Radar equipment electromagnetic environment equivalent simulation method and device, terminal and medium
By acquiring parameter information of radar equipment, calculating equivalent power density and simulated range, and using neural network models to predict equivalent simulated range, target simulation parameters are generated. This solves the problem of radar equipment's difficulty in verifying its adaptability to the battlefield electromagnetic environment under laboratory conditions, and achieves efficient and accurate equipment evaluation.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- 成都玖锦科技有限公司
- Filing Date
- 2026-03-04
- Publication Date
- 2026-05-05
AI Technical Summary
Existing technologies are insufficient to accurately verify the battlefield electromagnetic environment adaptability of radar equipment under laboratory conditions. Field tests have limited sample size, high cost, long cycle, and low evaluation accuracy, failing to meet the complex electromagnetic environment assessment requirements of modern equipment.
This paper provides a method for equivalent simulation of the electromagnetic environment of radar equipment. By acquiring parameter information of the target equipment and hardware equipment, calculating the equivalent power density and simulated distance, using a neural network model to predict the equivalent simulated distance, and combining the hardware parameters to generate target simulation parameters, the equivalent simulation of radar equipment is realized.
Based on existing hardware, it efficiently reproduces the real electromagnetic environment, supports comprehensive evaluation of equipment performance, improves the accuracy and efficiency of testing, and reduces testing costs.
Smart Images
Figure CN121978641A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of data processing technology, and in particular to a method, device, terminal and medium for equivalent simulation of the electromagnetic environment of radar equipment. Background Technology
[0002] With the development of electronic technology, the battlefield is filled with various radar, communication, and electronic countermeasures equipment, resulting in highly congested spectrum resources and intertwined and superimposed electromagnetic signals. This includes signal interference from friendly equipment as well as targeted electromagnetic suppression from the enemy, creating a complex electromagnetic environment characterized by multiple frequency bands, high density, and dynamic changes. Radar equipment faces severe challenges in its detection, identification, and anti-jamming capabilities. As a core sensing device in the combat system, the stability and reliability of radar in real electromagnetic environments directly affect combat decision-making and effectiveness. In traditional equipment research and development and acceptance, simple laboratory performance testing is insufficient to recreate battlefield electromagnetic interference scenarios and cannot accurately verify the equipment's combat adaptability.
[0003] Because current battlefield electromagnetic environment test data for modern radar equipment mainly relies on field exercises, it suffers from problems such as limited test samples, high test costs, long test cycles, and non-repeatable tests. In particular, the boundaries of field tests are unclear, resulting in low accuracy of assessments. For example, it is difficult to determine the complexity of the current electromagnetic environment, and there are no quantitative characterization and assessment methods, making it difficult to accurately determine whether the equipment's problem is related to anti-jamming capability or a normal probability event. Simply relying on field exercises can no longer meet the assessment requirements of modern equipment's adaptability to complex battlefield electromagnetic environments under the new circumstances. It is necessary to construct equivalent radar simulation systems for the electromagnetic environment of radar equipment in indoor fields or test ranges to achieve an equivalent and realistic reconstruction, and to reproduce the real electromagnetic environment of radar equipment as efficiently as possible. Summary of the Invention
[0004] The main objective of this application is to provide a method, device, terminal, and medium for equivalent simulation of the electromagnetic environment of radar equipment, aiming to achieve equivalent simulation of radar equipment in the electromagnetic environment based on existing hardware.
[0005] To achieve the above objectives, this application provides an equivalent simulation method for the electromagnetic environment of radar equipment, applied to a radar simulation system. The method includes: Acquire parameter information of the target equipment and the hardware equipment in the radar simulation system; Based on the parameter information of the target equipment, the equivalent power density is calculated; Based on the simulated site information corresponding to the radar simulation system and the parameter information of the hardware equipment, the equivalent simulated distance is determined. Based on the parameter information of the hardware equipment, the equivalent power density, and the equivalent simulation distance, target simulation parameters are obtained so that the hardware equipment performs equivalent simulation of the target equipment according to the target simulation parameters.
[0006] Specifically, the parameter information of the target equipment includes the transmission power of the target equipment, the antenna gain of the target equipment, and the effective range of the target equipment. The calculation of the equivalent power density based on the parameter information of the target equipment includes: The equivalent power density is calculated using the following formula:
[0007] in, This represents the equivalent power density. This indicates the transmission power of the target equipment. This indicates the effective range of the target equipment. This indicates the antenna gain of the target equipment.
[0008] Specifically, determining the equivalent simulated distance based on the simulated site information corresponding to the radar simulation system and the parameter information of the hardware equipment includes: Based on the simulated site information, the equivalent simulated distance prediction value is obtained through a preset equivalent simulated distance prediction model; Based on the parameter information of the hardware equipment, determine the reasonable constraint range corresponding to the equivalent simulation distance; The equivalent simulation distance is determined based on the predicted value of the equivalent simulation distance and the reasonable constraint range corresponding to the equivalent simulation distance.
