Electronic signal reconnaissance equipment construction method and device and storage medium

Abstract

The invention provides an electronic signal reconnaissance equipment construction method and device and a storage medium, and belongs to the technical field of equipment construction, and the method comprises the steps: importing electronic signal reconnaissance equipment construction demand data, and obtaining a radio frequency link parameter set from a pre-constructed radio frequency link database according to the electronic signal reconnaissance equipment construction demand data; obtaining a multi-channel signal processing parameter set from a pre-constructed multi-channel signal processing database according to the construction demand data of the electronic signal reconnaissance equipment; and gathering the radio frequency link parameter set and the multichannel signal processing parameter set to obtain a to-be-processed reconnaissance equipment construction data set. According to the invention, the problems of large size, high weight and large signal transmission loss under the traditional discrete board-level integrated architecture are solved, and the PCB design cycle is shortened, the cost is reduced, and the function upgrading process is simplified; the problems of long development period, poor compatibility and adaptability and low anti-electromagnetic interference capability of multi-channel signal sampling and signal processing functions are solved.

Description

Technical Field

[0001] This invention mainly relates to the field of equipment construction technology, specifically to a method, apparatus, and storage medium for constructing an electronic signal reconnaissance device. Background Technology

[0002] Traditional electronic signal reconnaissance equipment mainly consists of key core functional modules such as receiving antenna arrays, RF front-end modules, microwave frequency conversion channels, multi-channel sampling modules, and digital signal processing modules. It is typically designed with a "metal cavity + PCB board" combination for board-level integration, using cables and connectors for signal interaction. This discrete board-level integration layout design suffers from problems such as increased equipment size due to PCB cross-board routing and inter-module connector interactions; high-frequency signal cross-board transmission can cause electromagnetic interference, requiring additional redundant structures such as shielding cavities and impedance matching networks, which cannot meet the requirements for miniaturization and lightweighting. In existing electronic signal reconnaissance equipment, the RF front-end module and microwave frequency conversion channel are designed in a mixed configuration, while the multi-channel sampling module and digital signal processing module are designed with a discrete PCB architecture. This requires separate schematic design, PCB layout, and joint debugging for each module, resulting in a long design and development cycle. Upgrading module functionality requires redesigning the PCB routing, leading to poor compatibility and adaptability, which has become a key bottleneck restricting the development of high integration and miniaturization of equipment.

[0003] Due to limitations in discrete component manufacturing processes, electronic signal reconnaissance equipment suffers from impedance deviations and length tolerances in its various functional modules, connectors, and RF cables. In particular, there are issues with mixer / cavity filter center frequency drift and inconsistent microwave switch insertion losses. Multi-channel amplitude-phase consistency errors exhibit significant frequency dependence at broadband operating frequencies. Traditional discrete correction methods, which consider correction time and data storage space, and adjust amplitude-phase consistency errors according to a certain frequency step and local oscillator interval, cannot fully accommodate the reception of large instantaneous broadband signals within the reconnaissance equipment's operating range. This directly leads to decreased direction-finding accuracy, increased signal sorting and identification error rates, and severely impacts the reliability and stability of electronic signal reconnaissance equipment. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide a method, apparatus and storage medium for constructing an electronic signal reconnaissance device, which addresses the shortcomings of the prior art.

[0005] The technical solution of the present invention to solve the above-mentioned technical problems is as follows: A method for constructing an electronic signal reconnaissance device, comprising the following steps: Import the electronic signal reconnaissance equipment construction requirement data, and obtain the radio frequency link parameter set from the pre-built radio frequency link database based on the electronic signal reconnaissance equipment construction requirement data; Based on the electronic signal reconnaissance equipment construction requirement data, a multi-channel signal processing parameter set is obtained from a pre-built multi-channel signal processing database; By combining the radio frequency link parameter set and the multi-channel signal processing parameter set, a dataset for constructing the reconnaissance equipment to be processed is obtained. The dataset of the reconnaissance equipment to be processed is preprocessed to obtain the preprocessed dataset of the reconnaissance equipment; A calibration model is constructed, and a consistency analysis is performed on the preprocessed reconnaissance equipment dataset using the calibration model. The analysis results are then used as the construction results of the electronic signal reconnaissance equipment.

