High-precision simulation calculation method for radiation source signal detection effectiveness based on environmental information

Abstract

The present invention relates to a high-precision simulation calculation method for radiation source signal detection efficiency based on environmental information, the method comprising: step S1, based on environmental information modeling, calculating the path loss, path length, and reflection point of each transmission path; step S2, modeling the spatial distribution of radiation energy of the radiation source and the time domain waveform of the radiation signal; step S3, using the radiation equation to calculate the signal attenuation of the radiation source signal transmitted to the receiver through each transmission path; step S4, modeling the radiation signal sequence according to the time domain waveform and power of the radiation signal, and using the Monte Carlo method to calculate the radiation source signal detection efficiency of the signal. The present invention conducts full-process modeling analysis on the radiation signal, which can greatly improve the accuracy of the entire simulation and support model-based system simulation design.

Description

Technical Field

[0001] The present invention relates to the technical field of system modeling and simulation, and in particular to a high-precision simulation calculation method for radiation source signal detection efficiency based on environmental information. Background Art

[0002] In recent years, with the widespread application of model-based systems engineering (MBSE) in complex engineering fields such as aviation, aerospace and space systems, the accuracy of subsystem models and their consistency with actual systems have become key factors in the successful design of complex system engineering. However, there are still certain limitations in the simulation of electronic equipment systems such as aircraft, mainly due to the complexity of electronic information equipment itself. The various components of electronic equipment usually require fine professional division, resulting in the use of different methods in the analysis and design process and the lack of a full system simulation model. Therefore, in model-based systems engineering, the electronic system performance model lacks an accurate description.

[0003] Traditional electronic radiation signal detection system performance simulation usually adopts functional models, which makes the model too simple and difficult to simulate the entire process of electronic radiation signal detection and reception in the actual environment, as well as the impact of different environments on the receiver response, which seriously affects the analysis of its actual working performance. Summary of the invention

[0004] In order to solve the technical problems existing in the above-mentioned prior art, the purpose of the present invention is to provide a high-precision simulation calculation method for radiation source signal detection efficiency based on environmental information, which can greatly improve the simulation calculation accuracy of the detection efficiency of electronic equipment in actual environment.

[0005] To achieve the above-mentioned object of the invention, the present invention provides a high-precision simulation calculation method for radiation source signal detection efficiency based on environmental information, comprising the following steps:

[0006] Step S1, based on environmental information modeling, calculate the path loss, path length, and reflection point of each transmission path;

[0007] Step S2, modeling the spatial distribution of radiation energy of the radiation source and the time domain waveform of the radiation signal;

[0008] Step S3, using the radiation equation to calculate the signal attenuation of the radiation source signal transmitted to the receiver through each transmission path;

[0009] Step S4: Model the radiation signal sequence according to the time domain waveform and power of the radiation signal, and use the Monte Carlo method to calculate the radiation source signal detection efficiency of the signal.

[0010] According to a technical solution of the present invention, the step S1 specifically includes:

[0011] Step S11, obtaining environmental information, wherein the environmental information at least includes terrain information, building information and vegetation information;

[0012] Step S12: establishing a three-dimensional geometric model based on the environmental information, and determining the electromagnetic parameters of each geometric body in the actual environment;

[0013] Step S13, establishing a geometric body surface reflection coefficient calculation model according to the Fresnel equation, and completing the reflection coefficient calculation. In the transmission path calculation, the loss and phase information of each reflection point are calculated according to the electromagnetic material parameters and frequency information of each reflection point;

[0014] Step S14, radiation signal transmission loss and polarization calculation model;

[0015] Step S15: The radiation source position is expressed as P s The current position of the receiver is represented by P r It means that the possible propagation paths of the radiation signal are calculated by using the bouncing ray method, and a transmission path set is established, wherein the path set includes path loss, path length, and reflection points.

[0016] According to a technical solution of the present invention, the step S2 specifically includes:

[0017] Step S21, completing the three-dimensional directional pattern modeling calculation of the receiver and the radiation source antenna;

[0018] Step S22: Generate a time domain signal waveform.

