Bistatic radar long-time coherent accumulation method for air maneuvering target

Abstract

The invention discloses a bistatic radar long-time coherent accumulation method for an air maneuvering target. The method comprises the following steps: determining the positions of a transmitting station and a receiving station; constructing a target echo signal model under the collaborative double-base detection configuration; performing pulse compression on the echo signal, performing Fourier transform along a distance dimension, performing flipping along a slow time dimension, and multiplying a frequency echo signal after pulse compression with a flipped signal; second-order Keystone correction is carried out in the range frequency domain, and inverse Fourier transform is carried out along the range frequency; performing acceleration estimation to obtain an estimated value of the acceleration; compensating the distance frequency domain echo signal after the second-order Keystone correction to obtain a frequency echo signal after acceleration compensation; and carrying out inverse Fourier transform of a distance dimension and Fourier transform of a slow time dimension to obtain a signal after long-time phase-coherent accumulation. According to the method, long-time coherent accumulation can be carried out on the air maneuvering target with third-order motion under the collaborative double-base detection configuration.

Description

Technical Field

[0001] The invention belongs to the technical field of aerial moving target detection, and in particular relates to a long-time coherent accumulation method for aerial maneuvering targets using a dual-base radar. Background Art

[0002] Bistatic radar utilizes the spatial flexibility of transmitting and receiving stations to effectively detect aerial targets. Coherent integration is a key technology in radar signal processing. By aligning the phases of multiple pulse echoes (coherently) and superimposing them, it significantly improves the signal-to-noise ratio of target echoes, enhancing the radar's ability to detect faint targets.

[0003] At present, the research on the coherent integration performance of bistatic radar mainly focuses on radars in stationary scenarios. The research on aerial maneuvering targets only considers the influence of velocity and acceleration. There is less research on the long-term coherent integration of aerial maneuvering targets. In addition, the traditional long-term coherent integration method has the problems of high computational complexity of multi-dimensional parameter search and performance degradation. Therefore, it is urgent to carry out research on the long-term coherent integration method of bistatic radar for aerial maneuvering targets. Summary of the Invention

[0004] The purpose of the present invention is to provide a long-term coherent integration method for a bistatic radar aerial maneuvering target, a computer device, a computer-readable storage medium and a computer program product, which can perform long-term coherent integration of an aerial maneuvering target with third-order motion in a collaborative bistatic detection configuration.

[0005] To achieve the above objectives, one aspect of the present invention provides a long-term coherent integration method for a bistatic radar targeting an aerial maneuvering target, comprising: Step S1: Determine the locations of the transmitting and receiving stations and convert them into the ECEF coordinate system; Step S2: constructing a target echo signal model in a cooperative bistatic detection configuration to achieve space-time-frequency synchronization between the transmitting station and the receiving station; Step S3: performing pulse compression on the echo signal, performing Fourier transform on the pulse compressed echo signal along the distance dimension to obtain a pulse compressed frequency echo signal, flipping the pulse compressed frequency echo signal along the slow time dimension to obtain a pulse compressed frequency echo time flipped signal, and multiplying the pulse compressed frequency echo signal by the pulse compressed frequency echo time flipped signal to obtain a slow time series scale transformed echo signal; Step S4: performing a second-order Keystone correction in the range frequency domain on the echo signal after the slow time series scale transformation, and performing an inverse Fourier transform along the range frequency on the range frequency domain echo signal after the second-order Keystone correction to obtain a time domain echo signal after the second-order Keystone correction; Step S5: performing acceleration estimation on the time domain echo signal after the second-order Keystone correction to obtain an estimated value of acceleration; Step S6: constructing an acceleration compensation factor based on the estimated value of acceleration, compensating the range frequency domain echo signal after the second-order Keystone correction, and obtaining an acceleration-compensated frequency echo signal; Step S7: performing inverse Fourier transform of the distance dimension and Fourier transform of the slow time dimension on the frequency echo signal after acceleration compensation to obtain a signal after long-term coherent accumulation.