[0006] Another technical solution of the present invention to solve the above-mentioned technical problems is as follows: An electronic signal reconnaissance equipment construction device, comprising: The import module is used to import the data required for building electronic signal reconnaissance equipment. The first parameter set acquisition module is used to obtain the radio frequency link parameter set from the pre-built radio frequency link database based on the construction requirement data of the electronic signal reconnaissance equipment. The second parameter set acquisition module is used to obtain a multi-channel signal processing parameter set from a pre-built multi-channel signal processing database based on the electronic signal reconnaissance equipment's construction requirement data. The dataset acquisition module is used to combine the radio frequency link parameter set and the multi-channel signal processing parameter set to obtain the dataset of the reconnaissance device to be processed. The preprocessing module is used to preprocess the reconnaissance equipment construction dataset to obtain the preprocessed reconnaissance equipment construction dataset. The module for obtaining construction results is used to construct a calibration model, perform consistency analysis on the preprocessed reconnaissance equipment construction dataset using the calibration model, and use the analysis results as the construction results of the electronic signal reconnaissance equipment.

[0007] Another technical solution of the present invention to solve the above-mentioned technical problems is as follows: an electronic signal reconnaissance equipment construction system, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the electronic signal reconnaissance equipment construction method as described above.

[0008] Based on the above-described method for constructing an electronic signal reconnaissance device, the present invention also provides a computer-readable storage medium.

[0009] Another technical solution of the present invention to solve the above-mentioned technical problems is as follows: a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the electronic signal reconnaissance device construction method as described above.

[0010] The beneficial effects of this invention are as follows: It obtains an RF link parameter set from a pre-built RF link database based on the electronic signal reconnaissance equipment construction requirement data; it obtains a multi-channel signal processing parameter set from a pre-built multi-channel signal processing database based on the same data; it combines the RF link parameter set and the multi-channel signal processing parameter set to obtain a reconnaissance equipment construction dataset to be processed; it preprocesses the dataset to be processed to obtain a preprocessed dataset; it performs consistency analysis on the preprocessed dataset using a calibration model, and uses the analysis results as the construction result of the electronic signal reconnaissance equipment. This solves the problems of large size, heavy weight, and high signal transmission loss under traditional discrete board-level integrated architectures, shortens the PCB design cycle, reduces costs, and simplifies the functional upgrade process. It also solves the problems of long development cycles, poor compatibility, and low electromagnetic interference resistance of multi-channel signal sampling and signal processing functions, ensuring the reliability and stability of the electronic signal reconnaissance equipment. It has significant application value and meets the application requirements of rapid iteration and high reliability for electronic signal reconnaissance equipment. Attached Figure Description

[0011] Figure 1 A flowchart illustrating the method for constructing an electronic signal reconnaissance device according to an embodiment of the present invention; Figure 2 A block diagram of the overall composition of the electronic signal reconnaissance equipment provided in the embodiment of the present invention for the method of constructing electronic signal reconnaissance equipment; Figure 3 A block diagram of an electronic signal reconnaissance equipment construction device provided in an embodiment of the present invention. Detailed Implementation

[0012] The principles and features of the present invention are described below with reference to the accompanying drawings. The examples given are only for explaining the present invention and are not intended to limit the scope of the present invention.

[0013] Figure 1 This is a flowchart illustrating a method for constructing an electronic signal reconnaissance device according to an embodiment of the present invention.

[0014] like Figure 1 As shown, a method for constructing an electronic signal reconnaissance device includes the following steps: S1: Import the electronic signal reconnaissance equipment construction requirement data, and obtain the radio frequency link parameter set from the pre-built radio frequency link database based on the electronic signal reconnaissance equipment construction requirement data; S2: Based on the electronic signal reconnaissance equipment construction requirement data, obtain the multi-channel signal processing parameter set from the pre-built multi-channel signal processing database; S3: Combine the radio frequency link parameter set and the multi-channel signal processing parameter set to obtain the reconnaissance equipment to be processed and construct the dataset; S4: Preprocess the reconnaissance equipment construction dataset to be processed to obtain the preprocessed reconnaissance equipment construction dataset; S5: Construct a calibration model, perform consistency analysis on the preprocessed reconnaissance equipment dataset using the calibration model, and use the analysis results as the construction result of the electronic signal reconnaissance equipment.

[0015] In the above embodiments, the RF link parameter set is obtained from the pre-built RF link database based on the electronic signal reconnaissance equipment construction requirement data. The multi-channel signal processing parameter set is then obtained from the pre-built multi-channel signal processing database based on the same data. The RF link parameter set and the multi-channel signal processing parameter set are combined to obtain the reconnaissance equipment construction dataset to be processed. Preprocessing of this dataset yields a pre-processed reconnaissance equipment construction dataset. A consistency analysis of the pre-processed dataset is performed using a calibration model, and the analysis results are used as the construction result of the electronic signal reconnaissance equipment. This solves the problems of large size, high weight, and high signal transmission loss under traditional discrete board-level integrated architectures. It shortens the PCB design cycle, reduces costs, and simplifies the functional upgrade process. It also solves the problems of long development cycles, poor compatibility, and low electromagnetic interference resistance of multi-channel signal sampling and signal processing functions. This ensures the reliability and stability of the electronic signal reconnaissance equipment, has significant application value, and meets the application requirements of rapid iteration and high reliability for electronic signal reconnaissance equipment.

