A method, system, device and medium for fast off-line evaluation of direction finding accuracy

Abstract

The application discloses a kind of fast off-line evaluation methods, system, equipment and medium of direction finding accuracy, wherein the method comprises the following steps: impulse screening: the whole course of the whole impulse of the equipment to be measured is filtered, and the target pulse is retained, and the invalid pulse is removed;Impulse grouping: the filtered pulse is grouped according to frequency and pulse time period, and the test point direction corresponding to the pulse is obtained according to the time period of the pulse;Parallel computing: based on the root mean square error threshold, the numerical statistical calculation of the angle measurement result of all frequency grouping pulses is carried out in parallel;Result output: the direction finding error statistics of the remaining pulse after eliminating the interference signal, and the direction finding result of the direct wave pulse is calculated again according to the preset index.The application takes the bottom layer original full pulse of the receiver as the data source, and can flexibly filter invalid data offline according to the actual situation, to adapt to the complex electromagnetic environment in the field.

Description

Technical Field

[0001] This invention relates to the field of radio reconnaissance and detection technology, and more particularly to the field of direction finding accuracy verification and evaluation. Specifically, it relates to a rapid offline evaluation method, system, device, and medium for direction finding accuracy. Background Technology

[0002] In the field of radio reconnaissance and detection, the direction of arrival is one of the core indicators for signal detection. A schematic diagram of a commonly used interferometer direction-finding system in industrial applications is shown below. Figure 1 As shown, the system architecture typically consists of two main parts: electromagnetic detection and signal processing. Electromagnetic detection includes antenna reception, radio frequency amplification, and digital sampling, converting electromagnetic waves propagating in space into digital signals measured by the receiver. Signal processing includes signal sorting, signal identification, and signal fusion. Through a series of software processing steps, the digital signals reported by the receiver are converted into radio detection results with intelligence value. The electromagnetic detection stage relies on the performance of the equipment hardware, while the signal processing stage tests the capabilities of the software algorithms. Radio signal detection requires a combination of hardware and software approaches, working in tandem.

[0003] All types of airborne, shipborne, vehicle-mounted, or ground-based fixed detection equipment require regular direction-finding accuracy verification and calibration during production, commissioning, and maintenance. Currently, there is no unified standard for direction-finding accuracy verification in the industry, and technological development is relatively lagging. In the industrial sector, direction-finding verification of radio detection equipment mainly relies on manual methods, which are inaccurate and inefficient.

[0004] For large-scale detection equipment, the traditional method involves first selecting an open area, then using a total station, map, and compass to determine the normal direction or a specific direction of the receiving antenna of the system under test, from which electromagnetic waves are radiated. After the equipment under test detects the electromagnetic waves, it processes them using radio frequency methods and a series of internal signal processing steps to produce target information and direction-finding results. Finally, the direction-finding accuracy of the system under test at different angles is calculated through manual comparison.

[0005] For small detection devices, closed testing is typically conducted using a large microwave anechoic chamber. The device under test (DUT) is fixed to a mechanical turntable, and a transmitting antenna positioned in a fixed location within the anechoic chamber radiates electromagnetic waves toward the turntable. Rotating the turntable allows the DUT to receive electromagnetic wave signals at different angles. Once the DUT detects the electromagnetic waves, it produces target information and direction-finding results.

[0006] Traditional testing methods are simple in approach and do not require advanced technology. However, they also have significant shortcomings: First, the testing process has high requirements for the site or environment, requiring a microwave anechoic chamber or open space; second, they are not highly adaptable to complex electromagnetic environments, and it is difficult to accurately evaluate system indicators when there is signal interference or reflected signals; third, the test data are all derived from the final results after system signal processing, and the detection and evaluation of system hardware performance is not in-depth enough. Summary of the Invention

[0007] The technical problem to be solved by this invention is as follows:

[0008] 1) Existing direction finding accuracy detection methods are not sufficiently adaptable to complex electromagnetic environments in the external field;

[0009] 2) Existing methods for detecting direction finding accuracy are limited and do not provide a clear and thorough understanding of the underlying hardware capabilities of the equipment.