[0009] Specifically, the preset equivalent simulation distance prediction model includes a first input layer, a first hidden layer, and a first output layer. The simulated site information includes site structure parameters, site electromagnetic propagation parameters, site environmental interference parameters, and site available space parameters. The first input layer includes 4 nodes, the first hidden layer includes a first sub-hidden layer and a second hidden layer. The first hidden layer includes 64 nodes, the second hidden layer includes 32 nodes, and the first output layer includes 1 node. The step of obtaining the equivalent simulated distance prediction value based on the simulated site information and through a preset equivalent simulated distance prediction model includes: The site structure parameters, the site electromagnetic propagation parameters, the site environmental interference parameters, and the site available space parameters are input into the first input layer to obtain the first input vector; The first input vector is input into the first sub-hidden layer to obtain the first intermediate vector; The first intermediate vector is input into the second sub-hidden layer to obtain the first feature vector; The first feature vector is input into the first output layer to obtain the equivalent simulated distance prediction value.
[0010] Specifically, determining the equivalent simulation distance based on the predicted equivalent simulation distance value and the reasonable constraint range corresponding to the equivalent simulation distance includes: If the predicted equivalent simulation distance is not within the reasonable constraint range corresponding to the equivalent simulation distance, the reasonable constraint range corresponding to the equivalent simulation distance is adjusted through a preset constraint adjustment mechanism until the predicted equivalent simulation distance is within the reasonable constraint range corresponding to the adjusted equivalent simulation distance, so as to determine the equivalent simulation distance. If the predicted equivalent simulation distance is within the reasonable constraint range corresponding to the equivalent simulation distance, then the predicted equivalent simulation distance is used as the initial value, and the goal is to minimize the difference between the predicted equivalent simulation distance and the predicted equivalent simulation distance. The equivalent simulation distance is then calculated using a preset constraint optimization algorithm.
[0011] Specifically, the parameter information of the hardware equipment includes the power amplifier output power range of the hardware equipment and the antenna gain of the hardware equipment. The target simulation parameters are obtained based on the parameter information of the hardware equipment, the equivalent power density, and the equivalent simulation distance, including: Based on the power amplifier output power range of the hardware equipment, the antenna gain of the hardware equipment, the equivalent power density, and the equivalent simulation distance, the target simulation parameters are obtained by generating a model using preset target simulation parameters. The target simulation parameters include the target power amplifier transmit power and the target antenna gain.
[0012] Specifically, the preset target simulation parameter generation model includes a second input layer, a second hidden layer, and a second output layer. The second hidden layer includes a third sub-hidden layer, a fourth sub-hidden layer, and a fifth sub-hidden layer. The second output layer includes two nodes. The step of generating the target simulation parameters by using a preset target simulation parameter generation model based on the power amplifier output power range of the hardware equipment, the antenna gain of the hardware equipment, the equivalent power density, and the equivalent simulation distance includes: The power amplifier output power range of the hardware equipment, the antenna gain of the hardware equipment, the equivalent power density, and the equivalent analog distance are input to the second input layer to obtain the second input vector; The second input vector is input into the third sub-hidden layer to obtain the second intermediate vector; The second intermediate vector is input into the fourth sub-hidden layer to obtain the third intermediate vector; The third intermediate vector is input into the fifth sub-hidden layer to obtain the second feature vector; The second feature vector is input into the second output layer to obtain the target power amplifier transmit power and the target antenna gain.
[0013] To achieve the above objectives, this application also provides an equivalent simulation device for the electromagnetic environment of radar equipment, applied to a radar simulation system, the device comprising: The first unit is used to acquire parameter information of the target equipment and the hardware equipment in the radar simulation system. The second unit is used to calculate the equivalent power density based on the parameter information of the target equipment. The third unit is used to determine the equivalent simulated distance based on the simulated site information corresponding to the radar simulation system and the parameter information of the hardware equipment. The fourth unit is used to obtain target simulation parameters based on the parameter information of the hardware equipment, the equivalent power density, and the equivalent simulation distance, so that the hardware equipment performs equivalent simulation of the target equipment according to the target simulation parameters.
[0014] To achieve the above objectives, this application also provides a terminal, including a processor and a memory, the memory storing multiple instructions; the processor loads instructions from the memory to execute the steps in any of the methods provided in this application.
[0015] To achieve the above objectives, this application also provides a medium storing a plurality of instructions adapted for loading by a processor to execute the steps in any of the methods provided in this application.
[0016] This application provides a method, apparatus, terminal, and medium for equivalent electromagnetic environment simulation of radar equipment. It first acquires parameter information of the target equipment and the hardware equipment in the radar simulation system; calculates the equivalent power density based on the target equipment's parameter information; determines the equivalent simulation distance based on the simulation site information corresponding to the radar simulation system and the hardware equipment's parameter information; and obtains target simulation parameters based on the hardware equipment's parameter information, the equivalent power density, and the equivalent simulation distance, enabling the hardware equipment to perform equivalent simulation of the target equipment according to the target simulation parameters, thereby achieving equivalent simulation of radar equipment in an electromagnetic environment based on existing hardware. Attached Figure Description
[0017] Figure 1 A flowchart illustrating the method provided in the embodiments of this application; Figure 2 A schematic diagram of the preset equivalent simulation distance prediction model provided in the embodiments of this application; Figure 3 A schematic diagram of the preset target simulation parameter generation model provided in the embodiments of this application; Figure 4 A flowchart for one-click generation of equivalent simulation parameters provided in the embodiments of this application; Figure 5 A schematic diagram of the software interface for automatically generating equivalent simulation parameters provided in this application embodiment; Figure 6 A flowchart for the random generation of equivalent simulation parameters provided in the embodiments of this application.
