Radar multi-parameter model generation method, system and terminal

Abstract

The invention discloses a model generation method and system for various parameters of a radar and a terminal, and the method comprises the steps: obtaining target signal amplitudes corresponding to various transmitting parameters of a target radar and a signal source under a first preset condition based on a target test environment, and building a gain model of an amplifier according to thin-plate spline interpolation; based on the target test environment, target signal amplitudes corresponding to various intermediate frequency signal frequencies of the target radar under a second preset condition are acquired, and a transmission model of a filter is established according to thin-plate spline interpolation; based on an empty darkroom environment, acquiring a signal corresponding to a fixed frequency of the target radar under a third preset condition, and establishing a noise model according to a Gaussian mixture model; and obtaining and outputting a model set according to the gain model of the amplifier, the transmission model of the filter and the noise model. According to the method, various parameters can be obtained from the high-integration radar chip, so that the corresponding model is constructed.

Description

Technical Field

[0001] The present invention relates to the field of radar data processing, and in particular to a model generation method, system and terminal for multiple parameters of a radar. Background Art

[0002] For radars used in fields such as autonomous driving and drones, due to their generally high integration characteristics, the component parameters inside the radar cannot be directly obtained through testing, and only end-to-end data can be obtained.

[0003] At present, the method of obtaining component parameters from suppliers is not universal. There is currently a lack of methods to directly obtain amplifier gain, filter characteristics and noise parameters from highly integrated radar chips, so it is impossible to build a model that can accurately reflect the characteristics of real radars.

[0004] Therefore, the prior art still needs to be improved and developed. Summary of the invention

[0005] The main purpose of the present invention is to provide a model generation method, system, terminal and computer-readable storage medium for multiple parameters of a radar, aiming to solve the problem in the prior art that there is currently a lack of methods for directly obtaining amplifier gain, filtering characteristics and noise parameters from a highly integrated radar chip, so that a model that can accurately reflect the characteristics of a real radar cannot be established.

[0006] To achieve the above object, the present invention provides a method for generating models of multiple parameters of a radar, and the method for generating models of multiple parameters of a radar comprises the following steps:

[0007] Based on the target test environment, the target signal amplitudes corresponding to various emission parameters of the target radar and the signal source under the first preset condition are obtained, and a gain model of the amplifier is established according to thin plate spline interpolation;

[0008] Based on the target test environment, the target signal amplitudes corresponding to multiple intermediate frequency signal frequencies of the target radar under the second preset condition are obtained, and a transmission model of the filter is established according to thin plate spline interpolation;

[0009] Based on an empty darkroom environment, a signal corresponding to a fixed frequency of the target radar under a third preset condition is obtained, and a noise model is established according to a mixed Gaussian model;

[0010] According to the gain model of the amplifier, the transmission model of the filter and the noise model, a model collection is obtained and output.

[0011] Optionally, the acquiring, based on the target test environment, target signal amplitudes corresponding to a plurality of emission parameters of the target radar and the signal source under the first preset condition specifically includes:

[0012] Based on the target test environment, a horn antenna is set to face the target radar, and other parameters of the target radar are set to be fixed;

[0013] Obtain the target radar's received target signal amplitude corresponding to the target radar's multiple transmitted signal frequencies and the signal source transmitting a single-frequency continuous wave with a fixed frequency difference with the transmitted signal.

[0014] Optionally, establishing the gain model of the amplifier according to thin plate spline interpolation specifically includes:

[0015] Taking multiple transmission signal frequencies and corresponding transmission amplitudes as independent variables, taking the corresponding target signal amplitude as dependent variable, and calculating the relationship between the corresponding independent variables and dependent variables according to thin plate spline interpolation, multiple gain functions are obtained;

[0016] All gain functions are fitted to obtain a gain model of the amplifier.

[0017] Optionally, obtaining target signal amplitudes corresponding to multiple frequencies of the target radar under a second preset condition based on the target test environment specifically includes:

[0018] Based on the target test environment, a horn antenna is set to face the target radar, and the output power and frequency of the signal source are set to be fixed;

[0019] Obtain the target signal amplitude output by the target radar at different intermediate frequency signal frequencies.

[0020] Optionally, the step of establishing a transmission model of a filter according to thin plate spline interpolation specifically includes:

[0021] Taking the intermediate frequency signal frequency as the independent variable and the corresponding target signal amplitude as the dependent variable, the relationship between the independent variable and the dependent variable is calculated according to the thin plate spline interpolation to obtain the corresponding multiple transfer functions;

[0022] All transfer functions are fitted to obtain the transmission model of the filter.