[0010] 3) The testing process is inefficient, takes a long time, and is costly.

[0011] To address the aforementioned issues, this invention proposes a rapid offline evaluation method, system, equipment, and medium for direction finding accuracy, enabling ground-based calibration of direction finding accuracy to adapt to testing in complex electromagnetic environments.

[0012] The technical solution adopted in this invention is as follows:

[0013] A rapid offline evaluation method for direction finding accuracy includes the following steps:

[0014] S1. Pulse Filtering: Filters all pulses throughout the entire range of the device under test, retaining the target pulses and removing invalid pulses;

[0015] S2. Pulse Grouping: The filtered pulses are grouped according to frequency and pulse time period, and the location of the test point corresponding to the pulse is obtained according to the time period of the pulse;

[0016] S3. Parallel computing: Numerical statistical calculations of angle measurement results are performed in parallel on pulses of all frequency groups based on the root mean square error threshold δ;

[0017] S4. Result Output: Perform direction finding error statistics on the remaining pulses after removing interference signals, and recalculate the direction finding results of the direct wave pulses according to preset indicators.

[0018] Furthermore, step 3 includes the following sub-steps:

[0019] S301. Filter all pulses according to the frequency, pulse width, and repetition rate set during the test to obtain N pulses with matched electrical parameters, and wait for calculation in sequence;

[0020] S302. The first pulse enters the queue. The second pulse and the first pulse are calculated to obtain the root mean square error value ε of the angle. If ε≤δ, the first pulse and the second pulse are merged into one cluster group; if ε>δ, the first pulse and the second pulse are divided into two cluster groups.

[0021] S303. Calculate the clustering results of the third pulse with those of step S302. If ε≤δ, then classify the third pulse into the corresponding cluster group; if ε>δ, then determine the third pulse as a new cluster group.

[0022] S304. Calculate the results of the clustering of the 4th pulse and the clustering of the Nth pulse, and so on until the Nth pulse is calculated, thereby clustering the N pulses according to their azimuth angles;

[0023] S306. After calculating N pulses, count the number of pulses within each cluster. The cluster with the highest number of pulses is selected as the direct wave pulse, with a count of N. max ;

[0024] S307. The direct wave pulse obtained in step S306 is processed according to the system index δ of the device under test. 系统 The calculation is repeated, following steps S302 to S305, to obtain the system index δ. 系统 The number of pulses N δ ;

[0025] S308. The direction finding result of the tested equipment is N. δ The average angle of each pulse, the direction finding accuracy is

[0026] Furthermore, in step S1, the target pulse includes a pulse with the same frequency, pulse width, and repetition rate as the preset signal, and the invalid pulse includes environmental clutter and interference signals.

[0027] Furthermore, in step S4, the interference signal includes reflected waves, spatial diffraction signals, and diffraction signals.

[0028] A rapid offline evaluation system for direction finding accuracy includes:

[0029] The pulse filtering module is configured to filter all pulses throughout the entire process of the device under test, retaining target pulses and removing invalid pulses.

[0030] The pulse grouping module is configured to group the filtered pulses according to their frequency and pulse time period, and obtain the location of the test point corresponding to the pulse based on the time period of the pulse.

[0031] The parallel computing module is configured to perform numerical statistical calculations of the angle measurement results in parallel on pulses of all frequency groups based on the root mean square error threshold δ.

[0032] The result output module is configured to perform direction finding error statistics on the remaining pulses after removing interference signals, and to recalculate the direction finding results of the direct wave pulses according to preset indicators.

