Target and background joint simulation method based on target echo and clutter model

Abstract

The invention relates to the technical field of radar signal simulation, in particular to a target characteristic and ground clutter modeling simulation method under the airborne view angle of an unmanned aerial vehicle, and particularly relates to a target and background joint simulation method based on a target echo and clutter model. The invention provides a high-precision and high-reliability simulation method by utilizing the micro-Doppler effect characteristic of a target, the one-dimensional range profile and accurate modeling of ground clutter. The real ground clutter echo is generated by combining the motion trail of the airborne platform of the unmanned aerial vehicle and the landform information, so that the reality sense and reliability of a simulation result are improved.

Description

Technical Field

[0001] The present invention relates to the field of radar signal simulation technology, and in particular to a target characteristic and ground clutter modeling and simulation method under the airborne perspective of an unmanned aerial vehicle, specifically a target and background joint simulation method based on a target echo and clutter model. Background Art

[0002] UAV airborne radar plays an increasingly important role in modern reconnaissance, surveillance and target identification tasks, especially in multi-target environments and complex terrain conditions. Its high mobility and rapid deployment advantages make it have broad application prospects in both military and civilian fields. With the increasing popularity of UAVs in low-altitude operations and complex regional tasks, people's requirements for radar detection distance, imaging accuracy, target recognition ability and environmental adaptability are also increasing. Existing UAV airborne radar simulation methods mostly rely on simplified models and cannot effectively cope with complex flight environments and terrain features. In a multi-target environment, different targets (such as rotary-wing UAVs, fixed-wing aircraft, vehicles, ships, etc.) may appear in the radar field of view at the same time, and their motion modes and target characteristics are different. Existing methods have inaccurate or simplified limitations in modeling target characteristics (such as one-dimensional range images, micro-Doppler characteristics, etc.) and ground clutter, resulting in the simulation results being unable to accurately reflect the real radar echo characteristics. Therefore, there is an urgent need for a new simulation method that can accurately simulate the scattering characteristics of targets and ground clutter in different terrains and environments while maintaining high simulation efficiency, and truly reflect the echo distribution and evolution process of UAV airborne platforms in complex scenes. Summary of the invention

[0003] The present invention provides a method for jointly simulating target echoes and ground clutter based on the perspective of an unmanned aerial vehicle. By accurately simulating target characteristics and ground clutter echoes, the limitations of existing methods are solved, and complex flight environments and terrain features can be effectively dealt with. In particular, for multi-target environments and dynamic and complex scenes, the present invention utilizes the micro-Doppler effect characteristics of the target, one-dimensional range images, and accurate modeling of ground clutter to provide a high-precision, high-reliability simulation method. By combining the motion trajectory of the unmanned aerial vehicle airborne platform with terrain and geomorphic information, a real ground clutter echo is generated, thereby improving the realism and reliability of the simulation results.

[0004] The technical solution of the present invention is as follows:

[0005] A target and background joint simulation method based on target echo and clutter model, the steps are as follows:

[0006] (1) Radar transmission signal generation

[0007] Assume that the radar transmits a linear frequency modulated pulse. At time t, the transmitted signal S(t) is expressed as:

[0008]

[0009] Among them, rect(t) is the rectangular window function, T p is the pulse width of the transmitted signal, j is the imaginary unit; f 0 is the carrier frequency, B is the frequency modulation bandwidth, and the linear modulation rate

[0010] (2) Point target echo signal generation

[0011] According to the specific type of the target (UAV, space cone), its physical model is constructed, and the target's size, shape, surface material, motion state and other information are described in detail. Special attention is paid to its components with micro-motion modes and aerodynamic characteristics. By adjusting the plane wave viewing angle or changing the posture of the target components according to the external Matlab program call, the target complex scattering coefficient sequence at the corresponding time is obtained.

[0012] At time t, the echo signal received from a point target P in space is expressed as:

[0013]

[0014] Among them, the delay time from radar echo to radar receiver is The speed of light c = 3 × 10 8 m / s, the distance between point P and the radar is R.

