 is summed up, and the multi-range parameter matching degree P is calculated according to the following formula:

[0063]

[0064] Where P0 is the single range matching threshold set by the user, and m is the number of range parameters in the multi-range parameter identification library.

[0065] The matching degree calculation formula of the range parameters is as follows:

[0066]

[0067] Where Bmax and Bmin are the maximum and minimum values of the parameter interval in the recognition library, and Smax and Smin are the maximum and minimum values of the parameter interval of the signal to be identified.

[0068] The calculation formula for the matching confidence Z of the signal pattern in step S6 is as follows:

[0069] Z=p1*q1+p2*q2+…+p n *q n ;

[0070] In the above formula, p1, p2, ...p n is the matching degree of each characteristic parameter, q1, q2, ...q n is the identification weight of each feature parameter;

[0071] The recognition weight satisfies the normalization condition, i.e. q1+q2+...+q n =1, n is the number of characteristic parameters.

[0072] The step S9 specifically outputs and displays the signal pattern and its matching confidence in step 8 with a matching degree greater than the matching threshold value in the software interface according to the characteristic parameter matching threshold value set in step S3.

[0073] The radar radiation sources include conventional radar signals, repetition frequency difference radar signals, PRI jitter radar signals, pulse Doppler signals, frequency agile signals and frequency diversity signals.

[0074] The advantages and positive effects of the present invention are:

[0075] (1) When setting up the target recognition library, the present invention provides the ability to set weights and tolerances for each characteristic parameter of each signal pattern of each type of radar, converting expert experience into recognition rules and then converting them into recognition algorithms through computer technology, thereby improving recognition accuracy;

[0076] (2) The present invention adopts the 3σ criterion when calculating the feature parameter matching degree. The parameter matching result is no longer either 0 or 1. The calculated parameter matching degree is more precise. Combined with the weight of each feature parameter, the matching confidence of each signal pattern is more precise and accurate, thereby improving the recognition accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0077] Figure 1 A schematic flow chart of a radar emitter parameter matching and identification method based on expert rules provided by the present invention. DETAILED DESCRIPTION

[0078] The preferred embodiments of the present invention are described in detail below with reference to the accompanying drawings so that the advantages and features of the present invention can be more easily understood by those skilled in the art, thereby making a clearer and more precise definition of the protection scope of the present invention.

[0079] A radar emitter parameter matching and identification method based on expert rules, such as Figure 1 As shown, the method includes the following steps:

[0080] S1. Establish target recognition library

[0081] Establish a target recognition library based on radar radiation source signal pattern data, and the target recognition library is used to record radar radiation source signal patterns;

[0082] S2. Setting Expert Rules

[0083] Setting expert rule parameters formed by expert experience into the target recognition library;

[0084] S3. Set matching rules

[0085] The matching rules include feature parameter type and feature parameter matching threshold;

[0086] S4. Obtain the data to be identified to form a target database to be identified

[0087] According to the characteristic parameter type matching principle set in step S3, the target to be identified library consisting of signal patterns that meet the matching principle is screened in the target identification library;

[0088] S5. Calculation of characteristic parameter matching degree

[0089] According to the tolerance of each characteristic parameter set in the target recognition library, the characteristic parameter of each signal pattern in the target to be recognized library is matched with the characteristic parameter of the signal to be recognized to obtain the matching degree of each characteristic parameter in the signal pattern;

[0090] S6. Signal pattern matching confidence calculation

[0091] Calculate the matching confidence between each signal pattern in the target to be identified library and the signal to be identified based on the recognition weights of each feature parameter set in the target identification library;

[0092] S7, repeating steps S5 and S6 until the calculation of matching degree and matching confidence is completed for all signal patterns;

[0093] S8, Signal Style Sorting

[0094] Record the matching confidence of each signal pattern in the target to-be-identified library with the signal pattern to be identified, and sort all signal patterns from high to low according to the signal pattern matching confidence;

[0095] S9. Matching result output

[0096] According to the matching threshold set in the matching principle in S3, the signal pattern results that meet the matching threshold requirements are output.