[0033] Furthermore, the parallel computing module is configured to implement the following steps:

[0034] S301. Filter all pulses according to the frequency, pulse width, and repetition rate set during the test to obtain N pulses with matched electrical parameters, and wait for calculation in sequence;

[0035] S302. The first pulse enters the queue. The second pulse and the first pulse are calculated to obtain the root mean square error value ε of the angle. If ε≤δ, the first pulse and the second pulse are merged into one cluster group; if ε>δ, the first pulse and the second pulse are divided into two cluster groups.

[0036] S303. Calculate the clustering results of the third pulse with those of step S302. If ε≤δ, then classify the third pulse into the corresponding cluster group; if ε>δ, then determine the third pulse as a new cluster group.

[0037] S304. Calculate the results of the clustering of the 4th pulse and the clustering of the Nth pulse, and so on until the Nth pulse is calculated, thereby clustering the N pulses according to their azimuth angles;

[0038] S306. After calculating N pulses, count the number of pulses within each cluster. The cluster with the highest number of pulses is selected as the direct wave pulse, with a count of N. max ;

[0039] S307. The direct wave pulse obtained in step S306 is processed according to the system index δ of the device under test. 系统 The calculation is repeated, following steps S302 to S305, to obtain the system index δ. 系统 The number of pulses N δ ;

[0040] S308. The direction finding result of the tested equipment is N. δ The average angle of each pulse, the direction finding accuracy is

[0041] Furthermore, in the pulse screening module, the target pulse includes pulses with the same frequency, pulse width, and repetition rate as the preset signal, and the invalid pulses include environmental noise and interference signals.

[0042] Furthermore, in the result output module, the interference signal includes reflected waves, spatial diffraction signals, and diffraction signals.

[0043] A computer device includes a memory and a processor, the memory storing a computer program, characterized in that the processor executes the computer program to implement the steps of a rapid offline evaluation method for direction finding accuracy.

[0044] A computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of a method for rapid offline evaluation of direction-finding accuracy.

[0045] The beneficial effects of this invention are as follows:

[0046] 1) Using the receiver's underlying raw full pulse as the data source, invalid data can be flexibly filtered offline according to the actual situation, adapting to complex electromagnetic environments in the field;

[0047] 2) The calculation process is carried out offline, and the calculation results are decoupled from the signal processing flow of the system under test, eliminating the signal processing link of the system under test and greatly speeding up the system testing speed.

[0048] 3) Pulse-level numerical statistical calculations provide a more thorough verification of the underlying hardware capabilities of the system under test, and have stronger penetration in the verification.

[0049] 4) The solution has a clear concept, strong scalability, and is universally applicable to various types of radio reconnaissance and detection equipment. Attached Figure Description

[0050] Figure 1 Schematic diagram of an interferometer direction finding system.

[0051] Figure 2 Flowchart of the method for rapid offline evaluation of direction finding accuracy in Embodiment 1 of the present invention.

[0052] Figure 3 The flowchart of parallel numerical statistical calculation logic in Embodiment 1 of the present invention.

[0053] Figure 4 The pulse panoramic view in Embodiment 2 of the present invention.

[0054] Figure 5 Pulse grouping diagram in Embodiment 2 of the present invention.

[0055] Figure 6 The main signal pulse and system index pulse diagram in Embodiment 2 of the present invention. Detailed Implementation

[0056] To provide a clearer understanding of the technical features, objectives, and effects of the present invention, specific embodiments are now described. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention; that is, the described embodiments are only a part of the embodiments of the invention, not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0057] Example 1

[0058] like Figure 2 As shown, this embodiment provides a rapid offline evaluation method for direction finding accuracy, including the following steps:

[0059] S1. Pulse Filtering: The entire pulse stream from the device under test is filtered to retain target pulses and remove invalid pulses. Preferably, the target pulse can be a pulse with the same frequency, pulse width, and repetition rate as a preset signal, and invalid pulses can be noise and interference signals in the environment.

[0060] S2. Pulse Grouping: The filtered pulses are grouped according to frequency and pulse time period, based on the time period of the pulse (T1, T2...T...). n The azimuth of the test point corresponding to the pulse is obtained (θ1, θ2...θ). n ).

