Clutter internal motion opportunity airborne radar clutter signal fast simulation method and device

Abstract

The present application relates to the technical field of signal processing, and provides a clutter internal motion airborne radar clutter signal fast simulation method and device. According to the radar system parameters and environmental parameters when the clutter internal motion exists, the clutter power spectrum density function is constructed; the amplitude of each frequency point of the clutter power spectrum density function is calculated; the echo signal of the clutter block corresponding to a single space domain channel when the clutter internal motion exists is constructed; the inverse Fourier transform of the clutter power spectrum density function is carried out, and the time domain correlation function is obtained; the time domain error covariance matrix is obtained by using the time domain correlation function; and the time domain covariance matrix is obtained according to the time domain error covariance matrix and the echo signal. Wherein, the present application simulates the airborne radar clutter signal fast when the clutter internal motion exists, and solves the problem that the simulation echo data is low in fidelity due to the fact that the internal motion parameters between different clutter blocks are usually unknown in real time and accurately.

Description

Technical Field

[0001] This invention relates to the field of signal processing technology, and in particular to a method and apparatus for rapid simulation of onboard radar clutter signals during internal clutter motion. Background Technology

[0002] Compared to ground-based radar, airborne radar platforms are in motion. The clutter spectrum is shifted due to the relative motion between the platform and the ground, causing spectral broadening and introducing spatiotemporal coupling characteristics. In actual clutter environments, the movement of vegetation and trees due to wind causes the echo signals of individual clutter cells to decorrelate between pulses, thus altering the clutter covariance matrix. This inter-pulse clutter motion is also known as internal clutter motion (ICM), which increases the degrees of freedom of the clutter and broadens the clutter spectrum in the frequency domain.

[0003] In existing technologies, airborne radar clutter signal simulation methods for situations involving internal clutter motion typically assume that the internal clutter motion is uniform in the azimuth direction (i.e., that the internal clutter motion is independent of the clutter block in the azimuth direction) and does not change with distance. These simulation methods usually assume that the spectrum of the internal clutter motion follows a Gaussian distribution and that the environmental parameters of each clutter block are identical. However, in practical engineering, the internal motion parameters between different clutter blocks are usually not known accurately in real time. Therefore, the simulation echo data obtained based on this method has low fidelity and cannot meet the requirements for rapid simulation of airborne radar clutter signals.

[0004] Therefore, overcoming the shortcomings of the existing technology is an urgent problem to be solved in this technical field. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to provide a method and device for rapid simulation of airborne radar clutter signals when there is internal clutter movement. The purpose is to rapidly simulate airborne radar clutter signals when there is internal clutter movement, improve the realism of simulated echo data when there is internal clutter movement, and solve the problem of low realism of simulated echo data caused by the fact that the internal motion parameters between different clutter blocks are usually not known in real time and accurately.

[0006] The present invention adopts the following technical solution: In a first aspect, the present invention provides a method for rapid simulation of onboard radar clutter signals during internal clutter motion, comprising: Based on the radar system parameters and environmental parameters when clutter is moving inside, a clutter power spectral density function is constructed. Calculate the amplitude of the clutter power spectral density function at each frequency point; construct the echo signal of the clutter block corresponding to a single spatial channel when there is internal clutter motion; Perform an inverse Fourier transform on the clutter power spectral density function to obtain a time-domain correlation function; use the time-domain correlation function to obtain the time-domain error covariance matrix; The time-domain covariance matrix is ​​obtained based on the time-domain error covariance matrix and the echo signal.

[0007] Furthermore, the clutter power spectral density function includes Gaussian and exponential functions; the radar system parameters include the wavelength, angular frequency, carrier frequency, and velocity-related parameters of the airborne radar; and the environmental parameters include the internal velocity of the clutter. The construction of the clutter power spectral density function based on radar system parameters and environmental parameters when clutter internal motion exists includes: The Gaussian spectral bandwidth is determined based on the ratio of the internal velocity of the clutter to the wavelength; the Gaussian type function is determined based on the angular frequency and the Gaussian spectral bandwidth. An exponential function is generated based on the relationship between the carrier frequency and the internal velocity of the clutter, the Gaussian spectral bandwidth, and the velocity-related parameters.