[0006] Another aspect of the present invention provides a computer device, comprising a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the above method.

[0007] Another aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, which implements the steps of the above method when executed by a processor.

[0008] Yet another aspect of the present invention provides a computer program product, comprising a computer program, which implements the steps of the above method when executed by a processor.

[0009] The long-term coherent integration method, computer equipment, computer-readable storage medium and computer program product of a bistatic radar aerial maneuvering target according to the above aspects of the present invention can perform long-term coherent integration of aerial maneuvering targets with third-order motion in a collaborative bistatic detection configuration. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] In order to more clearly illustrate the technical solutions of the present invention, the following briefly introduces the drawings used in the description of the embodiments of the present invention. Obviously, the drawings described below are only some embodiments of the present invention. Those skilled in the art can also derive other drawings based on these drawings without inventive efforts. Figure 1 This is a flow chart of a bistatic radar long-term coherent integration method for an aerial maneuvering target according to an embodiment of the present invention; Figure 2 This is a schematic diagram of a simulation scenario of a satellite-aircraft collaborative dual-base detection test according to an embodiment of the present invention; Figure 3This is the coherent accumulation result diagram of the traditional method; Figure 4 This is a coherent accumulation result diagram of an embodiment of the present invention; Figure 5 It is a structural diagram of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0011] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0012] One embodiment of the present invention provides a long-term coherent integration method for a bistatic radar targeting an aerial maneuvering target, such as Figure 1 As shown, the method of the embodiment of the present invention includes steps S1 to S7.

[0013] Step S1: Determine the positions of the transmitting and receiving stations and convert them into the ECEF coordinate system.

[0014] Step S1 further includes steps S11 and S12.

[0015] Step S11: Determine the location coordinates of the transmitting station and convert them into the ECEF coordinate system Assume that the longitude, latitude and altitude coordinates of the transmitting station are , the transmitter station location can be converted to the ECEF coordinate system (Earth-Centered, Earth-Fixed) using the following formula:

[0016] in, is the Earth's eccentricity, Respectively represent the latitude, longitude and altitude information of the transmitting station, is the curvature radius of the transmitting station’s azimuth plane, is the equivalent radius of the Earth, usually set to 6378.137 km, then the transmitter station location Can be described as

[0017] Step S12: Determine the location coordinates of the receiving station and convert them to the ECEF coordinate system Assume that the longitude, latitude and altitude coordinates of the receiving station are , the receiving station position can be converted to the ECEF coordinate system. The conversion formula is as follows:

[0018] in, is the Earth's eccentricity, Respectively represent the latitude, longitude and altitude information of the receiving station, is the curvature radius of the receiving station’s y-axis plane, is the equivalent radius of the earth, usually set to 6378.137 km, then the receiving station location Can be described as

[0019] Step S2: Target echo signal model construction under cooperative bistatic detection configuration In an embodiment of the present invention, a bistatic radar forms a cooperative bistatic detection configuration. The cooperative bistatic detection configuration refers to a radar system configuration in which a transmitting station and a receiving station are located at different positions and achieve target detection through cooperative work.

[0020] Step S2 further includes steps S21 to S23.

[0021] Step S21: In the cooperative bistatic detection configuration, assuming that the transmitting station radar transmits a linear frequency modulation signal, the specific expression is as follows:

[0022] in .

[0023] in For distance fast time, is the carrier frequency of the radar signal, is the pulse width, is the modulation frequency of the signal.

[0024] The transmitted electromagnetic wave propagates through the dual-base configuration, and the received echo signal can be described as

[0025] in is the scattering coefficient of the target, represents the speed of light, Indicates the direction of slow time, Indicates the pulse repetition time (Pulse Repetition Time), Indicates the number of azimuth pulses, , is the sum of the instantaneous slant distances from the transmitting station to the moving target in the air and from the receiving station to the moving target in the air, express The distance from the transmitting station to the moving target in the air at any moment, express The distance between the receiving station and the moving target in the air at any moment.