[0061] S3. Parallel computing: Numerical statistical calculations of angle measurement results are performed in parallel on pulses of all frequency groups based on the root mean square error threshold δ.

[0062] S4. Result Output: Perform direction-finding error statistics on the remaining pulses after removing interference signals, and recalculate the direction-finding results of the direct wave pulses according to preset indicators. Preferably, the interference signal can be a reflected wave, a spatial diffraction signal, or a diffracted signal.

[0063] Preferably, such as Figure 3 As shown, step 3 includes the following sub-steps:

[0064] S301. Filter all pulses according to the frequency, pulse width, and repetition rate set during the test to obtain N pulses with matched electrical parameters, and wait for calculation in sequence;

[0065] S302. The first pulse enters the queue. The second pulse and the first pulse are calculated to obtain the root mean square error value ε of the angle. If ε≤δ, the first pulse and the second pulse are merged into one cluster group; if ε>δ, the first pulse and the second pulse are divided into two cluster groups.

[0066] S303. Calculate the clustering results of the third pulse with those of step S302. If ε≤δ, then classify the third pulse into the corresponding cluster group; if ε>δ, then determine the third pulse as a new cluster group.

[0067] S304. Calculate the results of the clustering of the 4th pulse and the clustering of the Nth pulse, and so on until the Nth pulse is calculated, thereby clustering the N pulses according to their azimuth angles;

[0068] S306. After calculating N pulses, count the number of pulses within each cluster. The cluster with the highest number of pulses is selected as the direct wave pulse, with a count of N. max ;

[0069] S307. The direct wave pulse obtained in step S306 is processed according to the system index δ of the device under test. 系统 The calculation is repeated, following steps S302 to S305, to obtain the system index δ. 系统 The number of pulses N δ ;

[0070] S308. The direction finding result of the tested equipment is N. δ The average angle of each pulse, the direction finding accuracy is

[0071] Preferably, this embodiment selects the full-pulse data recorded during the operation of the radio detection equipment as the input value for evaluating its direction-finding accuracy, instead of focusing on the specific signal reception results during the test. Changing the original test scheme from comparing final target-level results to post-test analysis of pulse data shortens the test time and improves work efficiency.

[0072] Preferably, for large detection equipment, a mobile test radiation source is set up, moving within the direction-finding capability range of the equipment under test and radiating electromagnetic waves. During the movement, test points are set at regular azimuth angles to accurately record their geographical location information and signal characteristic parameters (including frequency, pulse width, repetition rate, radiation time, etc.) relative to the equipment under test. After the motion test is completed, the recorded data of the equipment under test is compared with preset information, and calculations are performed according to the algorithm described below.

[0073] Preferably, for small reconnaissance equipment, the testing methods for large equipment can be followed, or a turntable can be used for fixed-point testing, but a microwave anechoic chamber is not required.

[0074] Preferably, multiple sets of signals can be superimposed during the test to perform the test simultaneously, traversing the operating frequency band of the device under test and improving test efficiency.

[0075] Example 2

[0076] This embodiment is based on embodiment 1:

[0077] This embodiment provides a rapid offline evaluation method for direction finding accuracy. Utilizing pulse angle numerical statistical calculations, it achieves good results in direction finding accuracy verification. This embodiment is illustrated in detail through simulation.

[0078] In radio reconnaissance scenarios, when the spatial orientation of the radiation source is relatively fixed, the target angle detected by radio tends to be stable. For large radio equipment or airborne equipment, small fluctuations in the angle measurement results are mainly affected by the following factors: 1. Atmospheric circulation causing cloud cover changes alters the atmospheric reflection of low-band signals, especially shortwave and VHF signals, ultimately affecting the signal's direction of origin; 2. Fixed buildings or steep slopes near the equipment cause signal reflection; 3. Signal power that is too high or too low, approaching the dynamic range of the system's radio frequency channel, causes measurement errors in the receiver; 4. The presence of co-channel noise or spurious signals in space.