[0016] Optionally, as an embodiment of the present invention, the electronic signal reconnaissance equipment construction requirement data includes radio frequency component requirement information, filter requirement information, substrate requirement information and wiring requirement information, and the pre-built radio frequency link database includes a radio frequency component data sub-library, a filter data sub-library, a substrate data sub-library and a wiring data sub-library; The process of obtaining the radio frequency link parameter set from the pre-built radio frequency link database based on the requirement data constructed by the electronic signal reconnaissance equipment includes: Based on the required RF component information, multiple RF component parameters are obtained from the RF component database. Multiple filter parameters are obtained from the filter data sub-database based on the filter requirement information; Multiple substrate parameters are obtained from the substrate database based on the substrate requirement information. Based on the wiring requirement information, multiple wiring parameters are obtained from the wiring data sub-database, and a set of RF link parameters is obtained by combining all the RF component parameters, all the filter parameters, all the substrate parameters, and all the wiring parameters.

[0017] It should be understood that the RF front-end module and the microwave frequency conversion channel (i.e., the pre-built RF link database) are designed for high-density heterogeneous integration in SIP to generate a high-density RF link in SIP (i.e., the RF link parameter set).

[0018] Understandably, based on the further refinement of the technical specifications of the RF front-end module and microwave frequency conversion channel, the technical specifications of discrete components in the SIP high-density RF link (i.e., the pre-built RF link database) are determined, and the selection, schematic design and layout design of discrete components are carried out.

[0019] Specifically, for components (i.e., the RF component data library), small-sized packaging is preferred. For example, RF components such as low-noise amplifiers, mixers, and local oscillators are preferably in bare-chip form to replace traditional metal cavity packaging. For filters (i.e., the filter data library), thin-film integration technology is used to replace traditional cavity filters.

[0020] Specifically, a low-temperature co-fired multilayer ceramic substrate (i.e., substrate data sub-library) is adopted, with RF links laid out on the top layer, ground plane and power distribution network designed in the middle layer, and control circuit integrated on the bottom layer; component interconnection is achieved through three-dimensional wiring (i.e. wiring data sub-library), shortening the length of the RF path; and grounding vias are set at key nodes to improve the isolation between channels.

[0021] In the above embodiments, the RF link parameter set is obtained from the pre-built RF link database based on the electronic signal reconnaissance equipment construction requirement data, which shortens the length of the RF path, improves the channel spacing, and solves the problems of large size, heavy weight and high signal transmission loss under the traditional discrete board-level integrated architecture. This achieves shorter PCB design cycle, lower cost and simplified functional upgrade process.

[0022] Optionally, as an embodiment of the present invention, the electronic signal reconnaissance equipment construction requirement data includes analog-to-digital converter requirement information, field-programmable gate array (FPGA) requirement information, central processing unit (CPU) requirement information, heat dissipation requirement information, temperature sensor requirement information, and power management requirement information. The pre-built multi-channel signal processing database includes analog-to-digital converter data sub-libraries, FPGA data sub-libraries, CPU data sub-libraries, heat dissipation data sub-libraries, temperature sensor data sub-libraries, and power management data sub-libraries. The process of obtaining a multi-channel signal processing parameter set from a pre-built multi-channel signal processing database based on the requirement data constructed by the electronic signal reconnaissance equipment includes: Based on the analog-to-digital converter (ADC) requirement information, multiple ADC parameters are obtained from the ADC data sub-database. Based on the field-programmable gate array (FPGA) requirement information, multiple FPGA parameters are obtained from the FPGA data sub-database. Multiple CPU parameters are obtained from the CPU database based on the CPU requirement information. Multiple heat dissipation parameters are obtained from the heat dissipation data sub-database based on the heat dissipation requirement information; Based on the temperature sensor requirement information, multiple temperature sensor parameters are obtained from the temperature sensor data sub-database; Based on the power management requirement information, multiple power management parameters are obtained from the power management data sub-database, and a multi-channel signal processing parameter set is obtained by combining all the analog-to-digital converter parameters, all the field-programmable gate array parameters, all the central processing unit parameters, all the heat dissipation parameters, all the temperature sensor parameters, and all the power management parameters.

[0023] It should be understood that the multi-channel sampling module and the digital signal processing module (i.e., the pre-built multi-channel signal processing database) are designed with high-density heterogeneous integration in SIP to generate a SIP multi-channel sampling processing module (i.e., a multi-channel signal processing parameter set).