[0023] Optionally, acquiring a signal corresponding to a fixed frequency of the target radar under a third preset condition based on an empty darkroom environment specifically includes:

[0024] Based on the empty darkroom environment, setting the frequency of the target radar to be fixed;

[0025] Get the signal output by the target radar.

[0026] Optionally, establishing a noise model according to a mixed Gaussian model specifically includes:

[0027] All signals output by the target radar are filtered to remove the influence of the filter and obtain multiple noise data;

[0028] All the noise data are fitted with a mixed Gaussian model to obtain the noise model.

[0029] In addition, to achieve the above-mentioned purpose, the present invention further provides a model generation system for multiple parameters of a radar, wherein the model generation system for multiple parameters of the radar includes:

[0030] A gain model generation module is used to obtain target signal amplitudes corresponding to multiple emission parameters of the target radar and the signal source under the first preset condition based on the target test environment, and establish a gain model of the amplifier according to thin plate spline interpolation;

[0031] A transmission model output module, used to obtain target signal amplitudes corresponding to multiple intermediate frequency signal frequencies of the target radar under a second preset condition based on the target test environment, and establish a transmission model of the filter according to thin plate spline interpolation;

[0032] A noise model generation module is used to obtain a signal corresponding to a fixed frequency of the target radar under a third preset condition based on an empty darkroom environment, and establish a noise model according to a mixed Gaussian model;

[0033] The result output module is used to obtain and output a model collection according to the gain model of the amplifier, the transmission model of the filter and the noise model.

[0034] In addition, to achieve the above-mentioned purpose, the present invention also provides a terminal, wherein the terminal includes: a memory, a processor, and a model generation program for multiple parameters of a radar stored in the memory and executable on the processor, and when the model generation program for multiple parameters of the radar is executed by the processor, the steps of the model generation method for multiple parameters of the radar as described above are implemented.

[0035] In addition, to achieve the above-mentioned purpose, the present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a model generation program for multiple parameters of a radar, and when the model generation program for multiple parameters of a radar is executed by a processor, the steps of the model generation method for multiple parameters of a radar as described above are implemented.

[0036] In the present invention, based on the target test environment, the target signal amplitudes corresponding to various emission parameters of the target radar and the signal source under the first preset condition are obtained, and the gain model of the amplifier is established according to the thin plate spline interpolation; based on the target test environment, the target signal amplitudes corresponding to various intermediate frequency signal frequencies of the target radar under the second preset condition are obtained, and the transmission model of the filter is established according to the thin plate spline interpolation; based on the empty darkroom environment, the signal corresponding to the fixed frequency of the target radar under the third preset condition is obtained, and the noise model is established according to the mixed Gaussian model; according to the gain model of the amplifier, the transmission model of the filter and the noise model, a model collection is obtained and output. The present invention can obtain corresponding data under specific circumstances through the set data acquisition method, thereby constructing a corresponding model, and achieving the effect of obtaining amplifier gain, filtering characteristics and noise parameters from a highly integrated radar chip. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 It is a flow chart of a preferred embodiment of a method for generating models of multiple parameters of a radar according to the present invention;

[0038] Figure 2 It is a schematic diagram of the structure of a target radar in the model generation method of multiple parameters of the radar of the present invention;

[0039] Figure 3 It is a schematic diagram of a target test environment in a method for generating a model of multiple parameters of a radar according to the present invention;

[0040] Figure 4 It is a signal schematic diagram of a test process corresponding to establishing a gain model of an amplifier in a model generation method of multiple parameters of a radar of the present invention;

[0041] Figure 5 It is a signal schematic diagram of a test process corresponding to establishing a transmission model of a filter in a model generation method of multiple parameters of a radar of the present invention;

[0042] Figure 6 It is a fitting schematic diagram of the amplifier gain model generation process in the radar multiple parameter model generation method of the present invention;

[0043] Figure 7 It is a fitting schematic diagram of the transmission model generation process of the filter in the model generation method of multiple parameters of the radar of the present invention;

[0044] Figure 8 It is a schematic diagram of removing the influence of the filter in the process of establishing the noise model in the model generation method of multiple parameters of the radar of the present invention;