[0008] Furthermore, the expression for the Gaussian function is: ; Where, angular frequency ω= , Indicates the pulse repetition period; The signal frequency; The Gaussian spectral bandwidth is expressed as follows: ,in, This indicates the velocity of the internal motion of the clutter. Indicates the wavelength; The expression relating the carrier frequency to the internal velocity of the clutter is: ; in, , The velocity of the internal motion of the clutter. The carrier frequency; The expression for the exponential function is: ; in, Represents the impact function; This refers to the speed-related parameters.

[0009] Further, the calculation of the amplitude of the clutter power spectral density function at each frequency point; and the construction of the echo signal of the clutter block corresponding to a single spatial channel when clutter internal motion exists, include: The frequencies of multiple points are sampled at intervals on both sides of the center of the power spectrum; the amplitude expression of each frequency point is determined according to the Gaussian function and the exponential function, respectively. According to the amplitude expression, the echo signal of the i-th clutter block corresponding to a single spatial channel with internal clutter motion is generated.

[0010] Furthermore, the amplitude expression is: ; in, This represents the frequency of each point. This represents the Gaussian function or the exponential function. The frequency sampling interval; The expression for the echo signal is: ; in, , Indicates the first The fuzzy distance is the first The time-domain steering vector corresponding to each clutter block Indicates the first The fuzzy distance is the first The amplitude expression corresponding to each clutter block In the case where there is no internal motion of clutter, the first The fuzzy distance is the first The echo signal of a clutter block, This represents the Hadamard product operation of matrices. It represents the imaginary unit.

[0011] Further, the inverse Fourier transform of the clutter power spectral density function yields a time-domain correlation function; using the time-domain correlation function, the time-domain error covariance matrix is ​​obtained, including: Perform an inverse Fourier transform on the Gaussian function to obtain a first correlation function, and then obtain a first covariance matrix according to the first correlation function; The inverse Fourier transform of the exponential function is performed to obtain the second correlation function, and the second covariance matrix is ​​obtained according to the second correlation function.

[0012] Furthermore, the expression for the first covariance matrix is: ; Among them, the number of coherently processed pulses of the airborne radar is K. and They represent any two pulses out of K pulses. This indicates the velocity of the internal motion of the clutter. Indicates the wavelength. Indicates the pulse repetition period; The expression for the second covariance matrix is: ; Where r represents the expression between the carrier frequency and the internal velocity of clutter. This refers to the speed-related parameters.

[0013] Furthermore, the expression for the time-domain covariance matrix is: ; in, This refers to the echo signal. The first corresponding to the internal motion of clutter The fuzzy distance is the first The echo signal of a clutter block, Represents the mathematical expectation. Indicates the first The fuzzy distance is the first The time-domain error covariance matrix of a clutter block caused by the internal motion of the clutter. The first corresponding to the internal motion of clutter The fuzzy distance is the first The time-domain error vector of each clutter block, Indicates the first The fuzzy distance is the first The complex amplitude of a clutter block Indicates the first The fuzzy distance is the first The time-domain steering vector of each clutter block, This represents the number of individual range gate clutter blocks, with the number of ambiguities being... .

[0014] Secondly, the present invention also provides a device for rapid simulation of onboard radar clutter signals during internal clutter motion, comprising: At least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the processor for performing the rapid simulation method for onboard radar clutter signals during internal clutter motion as described in the first aspect.

[0015] Thirdly, the present invention also provides a non-volatile computer storage medium storing computer-executable instructions, which are executed by one or more processors to perform the rapid simulation method for onboard radar clutter signals during internal clutter motion as described in the first aspect.

[0016] Fourthly, a computer program product containing instructions is provided, which, when executed on a computer or processor, causes the computer or processor to perform a rapid simulation method for onboard radar clutter signals during internal clutter motion, as described in the first aspect.

[0017] Fifthly, the present invention also provides a rapid simulation system for onboard radar clutter signals during internal clutter motion, including the rapid simulation device for onboard radar clutter signals during internal clutter motion as described in the second aspect, and using the rapid simulation method for onboard radar clutter signals during internal clutter motion as described in the first aspect to complete the interaction of the rapid simulation device for onboard radar clutter signals during internal clutter motion as described in the second aspect.