[0024] Specifically, the technical specifications of the multi-channel sampling module and the digital signal processing module (i.e., the pre-built multi-channel signal processing database) are further refined to determine the technical specifications of discrete components in the SIP multi-channel sampling processing module, and the selection, schematic design and layout design of discrete components are carried out.

[0025] Specifically, the multi-channel ADC (i.e., analog-to-digital converter data sub-library) uses die stacking and achieves inter-layer interconnection through silicon via technology, reducing the device layout volume; the FPGA (i.e., field-programmable gate array data sub-library) and CPU chip (i.e., central processing unit data sub-library) use reconfigurable dies and adopt a planar heterogeneous integration design, achieving high-speed interconnection through metal wiring made by RDL redistribution layer; the power management module (i.e., power management data sub-library) is integrated in the form of power management integrated circuit bare chips and is laid out on the same substrate as the digital chip, improving power supply efficiency.

[0026] Specifically, a microchannel heat dissipation structure (i.e., heat dissipation data sub-library) is integrated at the bottom of power devices (such as ADC, FPGA, CPU), combined with the analysis of the thermal conductivity and heat dissipation capacity of the substrate thermal conductive layer; at the same time, a temperature sensor (i.e., temperature sensor data sub-library) is integrated at the bottom layer of the substrate to monitor the chip junction temperature in real time and meet the requirements for stable operation in high-temperature environments.

[0027] In the above embodiments, a multi-channel signal processing parameter set is obtained from a pre-built multi-channel signal processing database based on the electronic signal reconnaissance equipment construction requirement data. This improves power supply efficiency, enables real-time monitoring of chip junction temperature, and ensures stable operation in high-temperature environments. It also solves the problems of large size, heavy weight, and high signal transmission loss under traditional discrete board-level integrated architecture, thereby shortening the PCB design cycle, reducing costs, and simplifying the functional upgrade process.

[0028] Optionally, as an embodiment of the present invention, the process of preprocessing the reconnaissance equipment construction dataset to obtain the preprocessed reconnaissance equipment construction dataset includes: Multiple filtered reconnaissance equipment construction data are selected from the reconnaissance equipment construction dataset to be processed according to the filtering criteria. The filtering criteria are that the frequency step of the reconnaissance equipment construction data to be processed in the reconnaissance equipment construction dataset is greater than or equal to a preset frequency threshold, and the local oscillator step of the reconnaissance equipment construction data to be processed in the reconnaissance equipment construction dataset is greater than or equal to a preset local oscillator threshold. The data for constructing each of the filtered reconnaissance devices are normalized, and the results of the normalization are combined to obtain the preprocessed reconnaissance device construction dataset.

[0029] Preferably, the preset frequency threshold can be 100MHz, and the preset local oscillator threshold can be 500MHz.

[0030] Specifically, the measured amplitude and phase data and ideal amplitude and phase consistency data collected at intervals of a certain frequency step (≥100MHz) and local oscillator step (≥500MHz) are preprocessed to remove outliers and data with severe noise interference; the amplitude and phase consistency data (i.e., the data constructed by the reconnaissance equipment after screening) are normalized to map the amplitude values ​​to the interval [0,1] and the phase values ​​to the interval [0,2π) to obtain the dataset used for model training (i.e., the dataset constructed by the reconnaissance equipment after preprocessing).

[0031] In the above embodiments, the reconnaissance equipment construction dataset to be processed is preprocessed to obtain the preprocessed reconnaissance equipment construction dataset, which solves the problems of large size, heavy weight and large signal transmission loss under the traditional discrete board-level integrated architecture, and realizes the shortening of PCB design cycle, cost reduction and functional upgrade process simplification.

[0032] Optionally, as an embodiment of the present invention, the correction model includes a deep neural network, a generative adversarial network, and a fully connected network. The process of performing consistency analysis on the preprocessed reconnaissance equipment dataset using the correction model and using the analysis result as the construction result of the electronic signal reconnaissance equipment includes: The deep neural network is used to extract features from the preprocessed reconnaissance equipment dataset to obtain multiple reconnaissance equipment construction feature vectors. The feature vectors of each of the reconnaissance devices are constructed and optimized using the generative adversarial network to obtain the reconnaissance device simulation error feature vectors corresponding to the feature vectors of each of the reconnaissance devices. The simulation error feature vectors of each of the reconnaissance devices are mapped through the fully connected network to obtain the original compensation coefficients corresponding to the construction feature vectors of each of the reconnaissance devices. Each of the original compensation coefficients is denormalized to obtain the denormalized compensation coefficients corresponding to the feature vectors constructed by each of the reconnaissance devices. Each of the inverse normalized compensation coefficients is smoothed to obtain the target compensation coefficients corresponding to the feature vectors constructed by each of the reconnaissance devices, and all the target compensation coefficients are used as the construction result of the electronic signal reconnaissance device.