[0045] Fig. 9It is a schematic diagram of fitting of a mixed Gaussian model in the process of establishing a noise model in the model generation method of multiple parameters of the radar of the present invention;

[0046] Fig.10 It is a structural diagram of a preferred embodiment of a model generation system for multiple parameters of a radar of the present invention;

[0047] Fig.11 It is a structural diagram of a preferred embodiment of the terminal of the present invention. DETAILED DESCRIPTION

[0048] In order to make the purpose, technical solution and advantages of the present invention clearer and more specific, the present invention is further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0049] For radars used in fields such as autonomous driving and drones, due to their generally high integration characteristics, the internal component parameters of the radar cannot be directly obtained through testing, and only end-to-end data can be obtained. At present, the method of obtaining component parameters from suppliers is not universal. There is currently a lack of methods to directly obtain amplifier gain, filtering characteristics, and noise parameters from highly integrated radar chips, so it is impossible to establish a model that can accurately reflect the characteristics of real radars.

[0050] In response to one or more of the above problems, the present invention obtains target signal amplitudes corresponding to multiple transmission parameters of a target radar and a signal source under a first preset condition based on a target test environment, and establishes a gain model of an amplifier according to thin plate spline interpolation; based on the target test environment, obtains target signal amplitudes corresponding to multiple intermediate frequency signal frequencies of the target radar under a second preset condition, and establishes a transmission model of a filter according to thin plate spline interpolation; based on an empty darkroom environment, obtains a signal corresponding to a fixed frequency of the target radar under a third preset condition, and establishes a noise model according to a mixed Gaussian model; and obtains a model collection according to the gain model of the amplifier, the transmission model of the filter and the noise model and outputs it.

[0051] The model generation method of multiple parameters of radar described in the preferred embodiment of the present invention is as follows: Figure 1 As shown, the model generation method of multiple parameters of the radar includes the following steps:

[0052] Step S10: based on the target test environment, the target signal amplitudes corresponding to the various transmission parameters of the target radar and the signal source under the first preset condition are obtained, and a gain model of the amplifier is established according to thin plate spline interpolation.

[0053] Specifically, in the present invention, the amplifier gain model is constructed by testing the target radar under the target test environment to obtain data. Figure 2 As shown, it includes a receiving antenna, a low noise amplifier (LNA), a mixer, a filter, an analog / digital converter (ADC), a power amplifier (PA) and a low pass filter (LPF). The signal amplitude A output by the receiving module Receiver The local oscillator signal A LO 、Echo signal A echo , low noise amplifier (LNA) gain G LNA (f, A), filtering characteristics Tr filter (f) Receiving pattern G pattern_Rx (θ, φ) and the mixed thermal noise A of the receiving circuit noise Influence. pattern_Rx (θ, φ) can be directly tested to obtain the radar transmission power and local oscillator signal A LO Known. Where f represents frequency and A represents amplitude.

[0054] In the present invention, the specific target test environment is as follows Figure 3 As shown in the figure, the test is carried out in the darkroom to reduce environmental interference. To collect the data of the radar receiving module, it is necessary to place a target in the microwave darkroom to generate an echo signal, but this method will introduce errors caused by the target RCS. In order to obtain a higher-precision echo signal, this paper uses a vector signal source and a standard gain antenna to transmit an amplitude of A. signal generator In each test, the spatial propagation loss L can be calculated based on the distance R1 between the antenna and the radar. space (f), and then calculate the echo signal amplitude A at the radar receiving antenna echo , where the corresponding calculation formula is as follows:

[0055] L space (f) = 20log 10 (R1)+20log 10 (f)+92.45;

[0056] A echo =A signal generator -L space .

[0057] Furthermore, the step of obtaining target signal amplitudes corresponding to a plurality of emission parameters of the target radar and the signal source under the first preset condition based on the target test environment specifically includes:

[0058] Based on the target test environment, a horn antenna is set to face the target radar, and other parameters of the target radar are set to be fixed;

[0059] Obtain the target radar's received target signal amplitude corresponding to the target radar's multiple transmitted signal frequencies and the signal source transmitting a single-frequency continuous wave with a fixed frequency difference with the transmitted signal.

[0060] It should be noted that, in the present invention, when establishing the gain model of the amplifier, the corresponding data is obtained by testing in the target test environment. The first preset condition is that the horn antenna is facing the target radar, and the other parameters of the target radar are set to be fixed.

