A method, system, device and medium for generating an interferometer external radiation calibration value

Abstract

The application discloses an interferometer external radiation calibration value generation method, system, device and medium, wherein the method comprises the following steps: full pulse acquisition: obtaining original full pulses through a receiver of a signal receiving system; pulse error correction filtering: performing error correction filtering on all full pulses, deleting invalid pulses, and retaining valid pulses; pulse quantity statistics: counting whether the number of valid pulses reaches a preset value N, if not, continuing to obtain original full pulses by the receiver; fitting algorithm processing: performing phase difference fitting calculation on the obtained N valid pulses based on a root mean square error threshold δ to obtain a fitting optimal solution; and outputting the phase optimal solution: collecting and arranging the fitting optimal solution of each frequency point into an external radiation calibration table and storing the table into the signal receiving system. The application directly obtains original pulse data reported by the receiver, calculates the optimal solution of the antenna channel phase difference value through a specific algorithm in an offline fitting manner, and the calculation process is completely decoupled from the signal processing flow of the system.

Description

Technical Field

[0001] This invention relates to the field of radio reconnaissance and detection technology, and more particularly to the field of interferometer external radiation calibration, specifically to a method, system, device, and medium for generating interferometer external radiation calibration values. Background Technology

[0002] In the field of radio reconnaissance and detection, angle information is a fundamental element. In general industrial applications, signal angle measurement is often achieved using interferometers, the theoretical principle of which is as follows: Figure 1 As shown. The classic interferometer direction finding formula is:

[0003] in, for AB Baseline phase difference, D Baseline length i The azimuth of the incoming wave. l The wavelength is the signal wavelength. The azimuth angle of the incoming wave can be obtained by reversing this formula. i .

[0004] In practical engineering development, to calculate the azimuth angle of a signal using formulas, a crucial prerequisite must first be met: the entire signal receiving system must not introduce any additional phase due to its own inherent characteristics, and the channel phase difference acquired by the receiver must equal the path difference of the electromagnetic wave propagating in space. Therefore, all interferometer direction-finding devices that rely on phase difference calculations must undergo interferometer external radiation calibration.

[0005] The phase difference in the radio frequency (RF) channels of electronic devices is often inherent, stable, and cannot be eliminated. Therefore, in engineering design, a "measure first, subtract later" approach is often adopted. Before delivery, the interferometer direction-finding system is usually installed in a microwave anechoic chamber to simulate the spatial reception process of electromagnetic waves under normal operating conditions. The pulse sorting results reported are collected at each frequency point, and the phase difference between channels is recorded. The phase differences of all channels at all frequencies are summarized in a table. When the equipment is operating normally, the phase difference value is subtracted to obtain the true path difference of the signal as it propagates through space to the receiving antenna. The schematic diagram is shown below. Figure 2 As shown.

[0006] Traditional methods are simple and easy to understand in engineering implementation, but they also have significant shortcomings: First, calibration work has stringent requirements for the electromagnetic environment, necessitating the use of a microwave anechoic chamber or the shutdown of other potentially interfering electronic equipment to ensure signal purity during the calibration process. Therefore, external radiation calibration during periodic maintenance faces numerous difficulties in complex electromagnetic environments. Second, while the traditional method fully accepts the system-reported detection results as the truth table, this approach, in practice, has a low fault tolerance and cannot completely eliminate system measurement errors. Summary of the Invention

[0007] The purpose of this invention is to: generate the optimal value for external radiation calibration of an interferometer based on pulse phase difference numerical fitting technology, improve traditional external radiation calibration methods, optimize phase difference measurement accuracy, and enhance adaptability to complex electromagnetic environments in the field.

[0008] The technical problem to be solved by this invention is as follows: 1) Existing external radiation calibration schemes are not adaptable enough to complex electromagnetic space environments and lack anti-interference capabilities; 2) Existing external radiation calibration schemes rely too much on the system's own calculation results and have insufficient fault tolerance.

[0009] To address the aforementioned issues, this invention proposes a method, system, device, and medium for generating external radiation calibration values ​​for an interferometer. This invention abandons the signal sorting results of conventional system reception processing and directly acquires the raw pulse data reported by the receiver. It then calculates the optimal solution for the antenna channel phase difference using a specific algorithm through offline fitting, completely decoupling the calculation process from the system's signal processing flow.