[0033] Specifically, a deep neural network and generative adversarial network were selected as the amplitude-phase consistency correction model. A multi-dimensional error feature extraction model was established to capture amplitude-phase distortion caused by process deviations and temperature changes in real time. The amplitude compensation coefficient and phase compensation value of each frequency point and different local oscillator points were output through a fully connected network. The performance of the trained model was evaluated using a test set to ensure that the prediction accuracy of the model meets the requirements.

[0034] Understandably, through feature extraction, attention focusing, and nonlinear mapping, the corrected amplitude and phase data (i.e., the original compensation coefficients) output by the model are denormalized, and the correction results (i.e., the denormalized compensation coefficients) are smoothed to remove possible local fluctuations, thereby obtaining the amplitude and phase consistency correction results (i.e., the target compensation coefficients) for the entire operating frequency range and the full coverage local oscillator range, thus achieving accurate correction of complex nonlinear amplitude and phase errors of electronic signal reconnaissance equipment.

[0035] In the above embodiments, a consistency analysis is performed on the preprocessed reconnaissance equipment dataset using a calibration model, and the analysis results are used as the construction results of the electronic signal reconnaissance equipment. This removes possible local fluctuations and achieves accurate correction of the complex nonlinear amplitude and phase errors of the electronic signal reconnaissance equipment.

[0036] Optionally, as another embodiment of the present invention, the present invention utilizes an integrated design method based on system-in-package (SIP) technology to integrate functionally related modules into the same package. Through short-distance interconnection, heterogeneous integration, and package-level optimization, the overall size and weight of the reconnaissance equipment are significantly reduced. By achieving high-density heterogeneous integration of the RF front-end and microwave frequency conversion channel, the problems of large size, high weight, and high signal transmission loss under the traditional discrete board-level integrated architecture are solved. By achieving high-density heterogeneous integration of multi-channel sampling modules and digital signal processing modules, the PCB design cycle is shortened, costs are reduced, and the functional upgrade process is simplified, solving problems such as long development cycles, poor compatibility, and low electromagnetic interference resistance of multi-channel signal sampling and signal processing functions. At the same time, the system's anti-interference capability and maintenance convenience are improved, meeting the application requirements of rapid iteration and high reliability of electronic signal reconnaissance equipment. By utilizing a broadband multi-channel amplitude-phase consistency dynamic correction method based on deep neural networks and generative adversarial networks, a multi-dimensional error feature extraction model is established to capture amplitude-phase consistency errors caused by manufacturing process deviations and temperature changes in real time. Combining signal frequency characteristics and local oscillator characteristics, the method achieves complete reception of large instantaneous broadband signals within the working range of the reconnaissance equipment and broadband nonlinear amplitude-phase error correction and compensation, improving direction finding accuracy and signal sorting and identification accuracy. This ensures the reliability and stability of highly integrated, miniaturized, multi-scenario electronic signal reconnaissance equipment and has significant application value.

[0037] Optionally, as another embodiment of the present invention, the present invention decomposes the key core functional modules of the equipment into technical indicators according to the technical requirements of electronic signal reconnaissance equipment, including receiving antenna array, radio frequency front-end module, microwave frequency conversion channel, multi-channel sampling module and digital signal processing module, etc.

[0038] Alternatively, as another embodiment of the present invention, based on the decomposition technical indicators of key core functional modules and considering the generalization and standardization requirements of each functional module, the present invention utilizes SIP technology to integrate functionally related modules into the same package, and through short-distance interconnection, heterogeneous integration and package-level optimization, achieves a significant reduction in the volume and weight of each functional module.

[0039] Optionally, as another embodiment of the present invention, the present invention manufactures and tests a prototype of the high-density radio frequency link and the multi-channel sampling processing module according to the design parameters of the SIP high-density radio frequency link and the SIP multi-channel sampling processing module after final iterative optimization.

[0040] Optionally, as another embodiment of the present invention, after the electronic signal reconnaissance equipment amplitude and phase consistency correction processing is completed, the present invention performs 8-channel array beamforming direction finding in the FPGA within the SIP multi-channel sampling processing module, and performs signal sorting and recognition processing in the CPU within the SIP multi-channel sampling processing module, thereby realizing high-precision direction finding and high-accuracy signal sorting and recognition functions for target signals.