[0019] According to a technical solution of the present invention, the step S21 specifically includes:

[0020] Step S211, determining the type of the unit antenna as the radiation transmitting antenna according to the known performance parameters of the radiation source;

[0021] Step S212: Model the antenna of the radiation source according to the aperture size of the antenna, and simulate and calculate the spatial radiation of the antenna of the radiation source;

[0022] Step S213: Calculate the periodic parameters of the spatial variation of the simulated directional pattern according to the operating parameters of the radiation source and the receiver.

[0023] According to a technical solution of the present invention, the step S22 specifically includes:

[0024] Step S221: Determine the buffer size according to the sampling frequency and processing period of the receiver to prepare for the generation of the time domain signal sequence;

[0025] Step S222: determine the type of radiation signal of the radiation source signal and the corresponding signal parameters, generate a baseband signal, modulate it onto a carrier, and complete the generation of a time domain signal.

[0026] According to a technical solution of the present invention, step S3 specifically includes:

[0027] Step S31, according to the gain distribution of the radiation source and the receiver antenna, establish a probability distribution model of the gain corresponding to each channel angle during the radiation source scanning process;

[0028] Step S32, calculating the average antenna gain corresponding to each channel in actual work according to the scanning period and independence of the radiation source antenna and the receiver antenna;

[0029] Step S33: modify the radiation signal propagation power attenuation model and calculate the loss and delay parameters of each channel of the transmitter receiving port.

[0030] According to a technical solution of the present invention, the step S4 specifically includes:

[0031] Step S41, calculating the noise power at the location of the receiver according to the working parameters and working environment of the receiver;

[0032] Step S42: Calculate the signal power of each channel signal according to the modified electromagnetic wave loss calculation formula to generate a received signal sequence in an actual environment;

[0033] Step S43: Detect the signal using the time-frequency detection technology and the constant false alarm detection technology to obtain the detection probability.

[0034] Compared with the prior art, the present invention has the following beneficial effects:

[0035] The present invention proposes a high-precision simulation calculation method for the detection efficiency of radiation source signals based on environmental information. The bouncing ray method is used to solve the multipath propagation calculation problem of radiation source signals in the actual environment. According to the antenna parameters of the radiation source and the receiver, the array synthesis method is used to obtain the energy distribution of the radiation source in the spatial range, and the radiation propagation equation and the Fresnel equation are used to calculate the loss and delay caused by each propagation path of the radiation signal. Finally, the Monte Carlo method is used to simulate the process of the actual radiation signal being processed by the receiver and the influence of multipath and environmental noise on the entire detection efficiency. The radiation signal is modeled and analyzed throughout the entire process, which can greatly improve the accuracy of the entire simulation and support model-based system simulation design.

[0036] Furthermore, a calculation method for the effective gain of the antenna is considered based on the change in the movement of the radiation source. By calculating the statistical distribution of the gain change between the radiation source and the receiver during the movement, the joint distribution of all gains that meet the signal detection during the entire movement process is calculated. By calculating their joint distribution, the average value of the antenna gain in the entire process is calculated, and the radiation source signal transmission loss of ray tracing is corrected to finally obtain the average received power of the receiving antenna port. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0038] Figure 1 A flowchart of a method for high-precision simulation calculation of radiation source signal detection effectiveness based on environmental information provided in accordance with an embodiment of the present invention is schematically shown;

[0039] Figure 2 A specific flow chart of step S1 in a flow chart of a method for high-precision simulation calculation of radiation source signal detection effectiveness based on environmental information according to an embodiment of the present invention is schematically shown;

[0040] Figure 3 A specific flow chart schematically showing step S2 in the flow chart of the method for high-precision simulation calculation of radiation source signal detection efficiency based on environmental information according to one embodiment of the present invention;

[0041] Figure 4 A specific flow chart schematically showing step S3 in the flow chart of the method for high-precision simulation calculation of radiation source signal detection efficiency based on environmental information according to one embodiment of the present invention;