[0010] The technical solution adopted in this invention is as follows: A method for generating external radiation calibration values ​​for an interferometer includes the following steps: S1. Full Pulse Acquisition: The raw full pulse is acquired through the receiver of the signal receiving system; S2. Pulse Error Correction Filtering: Perform error correction filtering on all pulses, delete invalid pulses, and retain valid pulses; S3. Pulse Count Statistics: Check whether the number of valid pulses has reached the preset pulse count value. N If the condition is not met, return to step S1. S4. Fitting algorithm processing: based on root mean square error threshold d On the income N Phase difference fitting calculation is performed on each effective pulse to obtain the optimal fitting solution; S5. Output the optimal phase solution: The optimal fitting solution for each frequency point is summarized and organized into an external radiation calibration table and stored in the signal receiving system.

[0011] Further, step S4 includes the following sub-steps: S401. The obtained N The valid pulses are sorted and waited for calculation in sequence. S402. Pulse No. 1 enters the queue. Pulse No. 2 is compared with pulse No. 1 to calculate the root mean square error of the phase difference. e ,like e ≤ d Then pulse 1 and pulse 2 will be merged into one cluster group; if e > d Then, pulse 1 and pulse 2 are divided into two cluster groups; S403. Calculate the results of the clustering process using the third pulse and the results of step S402. If... e ≤ d If the third pulse is classified into the corresponding cluster group, then the third pulse will be classified into the corresponding cluster group; if e > d Then, pulse number 3 will be identified as a new cluster group; S404. Perform calculation and clustering on pulse number 4 and the clustering results from step S403 until pulse number N completes the calculation and clustering; S405. For all clusters formed after calculating N valid pulses, count the number of pulses within each cluster and take the expected value of the phase difference of all pulses in the cluster with the largest number of pulses. x The optimal solution is output as the fit.

[0012] Furthermore, in step S2, the invalid pulse includes noise signals, harmonic signals, and intermodulation signals.

[0013] Furthermore, in step S3, the preset value of the pulse number N The root mean square error threshold is obtained through big data calculation; in step S4, the root mean square error threshold is... d The configuration depends on the hardware capabilities of the signal receiving system under test.

[0014] A system for generating external radiation calibration values ​​for an interferometer includes: The full-pulse acquisition module is configured to acquire the raw full pulse through the receiver of the signal receiving system; The pulse error correction and filtering module is configured to perform error correction and filtering on all pulses, deleting invalid pulses and retaining valid pulses; The pulse count module is configured to count whether the number of valid pulses has reached a preset pulse count value. N If the target is not reached, the original full pulse will continue to be acquired from the receiver. The fitting algorithm processing module is configured to be based on the root mean square error threshold. d On the income N Phase difference fitting calculation is performed on each effective pulse to obtain the optimal fitting solution; The output phase optimal solution module is configured to summarize and organize the optimal fitting solutions for each frequency point into an external radiation calibration table and store it in the signal receiving system.

[0015] Furthermore, the fitting algorithm processing module is configured as follows: The results N The valid pulses are sorted and waited for calculation in sequence. Add pulse number 1 to the queue, and calculate the root mean square error of the phase difference between pulse number 2 and pulse number 1. e ,like e ≤ d Then pulse 1 and pulse 2 will be merged into one cluster group; if e > d Then, pulse 1 and pulse 2 are divided into two cluster groups; Calculate the value of pulse number 3 with the clustering result from the previous step. If... e ≤ d If the third pulse is classified into the corresponding cluster group, then the third pulse will be classified into the corresponding cluster group; if e > d Then, pulse number 3 will be identified as a new cluster group; The fourth pulse is used to perform calculations and clustering with the clustering results from the previous step, until the Nth pulse completes the calculations and clustering. For all clusters formed after calculating N valid pulses, the number of pulses within each cluster is counted, and the expected value of the phase difference of all pulses in the cluster with the largest number of pulses is taken. x The optimal solution is output as the fit.

[0016] Furthermore, in the pulse error correction filtering module, the invalid pulse includes noise signals, harmonic signals, and intermodulation signals.

[0017] Furthermore, the pulse count module has a preset pulse count value. N The root mean square error threshold is obtained through big data calculations; in the fitting algorithm processing module, the root mean square error threshold is... d The configuration depends on the hardware capabilities of the signal receiving system under test.

[0018] A computer device includes a memory and a processor, the memory storing a computer program, the processor executing the computer program to implement the steps of a method for generating interferometer external radiation calibration values.

[0019] A computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of a method for generating external radiation calibration values ​​for an interferometer.