[0061] Specifically, the low noise amplifier gain G LNA (f, A) will change with the amplitude and frequency of the input signal, fitting G LNA (f, A) requires the amplitude data of the signal output by the receiving module when inputting echo signals of different amplitudes and frequencies while keeping other parameters in the receiving module unchanged. Therefore, in the present invention, the horn antenna is firstly placed directly against the target radar in the test environment to keep the receiving antenna gain G pattern_Rx (0, 0) remains unchanged, while the distance between the horn antenna and the target radar is set according to the requirements of the specific microwave darkroom; in order to keep the input to Tr filter (f) The intermediate frequency signal remains unchanged, and a radar is used to transmit a single-frequency continuous wave. The signal source, that is, the signal source transmits a single-frequency continuous wave with a fixed frequency difference from the radar transmission frequency. This method changes the frequency of the signal input to the LNA while ensuring that the intermediate frequency after mixing remains unchanged. Specifically, Figure 4 As shown. In addition, in order to obtain radar output data under different input frequencies and amplitudes, the radar's transmit signal frequency, the frequency and power of the signal source transmit signal are adjusted accordingly to obtain the target signal amplitude output by the radar under different frequency and amplitude echo signal inputs. The corresponding amplifier gain model is constructed by obtaining the corresponding received target signal amplitude in this case.

[0062] Furthermore, the step of establishing the gain model of the amplifier according to thin plate spline interpolation specifically includes:

[0063] Taking multiple transmission signal frequencies and corresponding transmission amplitudes as independent variables, taking the corresponding target signal amplitude as dependent variable, and calculating the relationship between the corresponding independent variables and dependent variables according to thin plate spline interpolation, multiple gain functions are obtained;

[0064] All gain functions are fitted to obtain a gain model of the amplifier.

[0065] Specifically, since the LNA gain varies with the frequency and amplitude of the input signal, the amplifier data collected at different amplitudes and frequencies, that is, the target signal amplitude corresponding to various transmission parameters of the target radar and the signal source under the first preset condition, is interpolated using thin plate splines to fit the radar LNA gain under different conditions and establish the amplifier gain model. When using thin plate spline interpolation, various transmission signal frequencies and corresponding transmission amplitudes are used as independent variables, and the corresponding target signal amplitude is used as the dependent variable. The relationship between the corresponding independent variable and the dependent variable is calculated according to the thin plate spline interpolation, and the corresponding function can be obtained. By fitting these functions, the amplifier gain model can be constructed.

[0066] Step S20: based on the target test environment, obtaining the target signal amplitudes corresponding to a plurality of intermediate frequency signal frequencies of the target radar under a second preset condition, and establishing a transmission model of the filter according to thin plate spline interpolation.

[0067] Specifically, for the transmission model of the filter, the present invention also adopts the target test environment for testing, so as to obtain the corresponding model.

[0068] Further, based on the target test environment, obtaining the target signal amplitudes corresponding to multiple frequencies of the target radar under the second preset condition specifically includes:

[0069] Based on the target test environment, a horn antenna is set to face the target radar, and the output power and frequency of the signal source are set to be fixed;

[0070] Obtain the target signal amplitude output by the target radar at different intermediate frequency signal frequencies.

[0071] Specifically, the second preset condition is that the horn antenna faces the target radar, and the output power and frequency of the signal source are set to be fixed. filter (f) Affected by the frequency of the intermediate frequency signal, the frequency of the RF signal and the strength of the echo signal A are maintained while changing the frequency of the intermediate frequency signal. echo and the receiving antenna pattern G pattern_Rx (θ, φ) remains unchanged, then we can get Tr filter (f) Data that varies with the frequency of the intermediate frequency signal. Therefore, in the present invention, also in a darkroom environment, i.e., a target test environment, the horn antenna is kept facing the target radar to maintain the receiving antenna gain G pattern_Rx (0, 0) remains unchanged, and only the signal amplitude of the target frequency point in the spectrum is extracted to ignore the influence of thermal noise and quantization noise. LNAThe influence of (f, A) is to keep the output power and frequency of the signal generator, that is, the signal source, unchanged so that the signal amplitude and strength output to the LNA remain unchanged. Correspondingly, the target signal amplitude output by the target radar under different intermediate frequency signals is obtained. The specific test process radar input and output are as follows Figure 5 As shown in the figure, the transmission model of the corresponding filter is constructed by obtaining the target signal amplitude output by the target radar at different intermediate frequency signal frequencies.