[0042] Figure 5 The specific flowchart of step S4 in the flowchart of the method for high-precision simulation calculation of radiation source signal detection efficiency based on environmental information according to one embodiment of the present invention is schematically shown. DETAILED DESCRIPTION

[0043] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0044] like Figure 1 As shown, a high-precision simulation calculation method for radiation source signal detection efficiency based on environmental information of the present invention comprises the following steps:

[0045] Step S1, based on environmental information modeling, calculate the path loss, path length, and reflection point of each transmission path; Step S2, model the spatial distribution of radiation energy of the radiation source and the time domain waveform of the radiation signal;

[0046] Step S3, using the radiation equation to calculate the signal attenuation of the radiation source signal transmitted to the receiver through each transmission path;

[0047] Step S4: Model the radiation signal sequence according to the time domain waveform and power of the radiation signal, and use the Monte Carlo method to calculate the radiation source signal detection efficiency of the signal.

[0048] In this embodiment, the entire process of radiation signal detection and reception can be simulated, and by modeling and calculating various working environments of the receiver, rapid generation and iterative optimization of large-scale satellite mission planning solutions can be achieved.

[0049] Through core methods such as the bouncing ray method, array synthesis, and constant false alarm detection, accurate modeling of the entire signal propagation process between the radiation source and the receiver is achieved. Compared with the traditional method, the antenna gain calculation method based on joint probability distribution is more consistent with the actual antenna scanning process, which can greatly improve the simulation calculation accuracy of the detection performance of electronic equipment in actual environments.

[0050] like Figure 2 As shown, in one embodiment of the present invention, preferably, step S1 specifically includes:

[0051] Step S11, obtaining environmental information, wherein the environmental information at least includes terrain information, building information and vegetation information;

[0052] Step S12: Establish a three-dimensional geometric model based on the environmental information, and determine the electromagnetic parameters of each geometric body in the actual environment. The electromagnetic parameters can be confirmed based on the following Table 1.

[0053]

[0054]

[0055] Table 1

[0056] Step S13: Establish a geometric surface reflection coefficient calculation model according to the Fresnel equation, and complete the reflection coefficient calculation. In the transmission path calculation, calculate the loss and phase information of each reflection point according to the electromagnetic material parameters and frequency information of each reflection point. The specific formula is as follows:

[0057]

[0058]

[0059] R H and R V are the Fresnel reflection coefficients for horizontal and vertical polarization, α is the incident angle of the ray, and ε r is the complex relative permittivity of the material.

[0060] Step S14: Radiated signal transmission loss and polarization calculation model.

[0061] The propagation of the radiation source radiation signal in three-dimensional space is tracked by calculating the transmission matrix P of the current propagation path, where i is the number of reflection points in the current transmission path.

[0062]

[0063] P i Represents the transmission matrix at each reflection point. For each reflection, the global coordinates of the incident radiation signal are transformed into the local coordinates of the reflection plane, multiplied by the reflection coefficient matrix, and then the coordinates are transformed back to the original global coordinate system. Finally, the transmission matrix of each channel is obtained, from which the channel response of each path is calculated. i The calculation method is as follows:

[0064]

[0065]

[0066] Among them, s, p, k represent a set of basis vectors of the incident plane, s represents the unit vector in the vertical direction, p represents the basis vector in the vertical direction, and k is determined according to the coordinate relationship.

[0067] After obtaining the transmission matrix P of the current path, calculate its projection in the polarization matrix R and transform the matrix into the spatial coordinate system.

[0068]

[0069] H in =P(Vtx×ktx)

[0070] Vin=PVtx

[0071] Among them, H rx and V rx are the horizontal electric field of the receiver (E θ ) and the vertical electric field The polarization vector in the global coordinate system. H in and V inare the horizontal and vertical polarization vectors of the propagation path respectively. tx The direction vector k represents the radiation direction of the radiation source tx Represents the radiation direction vector of the radiation source.

[0072] Use a 2*1 vector to represent the receiver J tx With radiation source J tx If these parameters are not provided, the default is Finally, the loss calculation formula of the path can be obtained (excluding the antenna):

[0073] IL=-20log 10 |J rx ′RJ tx |.