[0018] Figure 7 This is a schematic diagram of the device provided in the embodiments of this application; Figure 8 This is a schematic diagram of the terminal structure provided in an embodiment of this application. Detailed Implementation
[0019] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.
[0020] Because current battlefield electromagnetic environment test data for modern radar equipment mainly relies on field exercises, it suffers from problems such as limited test samples, high test costs, long test cycles, and non-repeatable tests. In particular, the boundaries of field tests are unclear, resulting in low accuracy of assessments. For example, it is difficult to determine the complexity of the current electromagnetic environment, and there are no quantitative characterization and assessment methods, making it difficult to accurately determine whether the equipment's problem is related to anti-jamming capability or a normal probability event. Simply relying on field exercises can no longer meet the assessment requirements of modern equipment's adaptability to complex battlefield electromagnetic environments under the new circumstances. It is necessary to construct equivalent radar simulation systems for the electromagnetic environment of radar equipment in indoor fields or test ranges to achieve an equivalent and realistic reconstruction, and to reproduce the real electromagnetic environment of radar equipment as efficiently as possible.
[0021] Therefore, embodiments of this application provide a method, apparatus, terminal, and medium for equivalent simulation of the electromagnetic environment of radar equipment to solve practical technical problems.
[0022] In some embodiments, the device may be integrated into an electronic device, such as a terminal or server.
[0023] In some embodiments, the server may also be implemented as a terminal.
[0024] The server can be a standalone physical server, a server cluster or distributed system consisting of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN (Content Delivery Network), and big data and artificial intelligence platforms.
[0025] The terminal can be a smartphone, tablet, laptop, desktop computer, smart speaker, smartwatch, etc., but is not limited to these. The terminal and the server can be connected directly or indirectly through wired or wireless communication, which is not limited herein.
[0026] The following sections provide detailed descriptions of each example. It should be noted that the sequence numbers of the following embodiments are not intended to limit the preferred order of the embodiments.
[0027] like Figure 1 An equivalent simulation method for the electromagnetic environment of radar equipment, applied to a radar simulation system, can be described in the following steps: S110: Acquire parameter information of the target equipment and the hardware equipment in the radar simulation system.
[0028] In some embodiments, parameter information of the target equipment is entered through host computer software to ensure data accuracy and completeness, including: The transmit power of the target equipment (unit: kW), for example, the transmit power of the US military's AN / TPQ-36 artillery frame correction and positioning radar is 23kW; Antenna gain of the target equipment (unit: dBi), for example, the antenna gain of the radar mentioned above is 30 dBi; The effective range of the target equipment (unit: m), for example, the effective range of the radar mentioned above is 18000m; It may also include the frequency range of the target equipment (e.g., 8GHz~12GHz) to provide a reference for subsequent simulation scenario adaptation.
[0029] In some embodiments, parameter information of existing hardware equipment in the radar simulation system is entered to define the hardware operating boundaries, specifically including: The power output power range of the hardware equipment (unit: W), that is, the minimum output power and the maximum output power of the power amplifier; The antenna gain of the hardware equipment (unit: dBi). If the antenna gain is adjustable, the adjustable range should be entered synchronously. If it is a fixed value, the value should be entered directly (e.g., 20dBi).
[0030] S120. Based on the parameter information of the target equipment, the equivalent power density is calculated.
[0031] In some embodiments, the parameter information of the target equipment includes the transmit power of the target equipment, the antenna gain of the target equipment, and the effective range of the target equipment.
[0032] Specifically, the calculation of the equivalent power density based on the parameter information of the target equipment includes the following specific implementation process: The equivalent power density is calculated using the following formula:
[0033] in, This represents the equivalent power density. This indicates the transmission power of the target equipment. This indicates the effective range of the target equipment. This indicates the antenna gain of the target equipment. This represents the spherical propagation area of the signal emitted by the target equipment.
[0034] Specifically, the host computer software automatically performs formula calculations, generates and displays the specific value of the equivalent power density S, for example, the AN / TPQ-53 radar ( =60000W =30dBi The calculated equivalent power density of (20000m) is approximately 0.000358 W / m². 2 .
[0035] S130. Based on the simulated site information corresponding to the radar simulation system and the parameter information of the hardware equipment, determine the equivalent simulated distance.
[0036] In some embodiments, determining the equivalent simulation distance based on the simulated site information corresponding to the radar simulation system and the parameter information of the hardware equipment includes the following steps S131 to S133: S131. Based on the simulated site information, the equivalent simulated distance prediction value is obtained through a preset equivalent simulated distance prediction model.
[0037] In some embodiments, such as Figure 2 As shown, the preset equivalent simulation distance prediction model includes a first input layer, a first hidden layer, and a first output layer. The simulated site information includes site structure parameters, site electromagnetic propagation parameters, site environmental interference parameters, and site available space parameters. The first input layer includes 4 nodes, the first hidden layer includes a first sub-hidden layer and a second hidden layer, the first hidden layer includes 64 nodes, the second hidden layer includes 32 nodes, and the first output layer includes 1 node.