[0015] Considering the modulation of the radar echo amplitude by the target, the point target echo signal can be obtained:

[0016]

[0017] The distance voltage coefficient of the scatterer, i.e. the amplitude Among them, P t is the radar transmitter power, wavelength Complex scattering coefficient of the target σ is the radar cross-section (RCS), φ is the phase term when the signal is reflected. When studying a single point target, the effect of the phase shift φ can be ignored, but if the target cannot be regarded as a point target, the phase shift φ cannot be ignored; antenna power gain Antenna pattern using sinc function:

[0018]

[0019] In the formula, θ and is the azimuth and elevation angle of the corresponding scattering unit, θ 0 and is the beam direction of the radar antenna, θ 3dB and is the 3dB main lobe width of the antenna.

[0020] (3) Extended target echo signal generation

[0021] For ships or other large and complex targets that cannot be regarded as point targets (such as drone clusters), full-wave simulation software is used to obtain the frequency response sequence F(ω) at the corresponding viewing angle, which contains the scattering information of the target at each frequency point. Applying inverse Fourier transform to the frequency response sequence can obtain the one-dimensional range image sequence of the target.

[0022] The scattered electric field data E of the target at each frequency point can be extracted from the scattering data obtained by simulation:

[0023]

[0024] Where j is the imaginary unit; let θ E , are the angles between the plane wave irradiation direction and the XOZ plane and the XOY plane in the ground coordinate system, with the target mass center as the center. are the real and imaginary parts of the electric field obtained under horizontal polarization and vertical polarization at the corresponding angles, respectively.

[0025] The UAV cluster is modeled as a large extended target as a whole, and a unified geometric model and scattering characteristics are used to describe the electromagnetic scattering behavior of the multi-target cluster as a whole. In this way, the changes in the scattering contribution of each sub-target in the cluster and the performance of the shielding effect in the radar echo can be reflected.

[0026] Considering its position information, the center point of the target model is set as point P, and the frequency domain scattering data H(ω) is combined with the frequency domain form S of the point target echo signal p By multiplying (ω), we can get the target echo signal in the frequency domain:

[0027] S target (ω)=S P (ω)H(ω)

[0028] The time domain target echo signal is obtained by inverse Fourier transform:

[0029] S target (t) = IFFT[S target (ω)]

[0030] (4) Clutter model establishment

[0031] For the ground area, the equidistance-equiazimuth division method is used to divide the ground units. First, the ground is divided into range rings according to the range resolution ΔR = c / 2B, and then the azimuth resolution is used to divide the ground into range rings. Each range ring is divided into multiple units; where V is the absolute velocity of the radar platform, ω is the pitch angle of the radar platform velocity in the inertial reference coordinate system, is the pitch angle of the ground unit, Δf d is the Doppler resolution. In order to balance the accuracy and efficiency of calculation, the angular resolution can be reduced, thereby reducing the number of units divided into each range ring.

[0032] When simulating clutter signals, the Digital Elevation Model (DEM) is introduced. According to the geographical location of each ground unit and the radar position, the incident angle between the radar beam and the ground can be obtained, and it can be determined whether the ground area is blocked.

[0033] Combined with digital elevation data, the terrain undulation is calculated, the obstruction of radar beam caused by terrain obstacles during propagation is considered, and the ground units that cannot receive echoes are eliminated.

[0034] The landform type parameters are extracted by introducing landform coverage data, and the landform type is reclassified. The incident angle and landform type of each unit are introduced into the Morchin sea clutter model and the modified Morchin model (Peng Shirui, Tang Ziyue. Research on the reflectivity model of land (sea) clutter [J]. Journal of Air Force Radar Academy, 2000, (04): 1-4+14.) to calculate the scattering coefficient of the scattering unit.

[0035] The imported target area may contain water. The scattering coefficient of the scattering unit in the water area uses the Morchin sea clutter model:

[0036]

[0037] For non-water areas, the scattering coefficient uses the modified Morchin model:

[0038]

[0039] Among them, σ 0 is the reflectivity coefficient, A, B, β 0 , is the coefficient related to land type; ss is the sea condition coefficient.