[0018] Unlike existing technologies, the present invention has at least the following beneficial effects: This invention uses the environmental parameters of each clutter block and the radar system parameters as references to construct a clutter power spectral density function. Then, when there is internal clutter motion, it constructs a corresponding time-domain correlation function to construct the echo signal of a clutter block corresponding to a single spatial channel under the condition of internal clutter motion. This yields the corresponding clutter time-domain covariance matrix under the condition of internal clutter motion, enabling rapid simulation of airborne radar clutter signals. It does not require the assumption that the spectrum of internal clutter motion follows a Gaussian distribution and that the environmental parameters of each clutter block are the same. Therefore, even when the internal motion parameters between different clutter blocks cannot be accurately known in real time, the realism of the generated simulation echo data can still be ensured. Attached Figure Description

[0019] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments of the present invention will be briefly described below. Obviously, the drawings described below are merely some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0020] Figure 1 This is a flowchart illustrating a method for rapid simulation of onboard radar clutter signals during internal clutter motion, as provided in an embodiment of the present invention. Figure 2 This is a schematic diagram of the overall process of a method for rapid simulation of onboard radar clutter signals during internal clutter motion, provided in an embodiment of the present invention. Figure 3 This is a structural block diagram of a method for rapid simulation of onboard radar clutter signals during internal clutter motion, provided in an embodiment of the present invention. Figure 4 This is a flowchart illustrating step 10 provided in an embodiment of the present invention; Figure 5 This is a flowchart illustrating step 20 provided in an embodiment of the present invention; Figure 6 This is a flowchart illustrating step 30 provided in an embodiment of the present invention; Figure 7 This is a schematic diagram of the architecture of a rapid simulation device for onboard radar clutter signals during internal clutter motion, provided in an embodiment of the present invention. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0022] Unless the context otherwise requires, throughout the specification and claims, the term "comprising" is interpreted as openly inclusive, meaning "including, but not limited to." In the description of the specification, terms such as "one embodiment," "some embodiments," "exemplary embodiment," "example," "specific example," or "some examples" are intended to indicate that a particular feature, structure, material, or characteristic associated with that embodiment or example is included in at least one embodiment or example of this disclosure. The illustrative representations of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics mentioned may be included in any suitable manner in any one or more embodiments or examples; that is, although they may be incorporated into embodiments or examples using the above terms for reasons such as order and position, it does not limit them to be incorporated in combination by a single embodiment or example.

[0023] In the description of this invention, it should be understood that the terms "center", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this disclosure and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this disclosure.

[0024] In the description of this invention, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined with "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of embodiments of this disclosure, unless otherwise stated, "a plurality of" means two or more. Furthermore, for example, the description may use the prefix "A" or "B" to describe the same type of nouns as two independent entities. In this case, the corresponding features defined with "A" and "B" are used only to distinguish between similar entities and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features.

[0025] In describing some embodiments, the terms "coupled," "coupled," and "connected," and their derivative expressions, may be used. For example, the term "connected" may be used in describing some embodiments to indicate that two or more components have direct physical or electrical contact with each other. Similarly, the term "coupled" may be used in describing some embodiments to indicate that two or more components have direct physical or electrical contact. However, the terms "connected" or "coupled" may also refer to two or more components that do not have direct contact with each other but still cooperate or interact with each other, such as "optical coupling," "wireless connection," etc. The embodiments disclosed herein are not necessarily limited to the scope of this invention.

[0026] In the description of this invention, the expression “A and / or B” (where A and B are used to formally represent specific features) will be used. The corresponding expression includes the following three combinations: only A, only B, and a combination of A and B.

[0027] As used in this invention, “about,” “approximately,” or “approximately” includes the stated value and the average value within an acceptable range of deviation from a particular value, wherein the acceptable range of deviation is determined by a person skilled in the art taking into account the measurement under discussion and the error associated with the measurement of the particular quantity (i.e., the limitations of the measurement system).

[0028] Furthermore, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0029] Example 1: To solve the above problems, such as Figure 1 As shown, this embodiment of the invention provides a method for rapid simulation of onboard radar clutter signals during internal clutter motion, including: Step 10: Construct the clutter power spectral density function based on the radar system parameters and environmental parameters when clutter is present and there is internal motion.

[0030] The power spectral density (PSD) reflects the power distribution intensity of a signal within a specific frequency range. Its unit is watts per hertz, representing the average power per unit bandwidth.

[0031] Radar system parameters refer to the technical specifications that need to be defined during the radar hardware or design process.

[0032] Environmental parameters are parameters that describe the movement characteristics of the external environment (e.g., vegetation, ocean waves).

[0033] Since it is usually impossible to obtain the internal motion parameters between different clutter blocks in real time in actual engineering, this embodiment of the invention pre-constructs a clutter power spectral density function so that when there is internal clutter motion, the airborne radar clutter signal can be quickly simulated based on the clutter power spectral density function; the radar system parameters and environmental parameters used to construct the clutter power spectral density function will be explained below.