[0079] To simplify the explanation, we assume the true direction of the incoming wave at this moment is 40°. Due to various reasons, the receiver actually measures a superposition of multiple signals. We select five of the most influential signals for illustration and simulation calculation:

[0080] Signal 1 is the measurement result of the receiver on the direct wave signal;

[0081] Signal 2 is used to simulate distortions introduced by the radio frequency channel or measurement ambiguity in the receiver;

[0082] Signals 3 and 4 simulate the reflection and diffraction of the calibration signal during its propagation in space radiation. They have the same parameters as the main signal but different angles.

[0083] Signal 5: Stray signals generated by the system itself or other signals of the same frequency that leak into the system and environmental noise.

[0084] Theoretically, the direct wave of a signal has the shortest path and the least propagation attenuation, therefore it should be subjected to the most pulses from signal 1. To simulate a complex electromagnetic environment, the pulse density ratio between the signals is set to 4:1:1:1:1, meaning that the pulse density of signals 2 to 5, which are interference signals, is 25% of that of the calibration signal, and the pulse interference-to-signal ratio in this scenario is 50%.

[0085] Use Excel software to create a random number function to simulate the random distribution of signal angle measurement results:

[0086] Signal 1 angle:

[0087] θ1 = RANDBETWEEN(38,42), the angle measurement range is 38°~42°;

[0088] Signal 2 angle:

[0089] θ2 = RANDBETWEEN(36, 44), the angle measurement range is 36° to 44°;

[0090] Signal 3 angle:

[0091] θ3 = RANDBETWEEN(25, 29), angle measurement range 25°~29°;

[0092] Signal 4 angle:

[0093] θ4 = RANDBETWEEN(55,59), the angle measurement range is 55°~59°;

[0094] Signal 5 angle:

[0095] θ5 = RANDBETWEEN(25,59), the angle measurement range is 25° to 59°.

[0096] Through software numerical simulation Figures 4 to 6 As shown below:

[0097] Figure 4 This is a pulse panorama, representing all pulse results measured by the system. There are 2000 angle results in total. The direct wave signal has the densest pulse density; considering receiver measurement errors, its reported angles are between 38 and 42 degrees. Signals 2 and 5 are artificially introduced error sources, and their fluctuation range is larger than that of signal 1. Signals 3 and 4 do not overlap with signal 1 because of their different incident angles.

[0098] Figure 5 Indicates will Figure 4 The pulses shown are grouped into three groups, consisting mainly of direct waves and two reflected signals. A comparison before and after processing reveals that... Figure 5 The error signal in the signal is combined with the direct wave to form the main signal. Figure 4 The stray signals are incorporated into the main signal and the two reflected signals according to their distribution.

[0099] Figure 6 This means that the method described in this embodiment filters the pulses, extracting the group with the largest number of pulses as the main signal pulses. Statistical analysis shows that the ratio of bright pulses to direct wave main signal pulses that meet the system specifications is 43.91%, meaning that in the simulation case, the receiver's accuracy in pulse direction measurement is 43.91%.

[0100] As can be seen from the comparison of the three figures, the pulse offline statistical method described in this invention has good results when used for line accuracy verification and has strong engineering application value.

[0101] Example 3

[0102] This embodiment provides a rapid offline evaluation system for direction finding accuracy, including:

[0103] The pulse filtering module is configured to filter all pulses throughout the entire process of the device under test, retaining target pulses and removing invalid pulses.

[0104] The pulse grouping module is configured to group the filtered pulses according to their frequency and pulse time period, and obtain the location of the test point corresponding to the pulse based on the time period of the pulse.

[0105] The parallel computing module is configured to perform numerical statistical calculations of the angle measurement results in parallel on pulses of all frequency groups based on the root mean square error threshold δ.