[0041] Alternatively, as another embodiment of the present invention, such as Figure 2 As shown, this invention mainly includes key core functional modules such as a receiving antenna array, a radio frequency front-end module, a microwave frequency conversion channel, a multi-channel sampling module, and a digital signal processing module. The receiving antenna array completes the reconnaissance and reception of electronic signals in the corresponding frequency band within the instantaneous coverage area. The radio frequency front-end module, through a single-pole double-throw switch, can amplify and filter the electronic signals received by the receiving antenna before sending them to the corresponding microwave frequency conversion channel for down-conversion processing; it can also use a built-in correction source module to complete the correction of equipment amplitude and phase consistency differences. The microwave frequency conversion channel, through reasonable setting of variable local oscillator combination control parameters, down-converts and outputs multiple intermediate frequency signals to the multi-channel sampling module. The multi-channel sampling module uses multiple ADC chips to perform analog-to-digital conversion sampling of the intermediate frequency signals, forming multiple intermediate frequency data streams that are sent to the digital signal processing module for quantization processing. The digital signal processing module adopts multi-channel digital reception and parallel data processing technology to complete intermediate frequency signal quantization processing, signal parameter measurement, and sorting and identification.

[0042] Figure 3 This is a module block diagram of an electronic signal reconnaissance equipment construction device provided in an embodiment of the present invention.

[0043] Alternatively, as another embodiment of the present invention, such as Figure 3 As shown, an electronic signal reconnaissance equipment construction device includes: The import module is used to import the data required for building electronic signal reconnaissance equipment. The first parameter set acquisition module is used to obtain the radio frequency link parameter set from the pre-built radio frequency link database based on the construction requirement data of the electronic signal reconnaissance equipment. The second parameter set acquisition module is used to obtain a multi-channel signal processing parameter set from a pre-built multi-channel signal processing database based on the electronic signal reconnaissance equipment's construction requirement data. The dataset acquisition module is used to combine the radio frequency link parameter set and the multi-channel signal processing parameter set to obtain the dataset of the reconnaissance device to be processed. The preprocessing module is used to preprocess the reconnaissance equipment construction dataset to obtain the preprocessed reconnaissance equipment construction dataset. The module for obtaining construction results is used to construct a calibration model, perform consistency analysis on the preprocessed reconnaissance equipment construction dataset using the calibration model, and use the analysis results as the construction results of the electronic signal reconnaissance equipment.

[0044] Optionally, as an embodiment of the present invention, the electronic signal reconnaissance equipment construction requirement data includes radio frequency component requirement information, filter requirement information, substrate requirement information and wiring requirement information, and the pre-built radio frequency link database includes a radio frequency component data sub-library, a filter data sub-library, a substrate data sub-library and a wiring data sub-library; The first parameter set acquisition module is specifically used for: Based on the required RF component information, multiple RF component parameters are obtained from the RF component database. Multiple filter parameters are obtained from the filter data sub-database based on the filter requirement information; Multiple substrate parameters are obtained from the substrate database based on the substrate requirement information. Based on the wiring requirement information, multiple wiring parameters are obtained from the wiring data sub-database, and a set of RF link parameters is obtained by combining all the RF component parameters, all the filter parameters, all the substrate parameters, and all the wiring parameters.

[0045] Optionally, as an embodiment of the present invention, the electronic signal reconnaissance equipment construction requirement data includes analog-to-digital converter requirement information, field-programmable gate array (FPGA) requirement information, central processing unit (CPU) requirement information, heat dissipation requirement information, temperature sensor requirement information, and power management requirement information. The pre-built multi-channel signal processing database includes analog-to-digital converter data sub-libraries, FPGA data sub-libraries, CPU data sub-libraries, heat dissipation data sub-libraries, temperature sensor data sub-libraries, and power management data sub-libraries. The second parameter set acquisition module is specifically used for: Based on the analog-to-digital converter (ADC) requirement information, multiple ADC parameters are obtained from the ADC data sub-database. Based on the field-programmable gate array (FPGA) requirement information, multiple FPGA parameters are obtained from the FPGA data sub-database. Multiple CPU parameters are obtained from the CPU database based on the CPU requirement information. Multiple heat dissipation parameters are obtained from the heat dissipation data sub-database based on the heat dissipation requirement information; Based on the temperature sensor requirement information, multiple temperature sensor parameters are obtained from the temperature sensor data sub-database; Based on the power management requirement information, multiple power management parameters are obtained from the power management data sub-database, and a multi-channel signal processing parameter set is obtained by combining all the analog-to-digital converter parameters, all the field-programmable gate array parameters, all the central processing unit parameters, all the heat dissipation parameters, all the temperature sensor parameters, and all the power management parameters.

[0046] Optionally, another embodiment of the present invention provides an electronic signal reconnaissance device construction system, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the electronic signal reconnaissance device construction method as described above. This system can be a computer or similar system.

[0047] Optionally, another embodiment of the present invention provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the electronic signal reconnaissance device construction method as described above.