[0034] like Figure 2 As shown, in this embodiment of the invention, a clutter power spectral density function is preset, and an echo signal is constructed when there is internal clutter motion using this clutter power spectral density function. A time-domain correlation function is also constructed to construct a time-domain covariance matrix when there is internal clutter motion. The airborne radar clutter signal is simulated using this time-domain covariance matrix.

[0035] Specifically, such as Figure 3 As shown, the clutter power spectral density function is first constructed based on the radar system parameters and environmental parameters when clutter is moving inside.

[0036] Step 20: Calculate the amplitude of the clutter power spectral density function at each frequency point; construct the echo signal of the clutter block corresponding to a single spatial channel when there is internal clutter motion.

[0037] In this context, the amplitude of the power spectral density function at each frequency point represents the average power within a unit bandwidth around that frequency. Power spectral density (PSD) describes the distribution of signal power in the frequency domain. The amplitude value at each frequency point represents the average power within a unit hertz bandwidth around that frequency. For example, if the PSD value at a frequency *f* is S(f) watts / hertz, then the power within a 1 hertz bandwidth around that frequency is S(f) watts. The amplitude of the PSD directly reflects the energy strength of the signal at different frequencies. The higher the amplitude of high-frequency components (such as noise) or specific frequency components (such as a sine wave), the greater the contribution of that frequency to the total power.

[0038] like Figure 3As shown, the amplitude at each frequency point is calculated using the constructed clutter power spectral density function, and the echo signal of the clutter block corresponding to a single spatial channel under the condition of internal clutter motion is constructed.

[0039] Step 30: Perform an inverse Fourier transform on the clutter power spectral density function to obtain the time-domain correlation function; use the time-domain correlation function to obtain the time-domain error covariance matrix.

[0040] like Figure 3 As shown, the inverse Fourier transform of the constructed clutter power spectral density function is then used to obtain the corresponding time-domain correlation function, and the time-domain error covariance matrix is ​​obtained according to the time-domain correlation function.

[0041] Step 40: Obtain the time-domain covariance matrix based on the time-domain error covariance matrix and the echo signal.

[0042] like Figure 3 As shown, the time-domain error covariance matrix obtained in step 30 and the echo signal of the clutter block corresponding to a single spatial channel when there is clutter internal motion constructed in step 20 are used to obtain the corresponding clutter time-domain covariance matrix.

[0043] This invention uses the environmental parameters of each clutter block and the radar system parameters as references to construct a clutter power spectral density function. Then, when there is internal clutter motion, it constructs a corresponding time-domain correlation function to construct the echo signal of a clutter block corresponding to a single spatial channel under the condition of internal clutter motion. This yields the corresponding clutter time-domain covariance matrix under the condition of internal clutter motion, enabling rapid simulation of airborne radar clutter signals. It does not require the assumption that the spectrum of internal clutter motion follows a Gaussian distribution and that the environmental parameters of each clutter block are the same. Therefore, even when the internal motion parameters between different clutter blocks cannot be accurately known in real time, the realism of the generated simulation echo data can still be ensured.

[0044] The following is a detailed description of the fast simulation method for onboard radar clutter signals during internal clutter motion according to an embodiment of the present invention: The factors that significantly reduce the realism of simulated echo data are, in addition to the fact that existing technical methods are based on the assumption that the spectrum of clutter internal motion follows a Gaussian distribution and that the environmental parameters of each clutter block are the same, that the Gaussian clutter spectrum cannot satisfy all situations where there is clutter internal motion.

[0045] Mathematical models describing the internal motion of clutter typically come in two forms: Gaussian and exponential. For ease of description, we will use "Gaussian function" to refer to "Gaussian clutter power spectral density function" and "exponential function" to refer to "exponential clutter power spectral density function".

[0046] To further improve the realism of the simulated echo data and meet the rapid simulation requirements of airborne radar clutter signals when clutter internal motion exists, in this embodiment of the invention, the clutter power spectral density function includes a Gaussian function and an exponential function; the radar system parameters include the wavelength, angular frequency, carrier frequency, and velocity-related parameters of the airborne radar; and the environmental parameters include the internal motion velocity of the clutter; wherein, the internal motion velocity of the clutter is an environmental condition that the radar needs to adapt to.