[0097] Each signal pattern of the radar radiation source signal pattern in step S1 includes:

[0098] Carrier type, carrier value, carrier weight, carrier tolerance;

[0099] Repeat interval type, repeat interval value, repeat interval weight, repeat interval tolerance;

[0100] Pulse width type, pulse width value, pulse width weight, pulse width tolerance;

[0101] Sweep type, sweep value, sweep weight, and sweep tolerance;

[0102] PRI reference value, PRI reference weight, PRI reference tolerance

[0103] Modulation type, modulation type weight;

[0104] Pulse group conversion time weight, pulse group conversion time tolerance;

[0105] Duty cycle value, duty cycle weight, duty cycle tolerance;

[0106] Intra-pulse modulation type weight;

[0107] Modulation bandwidth tolerance;

[0108] Symbol width value, symbol width weight, symbol width tolerance;

[0109] Identify the threshold.

[0110] The expert rules described in step S2 are specific to different radar emitter signals. The weight values of the characteristic parameters are not fixed. The weights and tolerances of the characteristic parameters of each signal pattern of each radar can be set independently. The expert rules are reflected in the characteristic parameters of each signal pattern during the identification process. The characteristic parameters of each signal pattern of the radar emitter need to be set.

[0111] The expert rules in step S2 include:

[0112] The weight of carrier frequency in matching and identification, and the tolerance of carrier frequency in the matching and identification process;

[0113] The weight of pulse width in matching and identification, and the tolerance of pulse width in the matching and identification process;

[0114] The weight of repeated intervals in matching and identification, and the tolerance of repeated intervals in the matching and identification process;

[0115] The weight of the PRI reference value in matching and identification, and the tolerance of the PRI reference value in the matching and identification process;

[0116] The weight of the sweep in matching and identification, and the tolerance of the sweep in the matching and identification process;

[0117] The weight of pulse group conversion time in matching and identification, and the tolerance of pulse group conversion time in the matching and identification process;

[0118] The weight of duty cycle in matching and identification, and the tolerance of duty cycle in the matching and identification process;

[0119] The weight of the intra-pulse modulation type in matching identification;

[0120] Tolerance of modulation bandwidth in the matching identification process;

[0121] The weight of code element width in matching and recognition, and the tolerance of code element width in the matching and recognition process;

[0122] Identify the threshold.

[0123] Each characteristic parameter type set in step S3 adopts a one-vote veto system;

[0124] Furthermore, the one-vote veto means that if a certain characteristic parameter type of the signal pattern to be identified is inconsistent with the corresponding characteristic parameter type of the signal pattern in the target recognition library, the signal pattern is considered to be unmatched and no further matching degree calculation and signal pattern matching confidence calculation are required.

[0125] Furthermore, the characteristic parameter matching threshold in step S3 is a sign of whether the signal pattern in the target to-be-identified library matches the signal to be identified successfully. If the signal pattern matching confidence exceeds the matching threshold, it is considered that the signal pattern matches the signal to be identified successfully.

[0126] The characteristic parameters include: single parameter, range parameter, multi-value parameter, multi-interval parameter,

[0127] Furthermore, the calculation of the parameter matching degree of the single parameter, multi-value parameter, and multi-interval parameter adopts the 3σ criterion, where σ is the tolerance;

[0128] in:

[0129] The matching calculation formula for the single parameter input is as follows:

[0130]

[0131]

[0132] Where kmax and kmin are the maximum and minimum values of the characteristic parameters in the recognition library, x is a certain characteristic parameter value, and x0 is the middle value between the maximum and minimum values of the characteristic parameters in the recognition library.

[0133] The multi-value parameter matching degree calculation is first based on the single-value matching degree P i , let the single value matching threshold be P0, and count P i The single-value matching degree of ≥P0 is summed up, and the multi-parameter matching degree P is calculated according to the following formula:

[0134]

[0135] Where P0 is the single parameter matching threshold set by the user, and m is the number of parameters in the multi-value parameter library to be identified.

[0136] The multi-interval parameter matching calculation first calculates the single value matching degree P based on the range parameter. i , let the single range matching threshold be P0, and count P i The single range matching degree of ≥P0 is summed up, and the multi-range parameter matching degree P is calculated according to the following formula:

[0137]

[0138] Where P0 is the single range matching threshold set by the user, and m is the number of range parameters in the multi-range parameter identification library.