[0038] Specifically, the preset equivalent simulated distance prediction model is a customized neural network model, specifically designed for predicting and adapting equivalent simulated distances based on site features, with the following structure: The first input layer contains four nodes, each corresponding to one of the four core parameters of the simulated site. It does not involve complex calculations and only handles data format adaptation and import. First hidden layer: It contains a first sub-hidden layer (64 nodes) and a second sub-hidden layer (32 nodes), and uses the ReLU activation function. Its core function is to extract high-order correlation information of site features. First output layer: Contains 1 node, uses a linear activation function, and outputs equivalent simulated distance prediction value (unit: m).
[0039] Specifically, the step of obtaining the equivalent simulated distance prediction value based on the simulated site information and through a preset equivalent simulated distance prediction model includes the following steps S1311 to S1314: S1311. Input the site structure parameters, the site electromagnetic propagation parameters, the site environmental interference parameters, and the site available space parameters into the first input layer to obtain the first input vector.
[0040] In some embodiments, the four types of parameters of the simulated site (site structure parameters, site electromagnetic propagation parameters, site environmental interference parameters, and site available space parameters) are quantized and then input into the first input layer to form a first input vector Vin1=[Vstruc,Vprop,Vdist,Vspace] with a dimension of 4, where: Vstruc is a quantitative value of the site structure parameters (integrating site length, width, height, and obstacle distribution characteristics). Vprop is a quantitative value of the electromagnetic propagation parameters of the site (calculated based on electromagnetic reflection coefficient, transmission coefficient, and propagation attenuation coefficient). Vdist is a quantitative value of site environmental interference parameters (characterizing the intensity and frequency distribution of inherent electromagnetic interference at the site). Vspace is a quantified value of the available space parameters of the site (calculated based on the effective electromagnetic propagation space range).
[0041] S1312. Input the first input vector into the first sub-hidden layer to obtain the first intermediate vector.
[0042] In some embodiments, the first input vector Vin1 is input to the first sub-hidden layer with 64 nodes, and the basic features are extracted by the fully connected operation Z1=W1×Vin1+b1 (W1 is the weight matrix and b1 is the bias vector). Then, the ReLU activation function A1=max(0,Z1) is used to introduce nonlinearity, and the first intermediate vector Vmid1 is output.
[0043] S1313. Input the first intermediate vector into the second sub-hidden layer to obtain the first feature vector.
[0044] In some embodiments, the first intermediate vector Vmid1 is input to the second sub-hidden layer with 32 nodes, and the fully connected operation and ReLU activation process are repeated (Z2=W2×Vmid1+b2, A2=max(0,Z2)) to further refine the core features and output the first feature vector Vfeat1.
[0045] S1314. Input the first feature vector into the first output layer to obtain the equivalent simulated distance prediction value.
[0046] In some embodiments, the first feature vector Vfeat1 is input to the first output layer, and the equivalent simulated distance prediction value Rpred is directly output through the linear activation function Rpred=W3×Vfeat1+b3 (W3 is the output layer weight, b3 is the output layer bias).
[0047] S132. Based on the parameter information of the hardware equipment, determine the reasonable constraint range corresponding to the equivalent simulation distance.
[0048] In some embodiments, the hardware equipment parameters collected in step S110 are extracted, including the power amplifier output power range. Hardware antenna gain (Fixed value or intermediate value within an adjustable range), and the equivalent power density calculated in step S120. .
[0049] Based on the electromagnetic equivalence principle and the hardware boundaries of power amplifier power and antenna gain, a reasonable range for the equivalent analog distance is derived. The derivation formula is as follows:
[0050]
[0051] in, To minimize the equivalent simulation distance, To achieve the maximum equivalent simulation distance, we ensure that the equivalent distance within this range can be used to achieve an equivalent simulation of the target power density using existing hardware.
[0052] S133. Based on the predicted equivalent simulation distance and the reasonable constraint range corresponding to the equivalent simulation distance, determine the equivalent simulation distance.
[0053] In some embodiments, determining the equivalent simulation distance based on the predicted equivalent simulation distance and the reasonable constraint range corresponding to the equivalent simulation distance includes the following specific implementation process: If the predicted equivalent simulation distance is not within the reasonable constraint range corresponding to the equivalent simulation distance, the reasonable constraint range corresponding to the equivalent simulation distance is adjusted through a preset constraint adjustment mechanism until the predicted equivalent simulation distance is within the reasonable constraint range corresponding to the adjusted equivalent simulation distance, so as to determine the equivalent simulation distance. If the predicted equivalent simulation distance is within the reasonable constraint range corresponding to the equivalent simulation distance, then the predicted equivalent simulation distance is used as the initial value, and the goal is to minimize the difference between the predicted equivalent simulation distance and the predicted equivalent simulation distance. The equivalent simulation distance is then calculated using a preset constraint optimization algorithm.
[0054] Specifically, if Then The equivalent simulation distance prediction value is the initial value. Perform the following operations: Set the optimization objective: minimize the final equivalent simulation distance, i.e. , and the predicted value The difference ensures that the reference value of the predicted value is maximized; By applying a pre-defined constraint optimization algorithm (such as the Lagrange multiplier method), hardware parameter constraints and site electromagnetic propagation characteristics constraints are incorporated into the optimization process to calculate the final equivalent simulated distance. ; Output This serves as the core input for subsequent target simulation parameter calculations.