[0020] The beneficial effects of this invention are as follows: 1) Using the receiver's underlying raw full pulse as the data source, erroneous data can be flexibly filtered according to actual conditions, adapting to complex electromagnetic environments in the field. 2) The calculation process is carried out offline, and the calculation results are decoupled from the signal processing flow of the system under test, so as not to affect the normal working flow of the system under test and not to add extra design burden to it. 3) Compared with traditional methods, the calibration test of this invention changes from passive reception to active calculation, resulting in faster calibration speed. The fitting result serves as the optimal solution for channel phase correction, and its physical meaning is clear. 4) The solution has a clear concept, strong scalability, and is universally applicable to interferometer-based reconnaissance and detection equipment. Attached Figure Description

[0021] Figure 1 Schematic diagram of the direction finding principle of an interferometer.

[0022] Figure 2 Schematic diagram of external radiation calibration principle for reconnaissance and detection system.

[0023] Figure 3 Flowchart of the full-pulse fitting calculation method.

[0024] Figure 4 Flowchart of the phase fitting algorithm.

[0025] Figure 5 Pulse panorama.

[0026] Figure 6 Pulse grouping diagram.

[0027] Figure 7 Extract the optimal solution for the phase difference of the main signal pulse fitting. Detailed Implementation

[0028] 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.

[0029] Example 1 like Figure 3 As shown, this embodiment provides a method for generating external radiation calibration values ​​for an interferometer, including the following steps: S1. Full Pulse Acquisition: The raw full pulse is acquired through the receiver of the signal receiving system; S2. Pulse Error Correction Filtering: Perform error correction filtering on all pulses, delete invalid pulses, and retain valid pulses; S3. Pulse Count Statistics: Check whether the number of valid pulses has reached the preset pulse count value. N If the condition is not met, return to step S1. S4. Fitting algorithm processing: based on root mean square error threshold d On the incomeN Phase difference fitting calculation is performed on each effective pulse to obtain the optimal fitting solution; S5. Output the optimal phase solution: The optimal fitting solution for each frequency point is summarized and organized into an external radiation calibration table and stored in the signal receiving system.

[0030] Preferably, such as Figure 4 As shown, step S4 includes the following sub-steps: S401. The obtained N The valid pulses are sorted and waited for calculation in sequence. S402. Pulse No. 1 enters the queue. Pulse No. 2 is compared with pulse No. 1 to calculate the root mean square error of the phase difference. e ,like e ≤ d Then pulse 1 and pulse 2 will be merged into one cluster group; if e > d Then, pulse 1 and pulse 2 are divided into two cluster groups; S403. Calculate the results of the clustering process using the third pulse and the results of step S402. If... e ≤ d If the third pulse is classified into the corresponding cluster group, then the third pulse will be classified into the corresponding cluster group; if e > d Then, pulse number 3 will be identified as a new cluster group; S404. Perform calculation and clustering on pulse number 4 and the clustering results from step S403 until pulse number N completes the calculation and clustering; S405. For all clusters formed after calculating N valid pulses, count the number of pulses within each cluster and take the expected value of the phase difference of all pulses in the cluster with the largest number of pulses. x The optimal solution is output as the fit.

[0031] Preferably, in step S2, the invalid pulses include pulse data with obvious errors such as noise signals, harmonic signals, and intermodulation signals.

[0032] Preferably, in step S3, the preset value of the number of pulses N A value of 2000 is typically used, and the accuracy of the fitting results is ensured through big data calculations. In step S4, the root mean square error threshold... d The configuration depends on the hardware capabilities of the signal receiving system under test.

[0033] Accordingly, this embodiment also provides a system for generating external radiation calibration values ​​for an interferometer, including: The full-pulse acquisition module is configured to acquire the raw full pulse through the receiver of the signal receiving system; The pulse error correction and filtering module is configured to perform error correction and filtering on all pulses, deleting invalid pulses and retaining valid pulses; The pulse count module is configured to count whether the number of valid pulses has reached a preset pulse count value. N If the target is not reached, the original full pulse will continue to be acquired from the receiver. The fitting algorithm processing module is configured to be based on the root mean square error threshold. d On the income N Phase difference fitting calculation is performed on each effective pulse to obtain the optimal fitting solution; The output phase optimal solution module is configured to summarize and organize the optimal fitting solutions for each frequency point into an external radiation calibration table and store it in the signal receiving system.