[0074] Step S15: The radiation source position is expressed as P S The current position of the receiver is represented by P r It means that the possible propagation paths of the radiation signal are calculated by using the bouncing ray method, and a transmission path set is established, wherein the path set includes path loss, path length, and reflection points.

[0075] The pseudo code of step S15 can be expressed as:

[0076]

[0077] like Figure 3 As shown, in one embodiment of the present invention, preferably, the step S2 specifically includes:

[0078] Step S21, completing the three-dimensional directional pattern modeling calculation of the receiver and the radiation source antenna;

[0079] Step S22: Generate a time domain signal waveform.

[0080] In one embodiment of the present invention, preferably, the step S21 specifically includes:

[0081] Step S211, determining the type of the unit antenna as the radiation transmitting antenna according to the known performance parameters of the radiation source;

[0082] Step S212: Model the antenna of the radiation source according to the aperture size of the antenna, and simulate and calculate the spatial radiation of the antenna of the radiation source;

[0083] Step S213: Calculate the periodic parameters of the spatial variation of the simulated directional pattern according to the operating parameters of the radiation source and the receiver.

[0084] In one embodiment of the present invention, preferably, the step S22 specifically includes:

[0085] Step S221: Determine the buffer size according to the sampling frequency and processing period of the receiver to prepare for the generation of the time domain signal sequence;

[0086] Step S212: Model the antenna of the radiation source according to the aperture size of the antenna, and simulate and calculate the spatial radiation of the antenna of the radiation source;

[0087] Taking line array as an example, there are three situations:

[0088] (1) If the beam width and sidelobe level of the radiation source antenna are not specified, the array factor of the uniform array is directly multiplied by the unit pattern to obtain the three-dimensional distribution pattern of the radiation source. The diameter of the radiation source in the X-axis direction is L x , the operating frequency is f, the wavelength λ = C / f, and the uniformly distributed array spacing is d x =λ / 2, so the number of units N x =floor(L x / d x ). Where floor means rounding down.

[0089]

[0090] θ represents the beam pointing direction and α represents the excitation phase per unit.

[0091] Finally, the radiation distribution of the radiation source in three-dimensional space is as follows:

[0092]

[0093] (2) If the antenna sidelobe level parameters are specified, the array factor is directly obtained by using methods such as Chebyshev synthesis to obtain the array source excitation I n , after calculating the array factor A and the unit pattern The spatial three-dimensional partial direction diagram of the radiation source is obtained.

[0094]

[0095] Among them, X0 is calculated according to the sidelobe level.

[0096] At this time, the array factor can be calculated according to the following expression

[0097]

[0098] Finally, the radiation distribution of the radiation source in three-dimensional space is as follows:

[0099]

[0100] (3) If the beam width and sidelobe level and other parameters are specified, the array factor of the radiation source is directly optimized and calculated using the intelligent optimization algorithm. After the array factor that meets the conditions is obtained, it is multiplied by the unit radiation pattern to obtain the three-dimensional spatial distribution radiation pattern of the radiation source.

[0101] Step S213: Calculate the periodic parameters of the spatial variation of the simulated directional pattern according to the operating parameters of the radiation source and the receiver.

[0102] In one embodiment of the present invention, preferably, the step S22 specifically includes:

[0103] Step S221: Determine the buffer size according to the sampling frequency and processing period of the receiver to prepare for the generation of the time domain signal sequence;

[0104] Step S222: determine the type of radiation signal of the radiation source signal and the corresponding signal parameters, generate a baseband signal, modulate it onto a carrier, and complete the generation of a time domain signal.

[0105] Step S222 specifically includes:

[0106] (1) Determine the signal type and signal parameters:

[0107] First, it is necessary to clarify the type of radiation source signal, which mainly includes the following situations: sine signal, square wave signal, pulse signal, random signal, and other custom signals;

[0108] For different types of signals, the following parameters need to be determined: frequency or period, amplitude, initial phase, and signal duration, which will determine the shape and characteristics of the signal in the time domain.