[0047] To illustrate the process of constructing the clutter power spectral density function, such as... Figure 4 As shown, step 10 includes: Step 101: Determine the Gaussian spectral bandwidth based on the ratio of the internal motion velocity of the clutter to the wavelength; determine the Gaussian type function based on the angular frequency and the Gaussian spectral bandwidth.

[0048] In one embodiment, the expression for the Gaussian function is: ; Where, angular frequency ω= , Indicates the pulse repetition period; The signal frequency is ω; the angular frequency ω is the mathematical expression of the carrier frequency, ω=2πf, and the carrier frequency is a core controllable parameter in radar design. The Gaussian spectral bandwidth is expressed as follows: ,in, This indicates the velocity of motion within the clutter. This indicates the wavelength.

[0049] Step 102: Generate an exponential function based on the relationship between the carrier frequency and the internal velocity of the clutter, the Gaussian spectral bandwidth, and the velocity-related parameters.

[0050] In one embodiment, the expression between the carrier frequency and the internal velocity of the clutter is: ;in, That is, the following relationship exists: ; in, The velocity of the internal motion of the clutter is expressed in miles per hour. The carrier frequency, in megahertz, affects the Doppler frequency shift described by the impulse function, and thus affects the accuracy of velocity estimation. A function representing the carrier frequency and the velocity of motion within clutter.

[0051] The expression for the exponential function is: ; in, The impulse function is represented by the transmitted signal, which can be expressed as a sequence of impulse functions. The velocity-related parameters, i.e., parameters related to the internal motion velocity of clutter, typically have the following relationship with wind speed: when the wind speed is between 0.4 m / s and 3.1 m / s. =12; when the wind speed is 3.1 m / s to 6.7 m / s =8; when the wind speed is 6.7 m / s to 13.3 m / s =5.7; when the wind speed is 13.3 m / s to 22.2 m / s =4.3.

[0052] To explain the process of obtaining the echo signal, such as Figure 5 As shown, step 20 includes: Step 201: Sample the frequencies of multiple points at intervals on both sides of the center of the power spectrum; determine the amplitude expression for each frequency point according to the Gaussian function and the exponential function respectively.

[0053] In one embodiment, M points are sampled at frequency sampling intervals of Δf on both sides of the power spectrum center. For each frequency point, the amplitude expression is: ; in, This represents the frequency of each point. This represents the Gaussian function or the exponential function. The frequency sampling interval.

[0054] Step 202: Generate the echo signal of the i-th clutter block corresponding to a single spatial channel under the condition of internal clutter motion, according to the amplitude expression.

[0055] In one embodiment, the echo signal is expressed as: ; in, , Indicates the first The fuzzy distance is the first The time-domain steering vector corresponding to each clutter block Indicates the first The fuzzy distance is the first The amplitude expression corresponding to each clutter block In the case where there is no internal motion of clutter, the first The fuzzy distance is the first The echo signal of a clutter block, This represents the Hadamard product operation. This represents the imaginary unit. It should be noted that the amplitude expression generated using either Gaussian or exponential functions is applicable to the expression for this echo signal.

[0056] To illustrate the process of obtaining the time-domain error covariance matrix, as follows: Figure 6 As shown, step 30 includes: Step 301: Perform an inverse Fourier transform on the Gaussian function to obtain a first correlation function, and then obtain a first covariance matrix according to the first correlation function.

[0057] The first correlation function is the time-domain error covariance matrix corresponding to the Gaussian function.

[0058] In one embodiment, the expression for the first correlation function is: Based on this, the expression for the first covariance matrix is: ; Among them, the number of coherently processed pulses of the airborne radar is K. and They represent any two pulses out of K pulses. This indicates the velocity of the internal motion of the clutter. Indicates the wavelength. This indicates the pulse repetition period.

[0059] Step 302: Perform an inverse Fourier transform on the exponential function to obtain a second correlation function, and then obtain the second covariance matrix according to the second correlation function.

[0060] In one embodiment, the expression for the second covariance matrix is: ; in, This represents the expression relating the carrier frequency to the velocity of motion within the clutter. This refers to the speed-related parameters.