[0106] The result output module is configured to perform direction finding error statistics on the remaining pulses after removing interference signals, and to recalculate the direction finding results of the direct wave pulses according to preset indicators.

[0107] Preferably, the parallel computing module is configured to implement the following steps:

[0108] S301. Filter all pulses according to the frequency, pulse width, and repetition rate set during the test to obtain N pulses with matched electrical parameters, and wait for calculation in sequence;

[0109] S302. The first pulse enters the queue. The second pulse and the first pulse are calculated to obtain the root mean square error value ε of the angle. If ε≤δ, the first pulse and the second pulse are merged into one cluster group; if ε>δ, the first pulse and the second pulse are divided into two cluster groups.

[0110] S303. Calculate the clustering results of the third pulse with those of step S302. If ε≤δ, then classify the third pulse into the corresponding cluster group; if ε>δ, then determine the third pulse as a new cluster group.

[0111] S304. Calculate the results of the clustering of the 4th pulse and the clustering of the Nth pulse, and so on until the Nth pulse is calculated, thereby clustering the N pulses according to their azimuth angles;

[0112] S306. After calculating N pulses, count the number of pulses within each cluster. The cluster with the highest number of pulses is selected as the direct wave pulse, with a count of N. max ;

[0113] S307. The direct wave pulse obtained in step S306 is processed according to the system index δ of the device under test. 系统 The calculation is repeated, following steps S302 to S305, to obtain the system index δ.系统 The number of pulses N δ ;

[0114] S308. The direction finding result of the tested equipment is N. δ The average angle of each pulse, the direction finding accuracy is

[0115] Preferably, in the pulse screening module, the target pulse includes pulses with the same frequency, pulse width, and repetition rate as the preset signal, and the invalid pulses include environmental noise and interference signals.

[0116] Preferably, in the result output module, the interference signal includes reflected waves, spatial diffraction signals, and diffraction signals.

[0117] Example 4

[0118] This embodiment is based on embodiment 1:

[0119] This embodiment provides a computer device, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the steps of the rapid offline evaluation method for direction-finding accuracy of Embodiment 1. The computer program can be in the form of source code, object code, executable file, or some intermediate form.

[0120] Example 5

[0121] This embodiment is based on embodiment 1:

[0122] This embodiment provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the rapid offline evaluation method for direction-finding accuracy described in Embodiment 1. The computer program can be in the form of source code, object code, executable file, or some intermediate form. The storage medium includes any entity or device capable of carrying computer program code, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc.

[0123] It should be noted that, for the sake of simplicity, the foregoing method embodiments are described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

Claims

1. A rapid offline evaluation method for direction finding accuracy, characterized in that, Includes the following steps: S1. Pulse Filtering: Filters all pulses throughout the entire process of the device under test, retaining the target pulses and removing invalid pulses; S2. Pulse Grouping: The filtered pulses are grouped according to frequency and pulse time period, and the location of the test point corresponding to the pulse is obtained according to the time period of the pulse; S3. Parallel Computing: Based on Root Mean Square Error Threshold δ Numerical statistical calculations of angle measurement results are performed in parallel for pulses of all frequency groups; S4. Result Output: Perform direction finding error statistics on the remaining pulses after removing interference signals, and recalculate the direction finding results of the direct wave pulses according to preset indicators; Step 3 includes the following sub-steps: S301. Filter all pulses according to the frequency, pulse width, and repetition rate set during the test to obtain... N Each pulse with matched electrical parameters is sequentially awaited for calculation. S302. The first pulse enters the queue. The second pulse is calculated in conjunction with the first pulse to determine the root mean square error of the angle. ε ,like ε ≤ δ Then, pulse number 1 and pulse number 2 will be merged into one cluster group; like ε > δ Then, pulse 1 and pulse 2 are divided into two cluster groups; S303. Calculate the results of the clustering process using the third pulse and the results of step S302. If... ε ≤ δ Then, pulse number 3 will be classified into the corresponding cluster group; like ε > δ Then, pulse number 3 will be identified as a new cluster group; S304. Calculate the results of the clustering in step S303 using pulse number 4; S305. Until the... N The calculation is completed by the first pulse, thus... N The pulses are clustered according to their azimuth angle; S306. Targeting N After calculating each pulse, the number of pulses within each cluster is counted. The cluster with the most pulses is selected as the direct wave pulse, with a count of [number missing]. N max ; S307. The direct wave pulse obtained in step S306 is processed according to the system specifications of the device under test. δ 系统 Repeat the calculations, following steps S302 to S305, to obtain the system indicators that are met. δ 系统 pulse number N δ ; S308. The direction finding result of the device under test is N δ The average angle of each pulse, the direction finding accuracy is .