[0109] (2) Generate baseband signal:

[0110] Based on the signal type and parameters you determined, use a suitable mathematical function or algorithm to generate the baseband signal. This can be a time domain representation of the signal, such as a sine function, square wave function, etc.

[0111] (3) Select carrier frequency:

[0112] The carrier frequency to modulate to needs to be chosen. This is usually determined by the requirements and parameters of the communication system. For example, for wireless communications, the carrier frequency of the radiating source is usually in the megahertz or gigahertz range.

[0113] (4) Modulation:

[0114] The baseband signal is modulated onto the selected carrier frequency using a suitable modulation method, which can be amplitude modulation (AM), frequency modulation (FM), phase modulation (PM), etc., depending on the radiation source parameters.

[0115] (5) Generate time domain signal:

[0116] Finally, the modulated signal is combined with the carrier to generate a complete time domain signal, which can be used as a radiation source signal for detection effectiveness calculation.

[0117] like Figure 4 As shown, in one embodiment of the present invention, preferably, the step S3 specifically includes:

[0118] Step S31, according to the gain distribution of the radiation source and the receiver antenna, establish a probability distribution model of the gain corresponding to each channel angle during the radiation source scanning process;

[0119] Step S31 includes the following steps:

[0120] Step S311: After obtaining the antenna pattern, calculate the value range of the radiation source antenna gain under the detection reception condition: The receiver antenna gain range is Then the antenna pattern is discretized. Generally, the antenna gain is in intervals of 1 dB. Therefore, after the radiation source and the receiver start to work together, the radiation source antenna gain and the receiver antenna gain corresponding to each channel are two random variables X i ,Y i (i represents the channel number).

[0121] Step S312: Discretize the angular range of the antenna corresponding to each channel, generally at intervals of 1°, and count the probability of occurrence of each gain amplitude to obtain its probability density function f1(x i ) and f2(y i ).

[0122] Step S32, calculating the average antenna gain corresponding to each channel in actual work according to the scanning period and independence of the radiation source antenna and the receiver antenna;

[0123] The main derivation of step S32 is as follows:

[0124] The antenna gain of the radiation source and the receiver value are both random variables, and their sum Z i =X i +Y i is also a random variable. Due to its independence, its joint distribution can be directly expressed as:

[0125] f3(x i ,y i )=f1(x i )f2(y i )

[0126] Its integral result over the range of the radiation source and receiver antenna gain is 1.

[0127] For the i-th channel, on the plane formed by the radiation source antenna and the receiver antenna gain, Defined rectangular area, the probability of a point falling within this area

[0128] and

[0129]

[0130] The probability that the radiation source gain and the receiver gain do not exceed a certain value W is:

[0131]

[0132] Therefore, the source and receiver gains and probability density functions are given by:

[0133] f3(z i )=∫f1(x i )f2z i -x i )dx i )

[0134] The average gain is G mean =∫Gf3(z i ), G represents the sum of the radiation source and receiver antenna gains.

[0135] Step S33, correcting the radiation signal propagation power attenuation model, and calculating the loss and delay parameters of each channel of the transmitter receiving port, specifically including:

[0136] Calculate the loss and delay parameters of each channel at the transmitter receiving port under the conditions of the transmitting and receiving antennas, where the loss of the i-th channel at the antenna port is equal to the channel loss IL i With the average gain G mean The sum is expressed as:

[0137] L i ant =IL i +G mean .

[0138] like Figure 5 As shown, in one embodiment of the present invention, preferably, the step S4 specifically includes:

[0139] Step S41, calculating the noise power at the location of the receiver according to the working parameters and working environment of the receiver; specifically comprising:

[0140] The thermal noise of the receiver is related to the noise factor NF of the receiver itself, the operating bandwidth BW of the receiver and other parameters. The thermal noise of the receiver can be calculated according to the following expression.

[0141]

[0142] in, Represents the noise floor, which is generally -174dbm.

[0143] Step S42, according to the modified electromagnetic wave loss calculation formula, calculate the signal power of each channel signal to generate a received signal sequence under the actual environment; specifically including the following steps:

[0144] Step S421: Calculate the received power currently transmitted to the receiving antenna port through the i-th channel according to the radiation transmission formula.