[0055] Specifically, Not located If the condition is met, the preset constraint adjustment mechanism will be activated: Based on the adjustable potential of hardware parameters (such as whether the power amplifier power is adjustable, whether the antenna gain is adjustable), a reasonable range of constraints is defined. Make adaptive adjustments, for example, if the antenna gain is adjustable, increase... The range of values should be recalculated. and ; Repeat the adjustment and range calculation process until... Falling into the adjusted constraint range Inside; Using the adjusted constraint range as the boundary and considering the actual available space on site, the final equivalent simulation distance is determined. ; After multiple adjustments If the simulation still fails to fall within the constraints, the experimenter can be prompted to check the hardware parameters or site conditions, and if necessary, replace the hardware module or adjust the simulation site.
[0056] S140. Based on the parameter information of the hardware equipment, the equivalent power density, and the equivalent simulation distance, target simulation parameters are obtained so that the hardware equipment performs equivalent simulation of the target equipment according to the target simulation parameters.
[0057] In some embodiments, the parameter information of the hardware device includes the power amplifier output power range of the hardware device and the antenna gain of the hardware device.
[0058] Specifically, obtaining the target simulation parameters based on the parameter information of the hardware equipment, the equivalent power density, and the equivalent simulation distance includes the following specific implementation process: Based on the power amplifier output power range of the hardware equipment, the antenna gain of the hardware equipment, the equivalent power density, and the equivalent simulation distance, the target simulation parameters are obtained by generating a model using preset target simulation parameters. The target simulation parameters include the target power amplifier transmit power and the target antenna gain.
[0059] In some embodiments, such as Figure 3 As shown, the preset target simulation parameter generation model includes a second input layer, a second hidden layer, and a second output layer. The second hidden layer includes a third sub-hidden layer, a fourth sub-hidden layer, and a fifth sub-hidden layer. The second output layer includes two nodes.
[0060] Specifically, the preset target simulation parameter generation model is an end-to-end deep neural network model, with the following structure: The second input layer: the number of nodes matches the dimension of the input parameters, and its core function is to receive and integrate input parameters from multiple sources; The second hidden layer contains a third, fourth, and fifth sub-hidden layers, all of which use the ReLU activation function to extract complex nonlinear correlation features between parameters. The second output layer contains two nodes, each using a linear activation function, and outputs the target power amplifier's transmit power. (Unit: W) and target antenna gain (Unit: dBi)
[0061] Specifically, the step of generating the target simulation parameters by using a preset target simulation parameter generation model based on the power amplifier output power range of the hardware equipment, the antenna gain of the hardware equipment, the equivalent power density, and the equivalent simulation distance includes the following steps S141 to S145: S141. Input the power amplifier output power range of the hardware equipment, the antenna gain of the hardware equipment, the equivalent power density, and the equivalent analog distance into the second input layer to obtain the second input vector.
[0062] In some embodiments, the following parameters are retrieved and input into the second input layer to form the second input vector Vin2=[ , , , , ],in: , The range of power output of the amplifier in the hardware equipment; Antenna gain of the hardware equipment (fixed value or intermediate value of adjustable range); The equivalent power density calculated in step S120; The equivalent simulation distance is determined in step S133.
[0063] S142. Input the second input vector into the third sub-hidden layer to obtain the second intermediate vector.
[0064] In some embodiments, the second input vector Vin2 is input to the third sub-hidden layer, and preliminary associated features are extracted through the fully connected operation Z3=W4×Vin2+b4. After processing by the ReLU activation function, the second intermediate vector Vmid2 is output, thereby realizing the preliminary feature fusion of the input parameters.
[0065] S143. Input the second intermediate vector into the fourth sub-hidden layer to obtain the third intermediate vector.
[0066] In some embodiments, the second intermediate vector Vmid2 is input to the fourth sub-hidden layer, and the fully connected operation and ReLU activation process are repeated (Z4=W5×Vmid2+b5, A4=max(0,Z4)) to further explore the deep correlation between parameters and output the third intermediate vector Vmid3.
[0067] S144. Input the third intermediate vector into the fifth sub-hidden layer to obtain the second feature vector.
[0068] In some embodiments, the third intermediate vector Vmid3 is input to the fifth sub-hidden layer, and the core features that have the greatest impact on the target simulation parameters are extracted through the fully connected operation Z5=W6×Vmid3+b6 and the ReLU activation function A5=max(0,Z5), and the second feature vector Vfeat2 is output.
[0069] S145. Input the second feature vector into the second output layer to obtain the target power amplifier transmit power and the target antenna gain.
[0070] In some embodiments, the second feature vector Vfeat2 is input to the second output layer and activated by a linear activation function [ , =W7×Vfeat2+b7 (W7 is the output layer weight matrix, b7 is the output layer bias vector), directly outputting the target power amplifier transmit power and the target antenna gain.
[0071] Therefore, the hardware equipment (power amplifier, antenna) in the radar simulation system starts to run according to the final determined target simulation parameters, accurately and equivalently simulating the battlefield electromagnetic environment of the target radar equipment, providing a realistic electromagnetic environment scenario for the indoor and outdoor tests of the equipment under test, and supporting the comprehensive evaluation of equipment performance.
[0072] The method will be illustrated below through another specific embodiment: The automatic generation software for equivalent simulation parameters of radar equipment electromagnetic environment calculates the actual transmission power density of the equipment based on information such as the frequency range, antenna gain, transmission power, and range of the radar equipment, according to the transmission power density S=P_t / 4πR²×G_t (W / m²).