2. The rapid offline evaluation method for direction finding accuracy according to claim 1, characterized in that, In step S1, the target pulse includes pulses with the same frequency, pulse width, and repetition rate as the preset signal, and the invalid pulse includes noise and interference signals in the environment.

3. The rapid offline evaluation method for direction finding accuracy according to claim 1, characterized in that, In step S4, the interference signals include reflected waves, spatial diffraction signals, and diffraction signals.

4. A rapid offline evaluation system for direction finding accuracy, characterized in that, include: The pulse filtering module is configured to filter all pulses throughout the entire process of the device under test, retaining target pulses and removing invalid pulses. The pulse grouping module is configured to group the filtered pulses according to their frequency and pulse time period, and obtain the location of the test point corresponding to the pulse based on the time period of the pulse. The parallel computing module is configured based on the root mean square error threshold. δ Numerical statistical calculations of angle measurement results are performed in parallel for pulses of all frequency groups; The result output module is configured to perform direction finding error statistics on the remaining pulses after removing interference signals, and to recalculate the direction finding results of the direct wave pulses according to preset indicators. The parallel computing module is configured to perform the following steps: S301. Filter all pulses according to the frequency, pulse width, and repetition rate set during the test to obtain... N Each pulse with matched electrical parameters is sequentially awaited for calculation. S302. The first pulse enters the queue. The second pulse is calculated in conjunction with the first pulse to determine the root mean square error of the angle. ε ,like ε ≤ δ Then, pulse number 1 and pulse number 2 will be merged into one cluster group; like ε > δ Then, pulse 1 and pulse 2 are divided into two cluster groups; S303. Calculate the results of the clustering process using the third pulse and the results of step S302. If... ε ≤ δ Then, pulse number 3 will be classified into the corresponding cluster group; like ε > δ Then, pulse number 3 will be identified as a new cluster group; S304. Calculate the results of the clustering in step S303 using pulse number 4; S305. Until the... N The calculation is completed by the first pulse, thus... N The pulses are clustered according to their azimuth angle; S306. Targeting N After calculating each pulse, the number of pulses within each cluster is counted. The cluster with the most pulses is selected as the direct wave pulse, with a count of [number missing]. N max ; S307. The direct wave pulse obtained in step S306 is processed according to the system specifications of the device under test. δ 系统 Repeat the calculations, following steps S302 to S305, to obtain the system indicators that are met. δ 系统 pulse number N δ ; S308. The direction finding result of the device under test is N δ The average angle of each pulse, the direction finding accuracy is .

5. The rapid offline evaluation system for direction finding accuracy according to claim 4, characterized in that, In the pulse filtering module, the target pulses include pulses with the same frequency, pulse width, and repetition rate as the preset signal, while invalid pulses include environmental noise and interference signals.

6. The rapid offline evaluation system for direction finding accuracy according to claim 4, characterized in that, In the result output module, the interference signals include reflected waves, spatial diffraction signals, and diffraction signals.

7. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the rapid offline evaluation method for direction finding accuracy as described in any one of claims 1-3.

8. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the rapid offline evaluation method for direction finding accuracy as described in any one of claims 1-3.

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