[0026] Step S22: Constructing the motion model of aerial maneuvering targets under the satellite-aircraft collaborative dual-base detection configuration In the satellite-aircraft collaborative dual-base detection configuration, the instantaneous slant range of any point on the moving target in the air can be obtained as

[0027] in represents the sum of the initial slant distances from the target to the transmitting station and to the receiving station, Indicates the equivalent speed of the target relative to the transmitting station and the receiving station, represents the equivalent acceleration of the target relative to the transmitting station and the receiving station, represents the equivalent acceleration of the target relative to the transmitting station and the receiving station, then the target echo signal model at this time can be described as

[0028] Step S23: Achieve "space-time-frequency" synchronization between the transmitting station and the receiving station On the one hand, the beam pointing area of ​​the transmitting station and the beam pointing area of ​​the receiving station are in the same spatial position, and on the other hand, the carrier center frequency of the transmitting station is and the carrier center frequency of the receiving station Keep consistent, that is, satisfy the following constraints

[0029] in Indicates the center frequency of the system.

[0030] Step S3: performing pulse compression, slow time dimension flipping and multiplication on the echo signal.

[0031] Step S3 further includes steps S31 and S32.

[0032] Step S31: Constructing a range-frequency domain matched filter , the specific expression is

[0033] in represents the distance frequency, represents the distance bandwidth, represents the frequency modulation, and .

[0034] Convert the echo signal into the frequency domain, then the echo signal can be described as

[0035] Then the echo signal after pulse compression is

[0036] in , represents the sinc function, Indicates the frequency along the distance Fast inverse Fourier transform operation.

[0037] Step S32: Flip the range frequency domain echo data after pulse compression in the slow time dimension and multiply it with the range frequency domain echo data after pulse compression. Perform Fourier transform on the echo signal after pulse compression along the distance dimension to obtain the frequency echo signal after pulse compression , the specific formula is

[0038] in Indicates the frequency along the distance Fast Fourier transform operation.

[0039] The frequency echo signal after pulse compression is flipped along the slow time dimension to obtain the frequency echo time flip signal after pulse compression , the specific expression is as follows:

[0040] Frequency echo signal after pulse compression Frequency echo time-reversed signal after pulse compression Multiply them to get the echo signal after slow time series scale transformation

[0041]

[0042] Step S4: Perform second-order Keystone correction on the echo signal after the slow time series scale transformation.

[0043] The echo signal after the slow time series scale transformation , perform second-order Keystone correction in the distance frequency domain, and the transformation formula is as follows:

[0044] in represents the original slow timescale variable, represents the new slow timescale variable.

[0045] At this time, the range frequency domain echo signal after the second-order Keystone correction It can be expressed as

[0046] The range frequency domain echo signal after the second-order Keystone correction Perform inverse Fourier transform along the range frequency to obtain the time domain echo signal after second-order Keystone correction

[0047]

[0048] Step S5: performing acceleration estimation on the time domain echo signal after the second-order Keystone correction.

[0049] The time domain echo signal after second-order Keystone correction Perform the following correlation processing to obtain the slow time autocorrelation signal

[0050]

[0051] in Indicates slow time, represents the wavelength, represents the conjugation operation.

[0052] From the above formula, we can see that choosing The peak value of acceleration can be obtained The estimated value is

[0053] in for The frequency value corresponding to the peak point.

[0054] Step S6: Compensate for the high-order phase error caused by acceleration.

[0055] According to the acceleration estimated in the previous step, construct the acceleration compensation factor , and the range frequency domain echo signal after the second-order Keystone correction Compensate and obtain the frequency echo signal after acceleration compensation

[0056]

[0057] Because is the acceleration The estimated value of , then the frequency echo signal after acceleration compensation is It can be further simplified to

[0058] Step S7: performing coherent accumulation on the acceleration-compensated frequency echo signal.