[0073] For example, as shown in Table 1, the AN / TPQ-53 artillery frame correction radar, with a transmitter power of 60kW, an antenna gain of 30dBi, and an effective range of 20km, has a target power density of approximately 0.000358W / ㎡. With an existing antenna gain of 20dBi, an effective range of 0.8km, and an equivalent target power density of approximately 0.000358W / ㎡, this system, with its power amplifier transmission power set to 144W, can perform equivalent simulation scenarios of the US AN / TPQ-53 artillery frame correction radar. Furthermore, the power amplifier and antenna can be adjusted according to the actual site distance to improve the utilization of existing hardware.
[0074] Table 1. Equivalent Simulation Table Analysis
[0075] One-click generation function for equivalent parameters, such as Figure 4 As shown, the antenna gain parameters of the hardware system are obtained based on the input equivalent power density (S) and equivalent distance (R) information. According to the formula Calculate the transmission power value and determine Does the current system's power amplifier output power range meet the requirements? If so, generate equivalent parameters and compare them to the radar equipment's power density. If not, prompt the user that the current hardware cannot perform equivalent simulation. Please adjust the equivalent distance and recalculate the equivalent parameters until equivalent simulation parameters suitable for the current hardware are generated. Figure 5 As shown, this enables one-click generation of equivalent parameters for electromagnetic environment simulation of radar equipment.
[0076] Equivalent random generation function, such as Figure 6 As shown, based on the input equivalent power density (S), the hardware system antenna gain parameters are... Maximum output power of the power amplifier in the hardware system and minimum output power value Calculate the equivalent distance range , This function randomly generates an equivalent range value within the equivalent range, calculates the power amplifier output power based on the equivalent range value, and realizes the function of randomly generating equivalent simulation parameters of the electromagnetic environment of radar equipment. This function can quickly and randomly generate equivalent parameters according to the current system hardware status, enrich the test sample, and improve the training efficiency of equipment.
[0077] In summary, this application provides an equivalent simulation method for the electromagnetic environment of radar equipment, enabling equivalent simulation of radar equipment in an electromagnetic environment based on existing hardware.
[0078] To better implement the above methods, this application also provides an equivalent simulation device for the electromagnetic environment of radar equipment. This device can be integrated into an electronic device, such as a terminal or server. The terminal can be a mobile phone, tablet computer, smart Bluetooth device, laptop computer, or personal computer; the server can be a single server or a server cluster composed of multiple servers.
[0079] For example, in this embodiment, the method of this application embodiment will be described in detail by taking the radar equipment electromagnetic environment equivalent simulation device specifically integrated into the terminal as an example.
[0080] For example, such as Figure 7 As shown, the radar equipment electromagnetic environment equivalent simulation device 700 may include a first unit 701, a second unit 702, a third unit 703 and a fourth unit 704. The radar equipment electromagnetic environment equivalent simulation device 700 is applied to the radar simulation system, and the device includes: Unit 701 is used to acquire parameter information of the target equipment and parameter information of the hardware equipment in the radar simulation system. The second unit 702 is used to calculate the equivalent power density based on the parameter information of the target equipment. The third unit 703 is used to determine the equivalent simulated distance based on the simulated site information corresponding to the radar simulation system and the parameter information of the hardware equipment. The fourth unit 704 is used to obtain target simulation parameters based on the parameter information of the hardware equipment, the equivalent power density, and the equivalent simulation distance, so that the hardware equipment performs equivalent simulation of the target equipment according to the target simulation parameters.
[0081] In practice, each of the above units can be implemented as an independent entity or can be arbitrarily combined to be implemented as the same or several entities. For the specific implementation of each of the above units, please refer to the previous method embodiments, which will not be repeated here.
[0082] As can be seen from the above, the embodiments of this application can realize the equivalent simulation of radar equipment in an electromagnetic environment based on existing hardware.
[0083] This application also provides an electronic device, which can be a terminal, a server, or other similar device. The terminal can be a mobile phone, tablet computer, smart Bluetooth device, laptop computer, personal computer, etc.; the server can be a single server or a server cluster composed of multiple servers, etc.
[0084] In some embodiments, the product processing device may also be integrated into multiple electronic devices, such as multiple servers, which implement the radar equipment electromagnetic environment equivalent simulation method of this application.
[0085] In this embodiment, the electronic device will be described in detail as a terminal, for example, such as... Figure 8 As shown, it illustrates a structural schematic diagram of the terminal 800 involved in an embodiment of this application. Specifically: The terminal 800 may include components such as a processor 801 with one or more processing cores, a memory 802 with one or more media, a power supply 803, an input module 804, and a communication module 805. Those skilled in the art will understand that... Figure 8 The terminal 800 structure shown does not constitute a limitation on the terminal 800 and may include more or fewer components than shown, or combine certain components, or have different component arrangements. Wherein: The processor 801 is the control center of the terminal 800. It connects various parts of the terminal 800 via various interfaces and lines. By running or executing software programs and / or modules stored in the memory 802, and by calling data stored in the memory 802, it performs various functions of the terminal 800 and processes data, thereby providing overall monitoring of the terminal 800. In some embodiments, the processor 801 may include one or more processing cores; in some embodiments, the processor 801 may integrate an application processor and a modem processor, wherein the application processor mainly handles the operating system, user interface, and applications, and the modem processor mainly handles wireless communication. It is understood that the modem processor may also not be integrated into the processor 801.