[0048] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0049] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the above-described apparatus and unit can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0050] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed.

[0051] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of the embodiments of the present invention, depending on actual needs.

[0052] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0053] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0054] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for constructing an electronic signal reconnaissance device, characterized in that, Includes the following steps: Import the electronic signal reconnaissance equipment construction requirement data, and obtain the radio frequency link parameter set from the pre-built radio frequency link database based on the electronic signal reconnaissance equipment construction requirement data; Based on the electronic signal reconnaissance equipment construction requirement data, a multi-channel signal processing parameter set is obtained from a pre-built multi-channel signal processing database; By combining the radio frequency link parameter set and the multi-channel signal processing parameter set, a dataset for constructing the reconnaissance equipment to be processed is obtained. The dataset of the reconnaissance equipment to be processed is preprocessed to obtain the preprocessed dataset of the reconnaissance equipment; A calibration model is constructed, and a consistency analysis is performed on the preprocessed reconnaissance equipment dataset using the calibration model. The analysis results are then used as the construction results of the electronic signal reconnaissance equipment.

2. The method for constructing an electronic signal reconnaissance device according to claim 1, characterized in that, The electronic signal reconnaissance equipment construction requirement data includes radio frequency component requirement information, filter requirement information, substrate requirement information, and wiring requirement information. The pre-built radio frequency link database includes a radio frequency component data sub-library, a filter data sub-library, a substrate data sub-library, and a wiring data sub-library. The process of obtaining the radio frequency link parameter set from the pre-built radio frequency link database based on the requirement data constructed by the electronic signal reconnaissance equipment includes: Based on the required RF component information, multiple RF component parameters are obtained from the RF component database. Multiple filter parameters are obtained from the filter data sub-database based on the filter requirement information; Multiple substrate parameters are obtained from the substrate database based on the substrate requirement information. Based on the wiring requirement information, multiple wiring parameters are obtained from the wiring data sub-database, and a set of RF link parameters is obtained by combining all the RF component parameters, all the filter parameters, all the substrate parameters, and all the wiring parameters.

3. The method for constructing an electronic signal reconnaissance device according to claim 1, characterized in that, The electronic signal reconnaissance equipment construction requirement data includes analog-to-digital converter requirement information, field-programmable gate array (FPGA) requirement information, central processing unit (CPU) requirement information, heat dissipation requirement information, temperature sensor requirement information, and power management requirement information. The pre-built multi-channel signal processing database includes analog-to-digital converter data sub-libraries, field-programmable gate array (FPGA) data sub-libraries, CPU data sub-libraries, heat dissipation data sub-libraries, temperature sensor data sub-libraries, and power management data sub-libraries. The process of obtaining a multi-channel signal processing parameter set from a pre-built multi-channel signal processing database based on the requirement data constructed by the electronic signal reconnaissance equipment includes: Based on the analog-to-digital converter (ADC) requirement information, multiple ADC parameters are obtained from the ADC data sub-database. Based on the field-programmable gate array (FPGA) requirement information, multiple FPGA parameters are obtained from the FPGA data sub-database. Multiple CPU parameters are obtained from the CPU database based on the CPU requirement information. Multiple heat dissipation parameters are obtained from the heat dissipation data sub-database based on the heat dissipation requirement information; Based on the temperature sensor requirement information, multiple temperature sensor parameters are obtained from the temperature sensor data sub-database; Based on the power management requirement information, multiple power management parameters are obtained from the power management data sub-database, and a multi-channel signal processing parameter set is obtained by combining all the analog-to-digital converter parameters, all the field-programmable gate array parameters, all the central processing unit parameters, all the heat dissipation parameters, all the temperature sensor parameters, and all the power management parameters.

4. The method for constructing an electronic signal reconnaissance device according to claim 1, characterized in that, The process of preprocessing the reconnaissance equipment construction dataset to obtain the preprocessed reconnaissance equipment construction dataset includes: Multiple filtered reconnaissance equipment construction data are selected from the reconnaissance equipment construction dataset to be processed according to the filtering criteria. The filtering criteria are that the frequency step of the reconnaissance equipment construction data to be processed in the reconnaissance equipment construction dataset is greater than or equal to a preset frequency threshold, and the local oscillator step of the reconnaissance equipment construction data to be processed in the reconnaissance equipment construction dataset is greater than or equal to a preset local oscillator threshold. The data for constructing each of the filtered reconnaissance devices are normalized, and the results of the normalization are combined to obtain the preprocessed reconnaissance device construction dataset.