[0072] Furthermore, the transmission model of the filter is established according to the thin plate spline interpolation, specifically including:

[0073] Taking the intermediate frequency signal frequency as the independent variable and the corresponding target signal amplitude as the dependent variable, the relationship between the independent variable and the dependent variable is calculated according to the thin plate spline interpolation to obtain the corresponding multiple transfer functions;

[0074] All transfer functions are fitted to obtain the transmission model of the filter.

[0075] Specifically, the filter characteristics vary with the frequency of the input signal, and the variation is relatively simple. The present invention also uses spline interpolation to fit the parameters and establish a transmission model of the filter; that is, the present invention uses thin plate spline interpolation to establish the transmission model of the filter. The intermediate frequency signal frequency is used as the independent variable, and the corresponding target signal amplitude is used as the dependent variable. The relationship between the corresponding independent variable and the dependent variable is calculated according to the thin plate spline interpolation to obtain the corresponding multiple transmission functions, so as to fit all the transmission functions to obtain the transmission model of the filter. The obtained transmission model of the filter and the gain model of the amplifier are both a transmission coefficient model.

[0076] Step S30: Based on an empty darkroom environment, a signal corresponding to a fixed frequency of the target radar under a third preset condition is obtained, and a noise model is established according to a mixed Gaussian model.

[0077] Specifically, in the present invention, for the construction of the noise model, an empty darkroom is used to measure the corresponding data, so that the noise model is established using the obtained data.

[0078] Further, based on the empty darkroom environment, obtaining the signal corresponding to the fixed frequency of the target radar under the third preset condition specifically includes:

[0079] Based on the empty darkroom environment, setting the frequency of the target radar to be fixed;

[0080] Get the signal output by the target radar.

[0081] Specifically, the third preset condition is that the frequency of the target radar is fixed; the thermal noise in the receiving circuit is mainly caused by the random thermal motion of the electrons inside the LNA and the mixer when the target radar is working. echo= 0, the G inside the target radar pattern_Rx (θ, φ) and G LNA (f, A) are not working, so in order to obtain thermal noise data, it is necessary to firstly make the radar transmitting module emit a single-frequency continuous wave at a fixed frequency to keep the radar in working state, and then place the radar in an empty darkroom to eliminate the echo signal generated by the external signal source and the reflection of the scene target. Since there is no target in front, the radar does not receive the echo signal. At this time, the signal output by the radar is all filtered thermal noise signals. Correspondingly, the signal output by the target radar is obtained in an empty darkroom environment and under the third preset condition, so as to construct a noise model.

[0082] Furthermore, the noise model is established according to the mixed Gaussian model, specifically including:

[0083] All signals output by the target radar are filtered to remove the influence of the filter and obtain multiple noise data;

[0084] All the noise data are fitted with a mixed Gaussian model to obtain the noise model.

[0085] Specifically, a single thermal noise is caused by fractional thermal motion and conforms to the Gaussian distribution. However, thermal noise is a mixed noise generated by multiple elements. The present invention uses a mixed Gaussian model to fit the noise data and establish a noise model. However, at this time, all the signals output by the target radar, that is, the noise data obtained by the test, are filtered data. Before fitting, the noise data must first be filtered to remove the influence of the filter, and then the mixed Gaussian model is used for fitting to obtain the noise model. Among them, the mixed Gaussian model assumes that all data points are generated by a mixture of multiple Gaussian distributions, and each Gaussian distribution represents a potential "cluster" or "category" in the data. These clusters are represented by Gaussian distributions with different parameters (including mean, covariance matrix and mixing coefficient). GMM can capture complex data distributions.

[0086] Step S40: Obtain a model collection according to the gain model of the amplifier, the transmission model of the filter and the noise model, and output the model collection.

[0087] Specifically, in the present invention, after obtaining the corresponding amplifier gain model, filter transmission model and noise model through testing, in the present invention, these models are summarized to obtain the corresponding model collection, and output to the target address or the device corresponding to the target user.