[0034] Preferably, the fitting algorithm processing module is configured as follows: The results N The valid pulses are sorted and waited for calculation in sequence. Add pulse number 1 to the queue, and calculate the root mean square error of the phase difference between pulse number 2 and pulse number 1. e ,like e ≤ d Then pulse 1 and pulse 2 will be merged into one cluster group; if e > d Then, pulse 1 and pulse 2 are divided into two cluster groups; Calculate the value of pulse number 3 with the clustering result from the previous step. If... e ≤ d If the third pulse is classified into the corresponding cluster group, then the third pulse will be classified into the corresponding cluster group; if e > d Then, pulse number 3 will be identified as a new cluster group; The fourth pulse is used to perform calculations and clustering with the clustering results from the previous step, until the Nth pulse completes the calculations and clustering. For all clusters formed after calculating N valid pulses, the number of pulses within each cluster is counted, and the expected value of the phase difference of all pulses in the cluster with the largest number of pulses is taken. x The optimal solution is output as the fit.

[0035] Preferably, in the pulse error correction filtering module, the invalid pulses include pulse data with obvious errors such as noise signals, harmonic signals, and intermodulation signals.

[0036] Preferably, in the pulse count module, the pulse count preset value N A value of 2000 is typically used, and the accuracy of the fitting results is ensured through big data calculations. In the fitting algorithm processing module, the root mean square error threshold... dThe configuration depends on the hardware capabilities of the signal receiving system under test.

[0037] Example 2 This embodiment is based on embodiment 1: This embodiment provides a method for generating external radiation calibration values ​​for an interferometer. It utilizes a full-pulse offline numerical fitting method to calculate the optimal phase difference solution, achieving good results in external radiation calibration. This embodiment is illustrated in detail through simulation. In typical circuit systems, the phase change of radio frequency signals tends to stabilize after transmission. Phase jitter is mainly influenced by objective factors such as component system temperature and channel saturation. For ease of explanation, the full-pulse phase difference value is assumed to be in the range of 0-2. π Convert to a representation based on 0-1024. Assume that at this point... Figure 2 The phase difference Δ between the two sinusoidal signals radiated into the receiver is theoretically measured. ψ The value is 150, which corresponds to an angle of 52.73°. Due to operational errors and other unavoidable objective reasons, the receiver actually measures a superposition of multiple signals. Five of the more influential signals are selected for explanation and simulation calculations: Signal 1 is the measurement result of the receiver on the direct wave of the calibration signal; Signal 2 is used to simulate distortions introduced by the radio frequency channel or measurement ambiguity in the receiver; 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. Signal 5: Stray signals generated by the system itself or other signals of the same frequency that leak into the system and environmental noise.

[0038] 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%.

[0039] Using Excel's random function formulas, the phase differences of each signal are created as follows: Phase difference of signal 1: DPS = RANDBETWEEN(140,160), angle measurement range 49.2°~56.25°; Phase difference of signal 2: DPS = RANDBETWEEN(130,170), angle range 45.7°~ 59.8°; Phase difference of signal 3: DPS= RANDBETWEEN(60,100), angle range 21.1°~35.2°; Signal 4 phase difference: DPS = RANDBETWEEN(190,230), angle range 66.8°~80.9°; Phase difference of signal 5: DPS = RANDBETWEEN(60,230), angle range 21.1°~80.9°; The results obtained through numerical simulation and processing are as follows: Figure 5-Figure 7 As shown, where: Figure 5 This is a pulse panorama, representing all pulse phase difference results measured by the system. There are a total of 2000 phase difference results in the figure. The direct wave signal has the densest pulse density; considering the receiver's phase detection error, its reported phase difference is between 140 and 160 degrees. Signals 2 and 5 are simulated error sources, and their phase error range is larger than that of signal 1. Signals 3 and 4 do not overlap with signal 1 because of their different incident angles.

[0040] Figure 6 Indicates will Figure 5 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 and the direct wave are merged into the same group. Figure 5 The stray signals are incorporated into the main signal and the two reflected signals according to their distribution.

[0041] Figure 7 This embodiment describes a method that filters pulses, extracting the most numerous pulses as the main signal pulses and calculating the expected value of their phase difference. As the value of N increases, the red phase difference fitting curve rapidly approaches 149.89, or 52.69°. The calculated value differs from the theoretical value by only 0.04°, meeting engineering requirements in terms of accuracy, and also demonstrating good interference filtering effect.

[0042] As can be seen from the comparison of the three figures, the phase difference numerical fitting method described in this invention has obvious effects and has strong engineering application value when used for external radiation calibration of interferometers.