[0086] The memory 802 can be used to store software programs and modules. The processor 801 executes various functional applications and data processing by running the software programs and modules stored in the memory 802. The memory 802 mainly includes a program storage area and a data storage area. The program storage area can store the operating system, application programs required for at least one function (such as sound playback function, image playback function, etc.), etc.; the data storage area can store data created according to the use of the terminal 800, etc. In addition, the memory 802 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device. Accordingly, the memory 802 may also include a memory controller to provide the processor 801 with access to the memory 802.
[0087] The terminal 800 also includes a power supply 803 that supplies power to the various components. In some embodiments, the power supply 803 can be logically connected to the processor 801 through a power management system, thereby enabling functions such as charging, discharging, and power consumption management through the power management system. The power supply 803 may also include one or more DC or AC power supplies, recharging systems, power fault detection circuits, power converters or inverters, power status indicators, and other arbitrary components.
[0088] The terminal 800 may also include an input module 804, which can be used to receive input digital or character information, and generate keyboard, mouse, joystick, optical or trackball signal inputs related to user settings and function control.
[0089] The terminal 800 may also include a communication module 805. In some embodiments, the communication module 805 may include a wireless module. The terminal 800 can perform short-range wireless transmission through the wireless module of the communication module 805, thereby providing users with wireless broadband Internet access. For example, the communication module 805 can be used to help users send and receive emails, browse web pages, and access streaming media.
[0090] Although not shown, terminal 800 may also include a display unit, etc., which will not be described in detail here. Specifically, in this embodiment, processor 801 in terminal 800 loads the executable files corresponding to the processes of one or more applications into memory 802 according to the following instructions, and processor 801 runs the applications stored in memory 802 to realize various functions, as follows: Acquire parameter information of the target equipment and the hardware equipment in the radar simulation system; Based on the parameter information of the target equipment, the equivalent power density is calculated; Based on the simulated site information corresponding to the radar simulation system and the parameter information of the hardware equipment, the equivalent simulated distance is determined. Based on the parameter information of the hardware equipment, the equivalent power density, and the equivalent simulation distance, target simulation parameters are obtained so that the hardware equipment performs equivalent simulation of the target equipment according to the target simulation parameters.
[0091] For details on the implementation of each of the above operations, please refer to the previous examples, which will not be repeated here.
[0092] As can be seen from the above, the embodiments of this application can realize the equivalent simulation of radar equipment in an electromagnetic environment based on existing hardware.
[0093] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be accomplished by instructions, or by instructions controlling related hardware. These instructions can be stored in a medium and loaded and executed by a processor.
[0094] Therefore, embodiments of this application provide a medium storing multiple instructions that can be loaded by a processor to execute steps in any of the radar equipment electromagnetic environment equivalent simulation methods provided in embodiments of this application. For example, the instructions can execute the following steps: Acquire parameter information of the target equipment and the hardware equipment in the radar simulation system; Based on the parameter information of the target equipment, the equivalent power density is calculated; Based on the simulated site information corresponding to the radar simulation system and the parameter information of the hardware equipment, the equivalent simulated distance is determined. Based on the parameter information of the hardware equipment, the equivalent power density, and the equivalent simulation distance, target simulation parameters are obtained so that the hardware equipment performs equivalent simulation of the target equipment according to the target simulation parameters.
[0095] The medium may include: read-only memory (ROM), random access memory (RAM), disk or optical disk, etc.
[0096] According to one aspect of this application, a computer program product or computer program is provided, comprising computer instructions stored in a medium. A processor of a computer device reads the computer instructions from the medium and executes the computer instructions, causing the computer device to perform the methods provided in the various optional implementations of the above embodiments.
[0097] Since the instructions stored in the medium can execute the steps in any of the radar equipment electromagnetic environment equivalent simulation methods provided in the embodiments of this application, the beneficial effects that any of the radar equipment electromagnetic environment equivalent simulation methods provided in the embodiments of this application can achieve can be realized. For details, please refer to the previous embodiments, which will not be repeated here.
[0098] The present application provides a detailed description of the electromagnetic environment equivalent simulation method, device, terminal, and medium for radar equipment. Specific examples have been used to illustrate the principles and implementation methods of the present application. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present application. At the same time, those skilled in the art will recognize that there will be changes in the specific implementation methods and application scope based on the ideas of the present application. Therefore, the content of this specification should not be construed as a limitation of the present application.
Claims
1. A method for equivalent simulation of the electromagnetic environment of radar equipment, characterized in that, Applied to a radar simulation system, the method includes: Acquire parameter information of the target equipment and the hardware equipment in the radar simulation system; Based on the parameter information of the target equipment, the equivalent power density is calculated; Based on the simulated site information corresponding to the radar simulation system and the parameter information of the hardware equipment, the equivalent simulated distance is determined. Based on the parameter information of the hardware equipment, the equivalent power density, and the equivalent simulation distance, target simulation parameters are obtained so that the hardware equipment performs equivalent simulation of the target equipment according to the target simulation parameters.