[0088] Furthermore, the method of the present invention is used to collect data, wherein a total of 20 LNA gain data of different frequencies in the radar working frequency band are collected, wherein 10 groups of different signal amplitudes are taken for each frequency, and thin plate spline interpolation fitting G is used. LNA (f, A), such as Figure 6As shown, it can be seen that the parameter is accurately fitted. The filter data is collected using the acquisition method of the present invention, and a total of 50 radar output target signal amplitudes at different transmission frequencies are collected. Spline interpolation is used to fit Tr filter (f) If Figure 7 As shown, it can be seen that this method achieves the fitting of parameters. At the same time, the data corresponding to the noise model is collected using the collection method of the present invention, and the noise data is corrected using the filter data after collection, such as Figure 8 As shown. Considering that the thermal noise signal of the receiving module is a mixture of the thermal noise of the LNA and the thermal noise of the mixer, the second-order mixed Gaussian model is used to fit the distribution of the noise, as shown in Fig. 9 As shown, the weight of the first Gaussian distribution is 0.3186, the mean is -66.1312, and the variance is 0.8167; the weight of the second Gaussian distribution is 0.6814, the mean is -65.2292, and the variance is 0.7247, achieving accurate fitting of the noise parameters.

[0089] Based on the target test environment, the present invention obtains the target signal amplitude corresponding to multiple emission parameters of the target radar and the signal source under the first preset condition, and establishes the gain model of the amplifier according to the thin plate spline interpolation; based on the target test environment, the target signal amplitude corresponding to multiple intermediate frequency signal frequencies of the target radar under the second preset condition is obtained, and the transmission model of the filter is established according to the thin plate spline interpolation; based on the empty darkroom environment, the signal corresponding to the fixed frequency of the target radar under the third preset condition is obtained, and the noise model is established according to the mixed Gaussian model; according to the gain model of the amplifier, the transmission model of the filter and the noise model, a model collection is obtained and output. The present invention can obtain the corresponding data under specific circumstances through the set data acquisition method, thereby constructing the corresponding model, and achieving the effect of obtaining the amplifier gain, filtering characteristics and noise parameters from the highly integrated radar chip.

[0090] In addition, according to the working principles of FMCW radar and RF components, the present invention adopts a test method for LNA gain, filter transmission characteristics and radar receiving circuit noise in a highly integrated radar RF circuit in a microwave darkroom by adjusting the test conditions, and effectively obtains the data of the above component parameters from end-to-end testing; and obtains the corresponding model by fitting.

[0091] Furthermore, if Fig.10 As shown, based on the above-mentioned radar multiple parameter model generation method, the present invention also provides a radar multiple parameter model generation system, wherein the radar multiple parameter model generation system includes:

[0092] The gain model generation module 101 is used to obtain the target signal amplitude corresponding to multiple transmission parameters of the target radar and the signal source under the first preset condition based on the target test environment, and establish the gain model of the amplifier according to the thin plate spline interpolation;

[0093] The transmission model output module 102 is used to obtain the target signal amplitudes corresponding to multiple intermediate frequency signal frequencies of the target radar under the second preset condition based on the target test environment, and establish the transmission model of the filter according to the thin plate spline interpolation;

[0094] The noise model generating module 103 is used to obtain the signal corresponding to the fixed frequency of the target radar under the third preset condition based on the empty darkroom environment, and establish the noise model according to the mixed Gaussian model;

[0095] The result output module 104 is used to obtain and output a model collection according to the gain model of the amplifier, the transmission model of the filter and the noise model.

[0096] Furthermore, if Fig.11 As shown, based on the above-mentioned radar multiple parameter model generation method and system, the present invention also provides a terminal accordingly, and the terminal includes a processor 10, a memory 20 and a display 30. Fig.11 Only some components of the terminal are shown, but it should be understood that it is not required to implement all of the components shown, and more or fewer components may be implemented instead.

[0097] In some embodiments, the memory 20 may be an internal storage unit of the terminal, such as a hard disk or memory of the terminal. In other embodiments, the memory 20 may also be an external storage device of the terminal, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the terminal. Further, the memory 20 may also include both an internal storage unit of the terminal and an external storage device. The memory 20 is used to store application software and various types of data installed in the terminal, such as the program code of the installation terminal. The memory 20 may also be used to temporarily store data that has been output or is to be output. In one embodiment, a model generation program 40 of multiple parameters of a radar is stored on the memory 20, and the model generation program 40 of multiple parameters of the radar can be executed by the processor 10, thereby realizing the model generation method of multiple parameters of the radar in the present invention.

[0098] In some embodiments, the processor 10 may be a central processing unit (CPU), a microprocessor or other data processing chip, used to run the program code or process data stored in the memory 20, such as executing a model generation method for multiple parameters of the radar.