[0043] Example 3 This embodiment is based on embodiment 1: 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 method for generating interferometer external radiation calibration values ​​according to Embodiment 1. The computer program can be in the form of source code, object code, executable file, or some intermediate form.

[0044] Example 4 This embodiment is based on embodiment 1: This embodiment provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of a method for generating interferometer external radiation calibration values ​​according to 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. It should be noted that the content contained in the storage medium can be appropriately added or removed according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the storage medium does not include electrical carrier signals and telecommunication signals.

[0045] 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 method for generating external radiation calibration values ​​for an interferometer, characterized in that, Includes the following steps: S1. Full Pulse Acquisition: The raw full pulse is acquired through the receiver of the signal receiving system; S2. Pulse Error Correction Filtering: Perform error correction filtering on all pulses, delete invalid pulses, and retain valid pulses; S3. Pulse Count Statistics: Check whether the number of valid pulses has reached the preset pulse count value. N If the condition is not met, return to step S1. S4. Fitting algorithm processing: based on root mean square error threshold δ On the income N Phase difference fitting calculation is performed on each effective pulse to obtain the optimal fitting solution; S5. Output the optimal phase solution: Summarize and organize the optimal fitting solutions for each frequency point into an external radiation calibration table and store it in the signal receiving system; Step S4 includes the following sub-steps: S401. The obtained N The valid pulses are sorted and waited for calculation in sequence. S402. Pulse No. 1 enters the queue. Pulse No. 2 is compared with pulse No. 1 to calculate the root mean square error of the phase difference. 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; S403. Calculate the results of the clustering process using the third pulse and the results of step S402. 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; S404. Perform calculation and clustering on pulse number 4 and the clustering results from step S403 until pulse number N completes the calculation and clustering; S405. For all clusters formed after calculating N valid pulses, count the number of pulses within each cluster and take the expected value of the phase difference of all pulses in the cluster with the largest number of pulses. ξ The optimal solution is output as the fit.

2. The method for generating external radiation calibration values ​​for an interferometer according to claim 1, characterized in that, In step S2, the invalid pulse includes noise signals, harmonic signals, and intermodulation signals.

3. The method for generating external radiation calibration values ​​for an interferometer according to claim 1, characterized in that, In step S3, the preset value of the number of pulses N The root mean square error threshold is obtained through big data calculation; in step S4, the root mean square error threshold is... δ The configuration depends on the hardware capabilities of the signal receiving system under test.

4. A system for generating external radiation calibration values ​​for an interferometer, characterized in that, include: The full-pulse acquisition module is configured to acquire the raw full pulse through the receiver of the signal receiving system; The pulse error correction and filtering module is configured to perform error correction and filtering on all pulses, deleting invalid pulses and retaining valid pulses; The pulse count module is configured to count whether the number of valid pulses has reached a preset pulse count value. N If the target is not reached, the original full pulse will continue to be acquired from the receiver. The fitting algorithm processing module is configured to be based on the root mean square error threshold. δ On the income N Phase difference fitting calculation is performed on each effective pulse to obtain the optimal fitting solution; The output phase optimal solution module is configured to summarize and organize the frequency-point-by-frequency fitting optimal solution into an external radiation calibration table and store it in the signal receiving system. The fitting algorithm processing module is configured as follows: The results N The valid pulses are sorted and waited for calculation in sequence. Add pulse number 1 to the queue, and calculate the root mean square error of the phase difference between pulse number 2 and pulse number 1. 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; Calculate the value of pulse number 3 with the clustering result from the previous step. 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; The fourth pulse is used to perform calculations and clustering with the clustering results from the previous step, until the Nth pulse completes the calculations and clustering. For all clusters formed after calculating N valid pulses, the number of pulses within each cluster is counted, and the expected value of the phase difference of all pulses in the cluster with the largest number of pulses is taken. ξ The optimal solution is output as the fit.

5. The system for generating external radiation calibration values ​​for an interferometer according to claim 4, characterized in that, In the pulse error correction and filtering module, the invalid pulses include noise signals, harmonic signals, and intermodulation signals.

6. The system for generating external radiation calibration values ​​for an interferometer according to claim 4, characterized in that, The pulse count statistics module, the pulse count preset value N The root mean square error threshold is obtained through big data calculations; in the fitting algorithm processing module, the root mean square error threshold is... δ The configuration depends on the hardware capabilities of the signal receiving system under test.

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 method for generating the external radiation calibration value of the interferometer according to 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 method for generating the external radiation calibration value of the interferometer as described in any one of claims 1-3.

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