[0145]

[0146] Step S422: Generate a signal sequence according to the signal waveform and the received power of the radiation signal, and generate an environmental noise signal according to the noise power and distribution.

[0147]

[0148]

[0149] Step S423: superimpose all signals to obtain a signal sequence under the current environment.

[0150]

[0151] Step S43: Detect the signal using the time-frequency detection technology and the constant false alarm detection technology to obtain the detection probability.

[0152] Based on the detection probability, the detection efficiency of the radiation source signal can be analyzed.

[0153] According to one aspect of the present invention, an electronic device is provided, comprising: one or more processors, one or more memories, and one or more computer programs; wherein the processor is connected to the memory, and the one or more computer programs are stored in the memory, and when the electronic device is running, the processor executes the one or more computer programs stored in the memory, so that the electronic device executes a high-precision simulation calculation method for radiation source signal detection efficiency based on environmental information, such as any one of the above technical solutions.

[0154] According to one aspect of the present invention, a computer-readable storage medium is provided for storing computer instructions. When the computer instructions are executed by a processor, a high-precision simulation calculation method for radiation source signal detection efficiency based on environmental information is implemented as described in any of the above technical solutions.

[0155] Computer-readable storage media may include any medium capable of storing or transmitting information. Examples of computer-readable storage media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, optical fiber media, radio frequency (RF) links, etc. Code segments may be downloaded via computer networks such as the Internet, intranets, etc.

[0156] The invention discloses a high-precision simulation calculation method for radiation source signal detection efficiency based on environmental information, the method comprising: step S1, based on environmental information modeling, calculating the path loss, path length, and reflection point of each transmission path; step S2, modeling the spatial distribution of radiation energy of the radiation source and the time domain waveform of the radiation signal; step S3, using the radiation equation to calculate the signal attenuation of the radiation source signal transmitted to the receiver through each transmission path; step S4, modeling the radiation signal sequence according to the time domain waveform and power of the radiation signal, and using the Monte Carlo method to calculate the radiation source signal detection efficiency of the signal. The bouncing ray method is used to solve the multipath propagation calculation problem of the radiation source signal in the actual environment, and the energy distribution of the radiation source in the spatial range is obtained according to the antenna parameters of the radiation source and the receiver by using the array synthesis method, and the radiation propagation equation and the Fresnel equation are used to calculate the loss and delay caused by each propagation path of the radiation signal. Finally, the Monte Carlo method is used to simulate the process of the actual radiation signal being processed by the receiver and the influence of multipath and environmental noise on the entire detection efficiency, and the radiation signal is modeled and analyzed in the whole process, which can greatly improve the accuracy of the entire simulation and support the system simulation design based on the model.

[0157] Furthermore, a calculation method for the effective gain of the antenna is considered based on the change in the movement of the radiation source. By calculating the statistical distribution of the gain change between the radiation source and the receiver during the movement, the joint distribution of all gains that meet the signal detection during the entire movement process is calculated. By calculating their joint distribution, the average value of the antenna gain in the entire process is calculated, and the radiation source signal transmission loss of ray tracing is corrected to finally obtain the average received power of the receiving antenna port.

[0158] In addition, it should be noted that the present invention can be provided as a method, an apparatus or a computer program product. Therefore, the embodiments of the present invention can take the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware. Moreover, the embodiments of the present invention can take the form of a computer program product implemented on one or more computer-usable storage media containing computer-usable program code.

[0159] The embodiments of the present invention are described with reference to the flowcharts and / or block diagrams of the methods, terminal devices (systems), and computer program products according to the embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, an embedded processor, or other programmable data processing terminal device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing terminal device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0160] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing terminal device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 These computer program instructions can also be loaded onto a computer or other programmable data processing terminal device, so that a series of operation steps are executed on the computer or other programmable terminal device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable terminal device provide for implementing the process in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0161] It should also be noted that, in this article, the terms "include", "comprises" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or terminal device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or terminal device. In the absence of further restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, article or terminal device including the elements.