[0099] In some embodiments, the display 30 may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch device, etc. The display 30 is used to display information on the terminal and to display a visual user interface. The components 10-30 of the terminal communicate with each other via a system bus.

[0100] In one embodiment, when the processor 10 executes the model generation program 40 for multiple parameters of the radar in the memory 20 , the steps of the above method for generating models for multiple parameters of the radar are implemented.

[0101] The present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a model generation program for multiple parameters of a radar, and when the model generation program for multiple parameters of the radar is executed by a processor, the following steps are implemented:

[0102] Based on the target test environment, the target signal amplitudes corresponding to various emission parameters of the target radar and the signal source under the first preset condition are obtained, and a gain model of the amplifier is established according to thin plate spline interpolation;

[0103] Based on the target test environment, the target signal amplitudes corresponding to multiple intermediate frequency signal frequencies of the target radar under the second preset condition are obtained, and a transmission model of the filter is established according to thin plate spline interpolation;

[0104] Based on an empty darkroom environment, a signal corresponding to a fixed frequency of the target radar under a third preset condition is obtained, and a noise model is established according to a mixed Gaussian model;

[0105] According to the gain model of the amplifier, the transmission model of the filter and the noise model, a model collection is obtained and output.

[0106] Wherein, obtaining the target signal amplitude corresponding to a plurality of emission parameters of the target radar and the signal source under the first preset condition based on the target test environment specifically includes:

[0107] Based on the target test environment, a horn antenna is set to face the target radar, and other parameters of the target radar are set to be fixed;

[0108] Obtain the target radar's received target signal amplitude corresponding to the target radar's multiple transmitted signal frequencies and the signal source transmitting a single-frequency continuous wave with a fixed frequency difference with the transmitted signal.

[0109] The step of establishing the amplifier gain model based on thin plate spline interpolation specifically includes:

[0110] Taking multiple transmission signal frequencies and corresponding transmission amplitudes as independent variables, taking the corresponding target signal amplitude as dependent variable, and calculating the relationship between the corresponding independent variables and dependent variables according to thin plate spline interpolation, multiple gain functions are obtained;

[0111] All gain functions are fitted to obtain a gain model of the amplifier.

[0112] Wherein, obtaining the target signal amplitudes corresponding to multiple frequencies of the target radar under the second preset condition based on the target test environment specifically includes:

[0113] Based on the target test environment, a horn antenna is set to face the target radar, and the output power and frequency of the signal source are set to be fixed;

[0114] Obtain the target signal amplitude output by the target radar at different intermediate frequency signal frequencies.

[0115] The step of establishing a transmission model of a filter based on thin plate spline interpolation specifically includes:

[0116] Taking the intermediate frequency signal frequency as the independent variable and the corresponding target signal amplitude as the dependent variable, the relationship between the independent variable and the dependent variable is calculated according to the thin plate spline interpolation to obtain the corresponding multiple transfer functions;

[0117] All transfer functions are fitted to obtain the transmission model of the filter.

[0118] Wherein, based on the empty darkroom environment, obtaining the signal corresponding to the fixed frequency of the target radar under the third preset condition specifically includes:

[0119] Based on the empty darkroom environment, setting the frequency of the target radar to be fixed;

[0120] Get the signal output by the target radar.

[0121] The step of establishing a noise model according to a mixed Gaussian model specifically includes:

[0122] All signals output by the target radar are filtered to remove the influence of the filter and obtain multiple noise data;

[0123] All the noise data are fitted with a mixed Gaussian model to obtain the noise model.

[0124] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or terminal including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or terminal. In the absence of further restrictions, an element defined by the sentence "includes a ..." does not exclude the existence of other identical elements in the process, method, article or terminal including the element.

[0125] Of course, those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing related hardware (such as a processor, a controller, etc.) through a computer program, and the program can be stored in a computer-readable storage medium that can be read by a computer, and the program can include the processes of the above-mentioned method embodiments when executed. The computer-readable storage medium can be a memory, a disk, an optical disk, etc.

[0126] It should be understood that the application of the present invention is not limited to the above examples. For ordinary technicians in this field, improvements or changes can be made based on the above description. All these improvements and changes should fall within the scope of protection of the claims attached to the present invention.