2. The method as described in claim 1, characterized in that, The parameter information of the target equipment includes the target equipment's transmission power, antenna gain, and effective range. The calculation of the equivalent power density based on the parameter information of the target equipment includes: The equivalent power density is calculated using the following formula: in, This represents the equivalent power density. This indicates the transmission power of the target equipment. This indicates the effective range of the target equipment. This indicates the antenna gain of the target equipment.
3. The method as described in claim 1, characterized in that, The determination of the equivalent simulated distance based on the simulated site information corresponding to the radar simulation system and the parameter information of the hardware equipment includes: Based on the simulated site information, the equivalent simulated distance prediction value is obtained through a preset equivalent simulated distance prediction model; Based on the parameter information of the hardware equipment, determine the reasonable constraint range corresponding to the equivalent simulation distance; The equivalent simulation distance is determined based on the predicted value of the equivalent simulation distance and the reasonable constraint range corresponding to the equivalent simulation distance.
4. The method as described in claim 3, characterized in that, The preset equivalent simulation distance prediction model includes a first input layer, a first hidden layer, and a first output layer. The simulated site information includes site structure parameters, site electromagnetic propagation parameters, site environmental interference parameters, and site available space parameters. The first input layer includes 4 nodes, the first hidden layer includes a first sub-hidden layer and a second hidden layer, the first hidden layer includes 64 nodes, the second hidden layer includes 32 nodes, and the first output layer includes 1 node. The step of obtaining the equivalent simulated distance prediction value based on the simulated site information and through a preset equivalent simulated distance prediction model includes: The site structure parameters, the site electromagnetic propagation parameters, the site environmental interference parameters, and the site available space parameters are input into the first input layer to obtain the first input vector; The first input vector is input into the first sub-hidden layer to obtain the first intermediate vector; The first intermediate vector is input into the second sub-hidden layer to obtain the first feature vector; The first feature vector is input into the first output layer to obtain the equivalent simulated distance prediction value.
5. The method as described in claim 3, characterized in that, The step of determining the equivalent simulation distance based on the predicted equivalent simulation distance value and the reasonable constraint range corresponding to the equivalent simulation distance includes: If the predicted equivalent simulation distance is not within the reasonable constraint range corresponding to the equivalent simulation distance, the reasonable constraint range corresponding to the equivalent simulation distance is adjusted through a preset constraint adjustment mechanism until the predicted equivalent simulation distance is within the reasonable constraint range corresponding to the adjusted equivalent simulation distance, so as to determine the equivalent simulation distance. If the predicted equivalent simulation distance is within the reasonable constraint range corresponding to the equivalent simulation distance, then the predicted equivalent simulation distance is used as the initial value, and the goal is to minimize the difference between the predicted equivalent simulation distance and the predicted equivalent simulation distance. The equivalent simulation distance is then calculated using a preset constraint optimization algorithm.
6. The method as described in claim 1, characterized in that, The parameter information of the hardware equipment includes the power amplifier output power range and the antenna gain of the hardware equipment. The target simulation parameters are obtained based on the parameter information of the hardware equipment, the equivalent power density, and the equivalent simulation distance, including: Based on the power amplifier output power range of the hardware equipment, the antenna gain of the hardware equipment, the equivalent power density, and the equivalent simulation distance, the target simulation parameters are obtained by generating a model using preset target simulation parameters. The target simulation parameters include the target power amplifier transmit power and the target antenna gain.
7. The method as described in claim 6, characterized in that, The preset target simulation parameter generation model includes a second input layer, a second hidden layer, and a second output layer. The second hidden layer includes a third sub-hidden layer, a fourth sub-hidden layer, and a fifth sub-hidden layer. The second output layer includes two nodes. The step of generating the target simulation parameters by using a preset target simulation parameter generation model based on the power amplifier output power range of the hardware equipment, the antenna gain of the hardware equipment, the equivalent power density, and the equivalent simulation distance includes: The power amplifier output power range of the hardware equipment, the antenna gain of the hardware equipment, the equivalent power density, and the equivalent analog distance are input to the second input layer to obtain the second input vector; The second input vector is input into the third sub-hidden layer to obtain the second intermediate vector; The second intermediate vector is input into the fourth sub-hidden layer to obtain the third intermediate vector; The third intermediate vector is input into the fifth sub-hidden layer to obtain the second feature vector; The second feature vector is input into the second output layer to obtain the target power amplifier transmit power and the target antenna gain.
8. A radar equipment electromagnetic environment equivalent simulation device, characterized in that, The device, used in a radar simulation system, includes: The first unit is used to acquire parameter information of the target equipment and the hardware equipment in the radar simulation system. The second unit is used to calculate the equivalent power density based on the parameter information of the target equipment. The third unit is used to determine the equivalent simulated distance based on the simulated site information corresponding to the radar simulation system and the parameter information of the hardware equipment. The fourth unit is used to obtain target simulation parameters based on the parameter information of the hardware equipment, the equivalent power density, and the equivalent simulation distance, so that the hardware equipment performs equivalent simulation of the target equipment according to the target simulation parameters.
9. A terminal, characterized in that, The method includes a processor and a memory, the memory storing multiple instructions; the processor loads instructions from the memory to perform the steps of the method as described in any one of claims 1 to 7.
10. A medium, characterized in that, The medium stores a plurality of instructions adapted for loading by a processor to execute the steps of the method according to any one of claims 1 to 7.