[0061] In one embodiment, when the number of fuzzing operations is... When clutter is present and there is internal movement within the clutter, the expression for the clutter signal in a single airspace channel of the onboard radar is: ; in, The first corresponding to the internal motion of clutter The fuzzy distance is the first The echo signal of each clutter block. Based on this, the expression for the time-domain covariance matrix is: ; in, This refers to the echo signal. The first corresponding to the internal motion of clutter The fuzzy distance is the first The echo signal of a clutter block, Represents the mathematical expectation. Indicates the first The fuzzy distance is the first The time-domain error covariance matrix of a clutter block caused by the internal motion of the clutter. The first corresponding to the internal motion of clutter The fuzzy distance is the first The time-domain error vector of each clutter block, Indicates the first The fuzzy distance is the first The complex amplitude of a clutter block Indicates the first The fuzzy distance is the first The time-domain steering vector of each clutter block, This represents the number of individual range gate clutter blocks, with the number of ambiguities being... .

[0062] Example 2: like Figure 7 The diagram shown is an architectural schematic of a rapid simulation device for onboard radar clutter signals during internal clutter motion according to an embodiment of the present invention. This rapid simulation device for onboard radar clutter signals during internal clutter motion includes one or more processors 21 and a memory 22. Figure 7 Take a processor 21 as an example.

[0063] Processor 21 and memory 22 can be connected via a bus or other means. Figure 7 Taking the example of a connection between China and Israel via a bus.

[0064] The memory 22, as a non-volatile computer-readable storage medium, can be used to store non-volatile software programs and non-volatile computer-executable programs, such as the fast simulation method for onboard radar clutter signals during internal clutter motion in this embodiment. The processor 21 executes the fast simulation method for onboard radar clutter signals during internal clutter motion by running the non-volatile software programs and instructions stored in the memory 22.

[0065] Memory 22 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 non-volatile solid-state storage device. In some embodiments, memory 22 may optionally include memory remotely located relative to processor 21, which can be connected to processor 21 via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0066] The program instructions / modules are stored in the memory 22. When executed by one or more processors 21, they perform the fast simulation method for onboard radar clutter signals when there is internal clutter movement in the clutter in the above embodiments. For example, they perform each step of the fast simulation method for onboard radar clutter signals when there is internal clutter movement in the clutter in the embodiments of the present invention described above.

[0067] This invention also provides a non-volatile computer storage medium storing computer-executable instructions that are executed by one or more processors, for example... Figure 7 A processor 21 enables one or more of the processors to execute the fast simulation method for onboard radar clutter signals during internal clutter motion in specific embodiments of the present invention. For example, it can execute the various steps of the fast simulation method for onboard radar clutter signals during internal clutter motion in embodiments of the present invention described above; it can also implement... Figure 7 The various modules and units shown; or the fast simulation method for onboard radar clutter signals when there is internal clutter motion in the specific embodiments of the present invention, for example, executing the various steps of the fast simulation method for onboard radar clutter signals when there is internal clutter motion in the embodiments of the present invention described above; can also be implemented Figure 7 The various modules and units mentioned above.

[0068] It is worth noting that the information interaction and execution process between the modules and units in the above-mentioned device and system are based on the same concept as the processing method embodiment of the present invention. For details, please refer to the description in the method embodiment of the present invention, and will not be repeated here.

[0069] Those skilled in the art will understand that all or part of the steps in the various methods of the embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, which may include: read-only memory (ROM), random access memory (RAM), magnetic disk or optical disk, etc.

[0070] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for rapid simulation of onboard radar clutter signals during internal clutter motion, characterized in that, include: Based on the radar system parameters and environmental parameters when clutter is moving inside, a clutter power spectral density function is constructed. Calculate the amplitude of the clutter power spectral density function at each frequency point; construct the echo signal of the clutter block corresponding to a single spatial channel when there is internal clutter motion; Perform an inverse Fourier transform on the clutter power spectral density function to obtain a time-domain correlation function; use the time-domain correlation function to obtain the time-domain error covariance matrix; The time-domain covariance matrix is ​​obtained based on the time-domain error covariance matrix and the echo signal.

2. The method for rapid simulation of onboard radar clutter signals during internal clutter motion according to claim 1, characterized in that, The clutter power spectral density function includes Gaussian and exponential functions; the radar system parameters include the wavelength, angular frequency, carrier frequency, and velocity-related parameters of the airborne radar; the environmental parameters include the internal velocity of the clutter. The method includes: The Gaussian spectral bandwidth is determined based on the ratio of the internal velocity of the clutter to the wavelength; the Gaussian type function is determined based on the angular frequency and the Gaussian spectral bandwidth. An exponential function is generated based on the relationship between the carrier frequency and the internal velocity of the clutter, the Gaussian spectral bandwidth, and the velocity-related parameters.