[0059] Frequency echo signal after acceleration compensation Perform inverse Fourier transform of the distance dimension and Fourier transform of the slow time dimension to obtain the signal after long-term coherent accumulation

[0060]

[0061] in represents the inverse Fourier transform along the distance dimension, represents the Fourier transform along the slow time dimension, , Indicates the number of azimuth pulses.

[0062] The advantages of the method according to the embodiment of the present invention are described below through simulation experiments.

[0063] 1) Simulation experiment environment: Experimental environment: MATLAB R2022b, Intel(R) Core i7-1165G7@ 2.8GHz, Windows 11 Ultimate Edition.

[0064] 2) Simulation experiment content and result analysis: Experimental content: Simulate the maneuverability of the target Figure 2 The cooperative dual-base detection configuration shown in the figure is used to perform coherent accumulation processing on maneuvering targets using other existing methods and the method of the present invention in a simulation environment. Figure 2 In the experimental simulation scenario shown, the transmitting station and the receiving station are separated, the transmitting station is located on the satellite, and the receiving station is located on the aircraft.

[0065] Experimental results: From Figure 2 It can be seen that the satellite platform of the transmitting station, the aircraft platform of the receiving station and the target (P) are all in motion; Figure 3 It can be seen that due to the maneuvering motion characteristics of the target, the results of the coherent accumulation of the traditional method are diffused in the Doppler dimension. One target is diffused into multiple targets in the Doppler dimension, which not only causes the energy after coherent accumulation to decrease, but also causes an increase in false point targets during detection. Therefore, the traditional method cannot achieve effective accumulation of aerial targets.

[0066] from Figure 4 It can be seen that not only the diffusion phenomenon of the target in the Doppler dimension is eliminated, but also all the energy of the target is focused on a peak point, which provides support for subsequent target detection. This shows that the method of the present invention can achieve coherent accumulation of aerial maneuvering targets under the collaborative detection configuration, thereby demonstrating the effectiveness of the method of the present invention.

[0067] Therefore, according to the method of the embodiment of the present invention, long-term coherent integration can be performed on an aerial maneuvering target with third-order motion in a cooperative bistatic detection configuration, which has the following beneficial effects: First, the present invention not only constructs a third-order model of velocity, acceleration and jerk for the motion characteristics of aerial maneuvering targets, but also greatly reduces the amount of calculation while ensuring unchanged performance, avoiding the high computational complexity and performance degradation of multi-dimensional parameter search in the traditional long-term coherent accumulation process, and provides a theoretical basis for the engineering application of long-term coherent accumulation in collaborative detection of aerial targets.

[0068] Second, the method of the present invention does not require hardware improvements to existing radar equipment during specific implementation, and has good engineering application prospects.

[0069] The embodiment of the present invention further provides a computer device, which may be a server, and its internal structure diagram may be as shown in FIG. Figure 5 As shown. The computer device includes a processor, a memory and a network interface connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The database of the computer device is used to store operating parameter data of each framework. The network interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, the steps of the method of the embodiment of the present invention are implemented.

[0070] Those skilled in the art will understand that Figure 5 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0071] An embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of the method of the embodiment of the present invention are implemented.

[0072] An embodiment of the present invention further provides a computer program product, including a computer program, which implements the steps of the method of the embodiment of the present invention when executed by a processor.

[0073] The above description is merely illustrative of certain exemplary embodiments of the present invention. It goes without saying that those skilled in the art will be able to modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the above drawings and description are illustrative in nature and should not be construed as limiting the scope of protection of the claims.