[0139] The matching degree calculation formula of the range parameters is as follows:

[0140]

[0141] Where Bmax and Bmin are the maximum and minimum values of the parameter interval in the recognition library, and Smax and Smin are the maximum and minimum values of the parameter interval of the signal to be identified.

[0142] The calculation formula for the matching confidence Z of the signal pattern in step S6 is as follows:

[0143] Z=p1*q1+p2*q2+…+p n *q n ;

[0144] In the above formula, p1, p2, ...p n is the matching degree of each characteristic parameter, q1, q2, ...q n is the identification weight of each feature parameter;

[0145] The recognition weight satisfies the normalization condition, i.e. q1+q2+...+q n =1, n is the number of characteristic parameters.

[0146] The step S9 specifically outputs and displays the signal pattern and its matching confidence in step 8 with a matching degree greater than the matching threshold value in the software interface according to the characteristic parameter matching threshold value set in step S3.

[0147] The matching algorithm is currently applicable to conventional radar signals, frequency-variable radar, PRI jitter radar signals, pulse Doppler signals, frequency agile signals and frequency diversity signals.

[0148] The above descriptions are merely embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention's description and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A radar emitter parameter matching and identification method based on expert rules, characterized in that: The method comprises the following steps: S1. Establish target recognition library Establish a target recognition library based on radar radiation source signal pattern data, and the target recognition library is used to record radar radiation source signal patterns; S2. Setting Expert Rules Setting expert rule parameters formed by expert experience into the target recognition library; S3. Set matching rules The matching rules include characteristic parameter type and characteristic parameter matching threshold; S4. Obtain the data to be identified to form a target database to be identified According to the characteristic parameter type matching principle set in step S3, the signal patterns that meet the matching principle are screened in the target recognition library to form a target to be recognized library; S5. Calculation of characteristic parameter matching degree According to the tolerance of each characteristic parameter set in the target recognition library, the characteristic parameter of each signal pattern in the target to be recognized library is matched with the characteristic parameter of the signal to be recognized to obtain the matching degree of each characteristic parameter in the signal pattern; S6. Signal pattern matching confidence calculation Calculate the matching confidence between each signal pattern in the target to be identified library and the signal to be identified based on the recognition weights of each feature parameter set in the target identification library; S7, repeating steps S5 and S6 until the calculation of matching degree and matching confidence is completed for all signal patterns; S8, Signal Style Sorting Record the matching confidence of each signal pattern in the target to-be-identified library with the signal pattern to be identified, and sort all signal patterns from high to low according to the signal pattern matching confidence; S9. Matching result output According to the matching threshold set in the matching principle in S3, the signal pattern results that meet the matching threshold requirements are output.

2. The radar emitter parameter matching and identification method based on expert rules according to claim 1 is characterized in that: Each signal pattern of the radar radiation source signal pattern in step S1 includes: Carrier type, carrier value, carrier weight, carrier tolerance; Repeat interval type, repeat interval value, repeat interval weight, repeat interval tolerance; Pulse width type, pulse width value, pulse width weight, pulse width tolerance; Sweep type, sweep value, sweep weight, and sweep tolerance; PRI reference value, PRI reference weight, PRI reference tolerance Modulation type, modulation type weight; Pulse group conversion time weight, pulse group conversion time tolerance; Duty cycle value, duty cycle weight, duty cycle tolerance; Intra-pulse modulation type weight; Modulation bandwidth tolerance; Symbol width value, symbol width weight, symbol width tolerance; Identify the threshold.

3. The radar emitter parameter matching and identification method based on expert rules according to claim 1, characterized in that: The expert rules described in step S2 are for different radar radiation source signals. The weight values of each characteristic parameter are not fixed. The weights and tolerances of each characteristic parameter of each signal pattern of each radar can be set independently. The expert rules are reflected in the characteristic parameters of each signal pattern during the identification process. The characteristic parameters of each signal pattern of the radar radiation source need to be set.