3. The method for rapid simulation of onboard radar clutter signals during internal clutter motion according to claim 2, characterized in that, The expression for the Gaussian function is: ； Among them, angular frequency , Indicates the pulse repetition period; The signal frequency; The Gaussian spectral bandwidth is expressed as follows: ,in, This indicates the velocity of the internal motion of the clutter. Indicates the wavelength; The expression relating the carrier frequency to the internal velocity of the clutter is: ； in, , The velocity of the internal motion of the clutter. The carrier frequency; The expression for the exponential function is: ； in, Represents the impact function; This refers to the speed-related parameters.

4. The method for rapid simulation of onboard radar clutter signals during internal clutter motion according to claim 2, characterized in that, The calculation of the amplitude of the clutter power spectral density function at each frequency point; and the construction of the echo signal of the clutter block corresponding to a single spatial channel when there is internal clutter motion, include: The frequencies of multiple points are sampled at intervals on both sides of the center of the power spectrum; the amplitude expression of each frequency point is determined according to the Gaussian function and the exponential function, respectively. According to the amplitude expression, the echo signal of the i-th clutter block corresponding to a single spatial channel with internal clutter motion is generated.

5. The method for rapid simulation of onboard radar clutter signals during internal clutter motion according to claim 4, characterized in that, The amplitude expression is: ； in, This represents the frequency of each point. This represents the Gaussian function or the exponential function. The frequency sampling interval; The expression for the echo signal is: ； in, , Indicates the first The fuzzy distance is the first The time-domain steering vector corresponding to each clutter block Indicates the first The fuzzy distance is the first The amplitude expression corresponding to each clutter block In the case where there is no internal motion of clutter, the first The fuzzy distance is the first The echo signal of a clutter block, This represents the Hadamard product operation on matrices. It represents the imaginary unit.

6. The method for rapid simulation of onboard radar clutter signals during internal clutter motion according to claim 2, characterized in that, The inverse Fourier transform of the clutter power spectral density function is performed to obtain the time-domain correlation function; Using the aforementioned time-domain correlation function, the time-domain error covariance matrix is ​​obtained as follows: Perform an inverse Fourier transform on the Gaussian function to obtain a first correlation function, and then obtain a first covariance matrix according to the first correlation function; The inverse Fourier transform of the exponential function is performed to obtain the second correlation function, and the second covariance matrix is ​​obtained according to the second correlation function.

7. The method for rapid simulation of onboard radar clutter signals during internal clutter motion according to claim 6, characterized in that, The expression for the first covariance matrix is: ； Among them, the number of coherently processed pulses of the airborne radar is K. and They represent any two pulses out of K pulses. This indicates the velocity of the internal motion of the clutter. Indicates the wavelength. Indicates the pulse repetition period; The expression for the second covariance matrix is: ； Where r represents the expression between the carrier frequency and the internal velocity of clutter. This refers to the speed-related parameters.

8. The method for rapid simulation of onboard radar clutter signals during internal clutter motion according to claim 6, characterized in that, The expression for the time-domain covariance matrix is: ； in, This refers to the echo signal. The first corresponding to the internal motion of clutter The fuzzy distance is the first The echo signal of a clutter block, Represents the mathematical expectation. Indicates the first The fuzzy distance is the first The time-domain error covariance matrix of a clutter block caused by the internal motion of the clutter. The first corresponding to the internal motion of clutter The fuzzy distance is the first The time-domain error vector of each clutter block, Indicates the first The fuzzy distance is the first The complex amplitude of a clutter block Indicates the first The fuzzy distance is the first The time-domain steering vector of each clutter block, This represents the number of individual range gate clutter blocks, with the number of ambiguities being... .

9. A rapid simulation device for onboard radar clutter signals during internal clutter motion, characterized in that, The rapid simulation device for onboard radar clutter signals during internal clutter motion includes at least one processor and a memory, which are connected via a data bus. The memory stores instructions that can be executed by the at least one processor. After being executed by the processor, the instructions are used to implement the rapid simulation method for onboard radar clutter signals during internal clutter motion as described in any one of claims 1-8.

10. A non-volatile computer storage medium, characterized in that, The computer storage medium stores computer-executable instructions, which are executed by one or more processors to perform the rapid simulation method for onboard radar clutter signals during internal clutter motion as described in any one of claims 1-8.

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