Claims

1. A long-term coherent integration method for a bistatic radar targeting an aerial maneuvering target, characterized in that: include: Step S1: Determine the locations of the transmitting and receiving stations and convert them into the ECEF coordinate system; Step S2: constructing a target echo signal model in a cooperative bistatic detection configuration to achieve space-time-frequency synchronization between the transmitting station and the receiving station; Step S3: performing pulse compression on the echo signal, performing Fourier transform on the pulse compressed echo signal along the distance dimension to obtain a pulse compressed frequency echo signal, flipping the pulse compressed frequency echo signal along the slow time dimension to obtain a pulse compressed frequency echo time flipped signal, and multiplying the pulse compressed frequency echo signal by the pulse compressed frequency echo time flipped signal to obtain a slow time series scale transformed echo signal; Step S4: performing a second-order Keystone correction in the range frequency domain on the echo signal after the slow time series scale transformation, and performing an inverse Fourier transform along the range frequency on the range frequency domain echo signal after the second-order Keystone correction to obtain a time domain echo signal after the second-order Keystone correction; Step S5: performing acceleration estimation on the time domain echo signal after the second-order Keystone correction to obtain an estimated value of acceleration; Step S6: constructing an acceleration compensation factor based on the estimated value of acceleration, compensating the range frequency domain echo signal after the second-order Keystone correction, and obtaining an acceleration-compensated frequency echo signal; Step S7: performing inverse Fourier transform of the distance dimension and Fourier transform of the slow time dimension on the frequency echo signal after acceleration compensation to obtain a signal after long-term coherent accumulation.

2. The method according to claim 1, wherein In step S2, under the cooperative bistatic detection configuration, the target echo signal model is: in, For distance fast time, Indicates the direction of slow time, represents the pulse repetition time, , Indicates the number of azimuth pulses, is the pulse width, is the scattering coefficient of the target, is the carrier frequency of the signal, is the modulation frequency of the signal, represents the speed of light, represents the sum of the initial slant distances from the target to the transmitting station and to the receiving station, Indicates the equivalent speed of the target relative to the transmitting station and the receiving station, represents the equivalent acceleration of the target relative to the transmitting station and the receiving station, It represents the equivalent acceleration of the target relative to the transmitting station and the receiving station.

3. The method according to claim 2, wherein In step S3, the echo signal after pulse compression for: in, Indicates the frequency along the distance The fast inverse Fourier transform operation, represents the wavelength, is the distance frequency domain matched filter, in represents the distance frequency, represents the distance bandwidth, represents the frequency modulation, and .

4. The method according to claim 3, wherein In step S3, the frequency echo signal after pulse compression for: in, Indicates the frequency along the distance Fast Fourier transform operation; Frequency echo time-reversed signal after pulse compression for: Echo signal after slow time series scale transformation for: 。 5. The method according to claim 4, wherein In step S4, the range frequency domain echo signal after the second-order Keystone correction for: in, represents a new slow time scale variable that satisfies: Time domain echo signal after second-order Keystone correction for: 。 6. The method according to claim 5, wherein In step S5, the acceleration Estimated value of for: in Slow-time autocorrelation signal The frequency value corresponding to the peak point is in Indicates slow time, represents the wavelength, represents the conjugation operation.

7. The method according to claim 6, wherein In step S6, the acceleration compensation factor for: Frequency echo signal after acceleration compensation for: , then the frequency echo signal after acceleration compensation is Further simplified to 。 8. The method according to claim 7, wherein In step S7, the signal after long-term coherent accumulation is for: in represents the Fourier transform along the slow time dimension, .

9. The method according to any one of claims 1 to 8, wherein In step S1, the position of the transmitting station is converted to the position in the ECEF coordinate system as follows : in, is the Earth's eccentricity, Respectively represent the latitude, longitude and altitude information of the transmitting station, is the curvature radius of the transmitting station’s azimuth plane, is the equivalent radius of the Earth; The position of the receiving station is converted to the position in the ECEF coordinate system as follows : in, is the Earth's eccentricity, Respectively represent the latitude, longitude and altitude information of the receiving station, is the curvature radius of the receiving station's azimuth plane.

10. A computer device comprising a memory, a processor, and a computer program stored in the memory, wherein: The processor executes the computer program to implement the steps of the method according to any one of claims 1 to 9.

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