[0162] Finally, it should be noted that the above is a preferred embodiment of the present invention. It should be pointed out that although the preferred embodiment of the present invention has been described, for those skilled in the art, once the basic creative concept of the present invention is known, several improvements and modifications can be made without departing from the principles of the present invention, and these improvements and modifications should also be regarded as the protection scope of the present invention. Therefore, the attached claims are intended to be interpreted as including the preferred embodiment and all changes and modifications that fall within the scope of the embodiments of the present invention.

Claims

1. A high-precision simulation calculation method for radiation source signal detection efficiency based on environmental information, characterized in that: The following steps are involved: Step S1, based on environmental information modeling, calculate the path loss, path length, and reflection point of each transmission path; Step S2, modeling the spatial distribution of radiation energy of the radiation source and the time domain waveform of the radiation signal; Step S3, using the radiation equation to calculate the signal attenuation of the radiation source signal transmitted to the receiver through each transmission path; Step S4, modeling the radiation signal sequence according to the time domain waveform and power of the radiation signal, and calculating the radiation source signal detection efficiency of the signal using the Monte Carlo method; The step S1 specifically includes: Step S11, obtaining environmental information, wherein the environmental information at least includes terrain information, building information and vegetation information; Step S12: establishing a three-dimensional geometric model based on the environmental information, and determining the electromagnetic parameters of each geometric body in the actual environment; Step S13, establishing a geometric body surface reflection coefficient calculation model according to the Fresnel equation, and completing the reflection coefficient calculation. In the transmission path calculation, the loss and phase information of each reflection point are calculated according to the electromagnetic material parameters and frequency information of each reflection point; Step S14, radiation signal transmission loss and polarization calculation model; Step S15: The radiation source position is expressed as P s The current position of the receiver is represented by P r It indicates that the possible propagation paths of the radiation signal are calculated by using the bouncing ray method, and a transmission path set is established, wherein the path set includes path loss, path length, and reflection points; The step S2 specifically includes: Step S21, completing the three-dimensional directional pattern modeling calculation of the receiver and the radiation source antenna; Step S22, generating a time domain signal waveform; The step S4 specifically includes: Step S41, calculating the noise power at the location of the receiver according to the working parameters and working environment of the receiver; Step S42: Calculate the signal power of each channel signal according to the modified electromagnetic wave loss calculation formula to generate a received signal sequence in an actual environment; Step S43: Detect the signal using the time-frequency detection technology and the constant false alarm detection technology to obtain the detection probability.

2. The high-precision simulation calculation method for radiation source signal detection efficiency based on environmental information according to claim 1 is characterized in that: The step S21 specifically includes: Step S211, determining the type of the unit antenna as the radiation transmitting antenna according to the known performance parameters of the radiation source; Step S212: Model the antenna of the radiation source according to the aperture size of the antenna, and simulate and calculate the spatial radiation of the antenna of the radiation source; Step S213: Calculate the periodic parameters of the spatial variation of the simulated directional pattern according to the operating parameters of the radiation source and the receiver.

3. The high-precision simulation calculation method for radiation source signal detection efficiency based on environmental information according to claim 1 is characterized in that: The step S22 specifically includes: Step S221: Determine the buffer size according to the sampling frequency and processing period of the receiver to prepare for the generation of the time domain signal sequence; Step S222: determine the type of radiation signal of the radiation source signal and the corresponding signal parameters, generate a baseband signal, modulate it onto a carrier, and complete the generation of a time domain signal.

4. The high-precision simulation calculation method for radiation source signal detection efficiency based on environmental information according to claim 1 is characterized in that: The step S3 specifically includes: Step S31, according to the gain distribution of the radiation source and the receiver antenna, establish a probability distribution model of the gain corresponding to each channel angle during the radiation source scanning process; Step S32, calculating the average antenna gain corresponding to each channel in actual work according to the scanning period and independence of the radiation source antenna and the receiver antenna; Step S33: modify the radiation signal propagation power attenuation model and calculate the loss and delay parameters of each channel of the transmitter receiving port.

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