Claims

1. A method for generating a model of multiple parameters of a radar, characterized in that: The model generation method of the multiple parameters of the radar includes: Based on the target test environment, the target signal amplitudes corresponding to various emission parameters of the target radar and the signal source under the first preset condition are obtained, and a gain model of the amplifier is established according to thin plate spline interpolation; Based on the target test environment, the target signal amplitudes corresponding to multiple intermediate frequency signal frequencies of the target radar under the second preset condition are obtained, and a transmission model of the filter is established according to thin plate spline interpolation; Based on an empty darkroom environment, a signal corresponding to a fixed frequency of the target radar under a third preset condition is obtained, and a noise model is established according to a mixed Gaussian model; According to the gain model of the amplifier, the transmission model of the filter and the noise model, a model collection is obtained and output.

2. The method for generating a model of multiple parameters of a radar according to claim 1, characterized in that: The step of obtaining target signal amplitudes corresponding to a plurality of emission parameters of the target radar and the signal source under the first preset condition based on the target test environment specifically includes: Based on the target test environment, a horn antenna is set to face the target radar, and other parameters of the target radar are set to be fixed; Obtain the target radar's received target signal amplitude when the target radar transmits multiple signal frequencies and the signal source transmits a single-frequency continuous wave with a fixed frequency difference with the transmitted signal.

3. The method for generating a model of multiple parameters of a radar according to claim 2, characterized in that: The step of establishing the amplifier gain model based on thin plate spline interpolation specifically includes: Taking multiple transmission signal frequencies and corresponding transmission amplitudes as independent variables, taking the corresponding target signal amplitude as dependent variable, calculating the relationship between the corresponding independent variable and the dependent variable according to thin plate spline interpolation, and obtaining multiple gain functions; All gain functions are fitted to obtain a gain model of the amplifier.

4. The method for generating a model of multiple parameters of a radar according to claim 1, characterized in that: The obtaining, based on the target test environment, target signal amplitudes corresponding to multiple frequencies of the target radar under the second preset condition specifically includes: Based on the target test environment, a horn antenna is set to face the target radar, and the output power and frequency of the signal source are set to be fixed; Obtain the target signal amplitude output by the target radar at different intermediate frequency signal frequencies.

5. The method for generating a model of multiple parameters of a radar according to claim 1, characterized in that: The transmission model of the filter is established according to the thin plate spline interpolation, specifically comprising: Taking the intermediate frequency signal frequency as the independent variable and the corresponding target signal amplitude as the dependent variable, the relationship between the independent variable and the dependent variable is calculated according to the thin plate spline interpolation to obtain the corresponding multiple transfer functions; All transfer functions are fitted to obtain the transmission model of the filter.

6. The method for generating a model of multiple parameters of a radar according to claim 1, characterized in that: The step of obtaining a signal corresponding to a fixed frequency of the target radar under a third preset condition based on an empty darkroom environment specifically includes: Based on the empty darkroom environment, setting the frequency of the target radar to be fixed; Get the signal output by the target radar.

7. The method for generating a model of multiple parameters of a radar according to claim 5, characterized in that: The noise model is established according to the mixed Gaussian model, specifically comprising: All signals output by the target radar are filtered to remove the influence of the filter and obtain multiple noise data; All the noise data are fitted with a mixed Gaussian model to obtain the noise model.

8. A radar multiple parameter model generation system, characterized in that: The model generation system of various parameters of the radar includes: A gain model generation module is used to obtain target signal amplitudes corresponding to multiple emission parameters of the target radar and the signal source under the first preset condition based on the target test environment, and establish a gain model of the amplifier according to thin plate spline interpolation; A transmission model output module, used to obtain target signal amplitudes corresponding to multiple intermediate frequency signal frequencies of the target radar under a second preset condition based on the target test environment, and establish a transmission model of the filter according to thin plate spline interpolation; A noise model generation module is used to obtain a signal corresponding to a fixed frequency of the target radar under a third preset condition based on an empty darkroom environment, and establish a noise model according to a mixed Gaussian model; The result output module is used to obtain and output a model collection according to the gain model of the amplifier, the transmission model of the filter and the noise model.

9. A terminal, characterized in that: The terminal includes: a memory, a processor, and a model generation program for multiple parameters of the radar stored in the memory and executable on the processor. When the model generation program for multiple parameters of the radar is executed by the processor, the steps of the model generation method for multiple parameters of the radar as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a model generation program for multiple parameters of a radar, and when the model generation program for multiple parameters of a radar is executed by a processor, the steps of the model generation method for multiple parameters of a radar are implemented as described in any one of claims 1-7.

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