4. The radar emitter parameter matching and identification method based on expert rules according to claim 1, characterized in that: The expert rules in step S2 include: The weight of carrier frequency in matching and identification, and the tolerance of carrier frequency in the matching and identification process; The weight of pulse width in matching and identification, and the tolerance of pulse width in the matching and identification process; The weight of repeated intervals in matching and identification, and the tolerance of repeated intervals in the matching and identification process; The weight of the PRI reference value in matching and identification, and the tolerance of the PRI reference value in the matching and identification process; The weight of the sweep in matching and identification, and the tolerance of the sweep in the matching and identification process; The weight of pulse group conversion time in matching and identification, and the tolerance of pulse group conversion time in the matching and identification process; The weight of duty cycle in matching and identification, and the tolerance of duty cycle in the matching and identification process; The weight of the intra-pulse modulation type in matching identification; Tolerance of modulation bandwidth in the matching identification process; The weight of code element width in matching and recognition, and the tolerance of code element width in the matching and recognition process; Identify the threshold.

5. The radar emitter parameter matching and identification method based on expert rules according to claim 1, characterized in that: Each characteristic parameter type set in step S3 adopts a one-vote veto system; The veto means that if a certain characteristic parameter type of the signal pattern to be identified is inconsistent with the corresponding characteristic parameter type of the signal pattern in the target recognition library, the signal pattern is considered to be unmatched and no further matching degree calculation and signal pattern matching confidence calculation are required.

6. The radar emitter parameter matching and identification method based on expert rules according to claim 1 is characterized in that: The characteristic parameter matching threshold in step S3 is a sign of whether the signal pattern in the target to-be-identified library matches the signal to be identified successfully. If the signal pattern matching confidence exceeds the matching threshold, it is considered that the signal pattern matches the signal to be identified successfully.

7. The radar emitter parameter matching and identification method based on expert rules according to any one of claims 1, 2, 4, and 5, characterized in that: The characteristic parameters include: single parameter, range parameter, multi-value parameter, and multi-interval parameter.

8. The radar emitter parameter matching and identification method based on expert rules according to claim 7 is characterized in that: The matching degree calculation formula of the range parameters is as follows: Among them, Bmax and Bmin are the maximum and minimum values of the parameter interval in the recognition library, and Smax and Smin are the maximum and minimum values of the parameter interval of the signal to be identified.

9. The radar emitter parameter matching and identification method based on expert rules according to claim 7, characterized in that: The matching degree calculation of the single parameter, multi-value parameter, and multi-interval parameter adopts the 3σ criterion, where σ is the tolerance, where: The matching degree calculation formula of the single parameter is as follows: In the above formula, kmax and kmin are the maximum and minimum values of the characteristic parameters in the recognition library, x is a certain characteristic parameter value, and x0 is the middle value between the maximum and minimum values of the characteristic parameters in the recognition library; The multi-value parameter matching degree calculation is first based on the single-value matching degree P i , let the single value matching threshold be P0, and count P i The single-value matching degree of ≥P0 is summed up, and the multi-parameter matching degree P is calculated according to the following formula: Where P0 is the single parameter matching threshold set by the user, and m is the number of parameters in the multi-value parameter library to be identified; The multi-interval parameter matching calculation first calculates the single value matching degree P based on the range parameter. i , let the single range matching threshold be P0, and count P i The single range matching degree of ≥P0 is summed up, and the multi-range parameter matching degree P is calculated according to the following formula: In the above formula, P0 is the single range matching threshold set by the user, and m is the number of range parameters in the multi-range parameter identification library.

10. The radar emitter parameter matching and identification method according to claim 1, characterized in that: The calculation formula for the matching confidence Z of the signal pattern in step S6 is as follows: Z=p1*q1+p2*q2+…+p n *q n In the above formula, p1, p2, ...p n is the matching degree of each characteristic parameter, q1, q2, ...q n is the identification weight of each feature parameter; The recognition weight satisfies the normalization condition, i.e. q1+q2+...+q n =1, n is the number of characteristic parameters.

11. The radar radiation source parameter matching and identification method according to claim 1, characterized in that: The step S9 specifically outputs the signal pattern and its matching confidence in step S8 whose matching degree is greater than the matching threshold according to the characteristic parameter matching threshold set in step S3.

12. The radar radiation source parameter matching and identification method according to claim 1, characterized in that: The radar radiation sources include conventional radar signals, repetition frequency difference radar signals, PRI jitter radar signals, pulse Doppler signals, frequency agile signals and frequency diversity signals.

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