5. The method for constructing an electronic signal reconnaissance device according to claim 1, characterized in that, The correction model includes deep neural networks, generative adversarial networks, and fully connected networks. The process of performing consistency analysis on the preprocessed reconnaissance equipment dataset using the correction model and using the analysis results as the construction result of the electronic signal reconnaissance equipment includes: The deep neural network is used to extract features from the preprocessed reconnaissance equipment dataset to obtain multiple reconnaissance equipment construction feature vectors. The feature vectors of each of the reconnaissance devices are constructed and optimized using the generative adversarial network to obtain the reconnaissance device simulation error feature vectors corresponding to the feature vectors of each of the reconnaissance devices. The simulation error feature vectors of each of the reconnaissance devices are mapped through the fully connected network to obtain the original compensation coefficients corresponding to the construction feature vectors of each of the reconnaissance devices. Each of the original compensation coefficients is denormalized to obtain the denormalized compensation coefficients corresponding to the feature vectors constructed by each of the reconnaissance devices. Each of the inverse normalized compensation coefficients is smoothed to obtain the target compensation coefficients corresponding to the feature vectors constructed by each of the reconnaissance devices, and all the target compensation coefficients are used as the construction result of the electronic signal reconnaissance device.

6. An apparatus for constructing an electronic signal reconnaissance device, characterized in that, include: The import module is used to import the data required for building electronic signal reconnaissance equipment. The first parameter set acquisition module is used to obtain the radio frequency link parameter set from the pre-built radio frequency link database based on the construction requirement data of the electronic signal reconnaissance equipment. The second parameter set acquisition module is used to obtain a multi-channel signal processing parameter set from a pre-built multi-channel signal processing database based on the electronic signal reconnaissance equipment's construction requirement data. The dataset acquisition module is used to combine the radio frequency link parameter set and the multi-channel signal processing parameter set to obtain the dataset of the reconnaissance device to be processed. The preprocessing module is used to preprocess the reconnaissance equipment construction dataset to obtain the preprocessed reconnaissance equipment construction dataset. The module for obtaining construction results is used to construct a calibration model, perform consistency analysis on the preprocessed reconnaissance equipment construction dataset using the calibration model, and use the analysis results as the construction results of the electronic signal reconnaissance equipment.

7. The electronic signal reconnaissance equipment construction apparatus according to claim 6, characterized in that, The electronic signal reconnaissance equipment construction requirement data includes radio frequency component requirement information, filter requirement information, substrate requirement information, and wiring requirement information. The pre-built radio frequency link database includes a radio frequency component data sub-library, a filter data sub-library, a substrate data sub-library, and a wiring data sub-library. The first parameter set acquisition module is specifically used for: Based on the required RF component information, multiple RF component parameters are obtained from the RF component database. Multiple filter parameters are obtained from the filter data sub-database based on the filter requirement information; Multiple substrate parameters are obtained from the substrate database based on the substrate requirement information. Based on the wiring requirement information, multiple wiring parameters are obtained from the wiring data sub-database, and a set of RF link parameters is obtained by combining all the RF component parameters, all the filter parameters, all the substrate parameters, and all the wiring parameters.

8. The electronic signal reconnaissance equipment construction apparatus according to claim 6, characterized in that, The electronic signal reconnaissance equipment construction requirement data includes analog-to-digital converter requirement information, field-programmable gate array (FPGA) requirement information, central processing unit (CPU) requirement information, heat dissipation requirement information, temperature sensor requirement information, and power management requirement information. The pre-built multi-channel signal processing database includes analog-to-digital converter data sub-libraries, field-programmable gate array (FPGA) data sub-libraries, CPU data sub-libraries, heat dissipation data sub-libraries, temperature sensor data sub-libraries, and power management data sub-libraries. The second parameter set acquisition module is specifically used for: Based on the analog-to-digital converter (ADC) requirement information, multiple ADC parameters are obtained from the ADC data sub-database. Based on the field-programmable gate array (FPGA) requirement information, multiple FPGA parameters are obtained from the FPGA data sub-database. Multiple CPU parameters are obtained from the CPU database based on the CPU requirement information. Multiple heat dissipation parameters are obtained from the heat dissipation data sub-database based on the heat dissipation requirement information; Based on the temperature sensor requirement information, multiple temperature sensor parameters are obtained from the temperature sensor data sub-database; Based on the power management requirement information, multiple power management parameters are obtained from the power management data sub-database, and a multi-channel signal processing parameter set is obtained by combining all the analog-to-digital converter parameters, all the field-programmable gate array parameters, all the central processing unit parameters, all the heat dissipation parameters, all the temperature sensor parameters, and all the power management parameters.

9. An apparatus for constructing an electronic signal reconnaissance device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method for constructing an electronic signal reconnaissance device as described in any one of claims 1 to 5.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the method for constructing an electronic signal reconnaissance device as described in any one of claims 1 to 5.

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