[0040] When the terrain type is desert, θ is the ground rubbing angle of the unit under test,

[0041] Then, the ground unit scattering coefficient of the mth ground scattering unit on the nth range ring is is the reflectivity coefficient of the unit, S mn is the area of ​​the ground scattering unit, R mnThe distance from the radar to the ground unit.

[0042] The ground scattering unit echo signal is expressed as:

[0043]

[0044] S c (t) is convolved with the linear frequency modulation signal S(t) in the time domain to obtain the clutter scattering echo S clutter (t).

[0045] (5) Echo signal output and analysis

[0046] Random noise is expressed as:

[0047] S noise (t) = rand(t)

[0048] Here, rand(t) represents a function for generating random numbers uniformly distributed in the interval [0,1].

[0049] First, according to the preset signal-to-noise ratio, the target echo signal and the clutter echo signal are weighted superimposed at the amplitude or power level; then, according to the set signal-to-noise ratio, a random noise signal of the corresponding amplitude or power level is added. The superimposed signal is convolved with the transmitted signal sequence to obtain the drone airborne radar echo signal in a complex scene including the target echo, ground clutter and random noise. The radar received signal S r (t) is represented by the target scattered echo S target (t), clutter scatter echo S clutter (t) and random noise S noise The vector sum of (t):

[0050] S r (t) = S target (t)+S clutter (t)+S noise (t)

[0051] S r (t) is a received signal in the form of linear frequency modulation, which needs to be subjected to pulse compression processing. The matched filter is expressed as:

[0052] h(t)=exp(-jπμt 2 )

[0053] Get the echo signal after pulse compression:

[0054]

[0055] The echo signal matrix after pulse compression contains a one-dimensional range image of the target. The micro-Doppler effect of the target can be observed by time-frequency analysis of the echo signal matrix. The simulated radar echo signal can be used for further signal processing and analysis, such as clutter suppression, target detection, target recognition, etc.

[0056] Beneficial effects of the present invention:

[0057] (1) High-precision target characteristic simulation: The present invention combines rotor motion with radar waveform modeling to truly reflect the micro-Doppler effect and one-dimensional range image changes of the target from the perspective of the UAV airborne radar.

[0058] (2) Accurate ground clutter modeling: By combining surface data and terrain information with the motion trajectory of the UAV airborne platform, ground clutter echoes that conform to the UAV airborne perspective are generated.

[0059] (3) Comprehensive target-clutter interaction simulation: The interaction between targets and ground clutter is fully modeled, which is applicable to multi-target dynamic scenarios and enhances the versatility and adaptability of the simulation system. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Figure 1 The distance-Doppler diagram of the simulation results in the embodiment;

[0061] Figure 2 It is a time-frequency diagram of a UAV echo in a simulation scenario in the embodiment. DETAILED DESCRIPTION

[0062] The specific implementation of the present invention is further described below in combination with the technical content.

[0063] The present invention mainly adopts the method of simulation experiment for verification. The target characteristic simulation needs to obtain the target characteristic sequence with the help of full-wave simulation software. All results are verified to be correct on MATLAB2023b. The technical solution adopted in this embodiment is as follows:

[0064] S1. Set the radar transmission signal simulation parameters. The transmission signal adopts the linear frequency modulation pulse form, the carrier frequency is 35.5GHz, the bandwidth is 200MHz, the sampling rate is 400MHz, the pulse repetition period PRF=22000Hz, and the pulse width is 1μs. Generate the radar transmission signal according to the above simulation parameters.

[0065] S2. At t = 0, the drone airborne radar is located at [0, 0, 500], the velocity vector is [20, 0, 0], and the center of the drone formation is located at [2300, 0, 400]. At the same time, in order to observe the impact of distance on the target echo, a drone is set up in the area near [2185, 0, 400]. All drones fly in the same direction with a velocity vector of [-10, 10, 0]. The radar line of sight points to the center of the target drone formation, and the radar line of sight pitch angle is about -2.5°.

[0066] The DJI Inspire 2 drone and drone cluster models were built and imported into the full-wave simulation software. In order to simulate the mutual occlusion between drone clusters, some drones were arranged on the radar line of sight, and the target echo simulation method was extended. The frequency domain scattering data of the target drone and cluster were obtained with the help of the full-wave simulation software, and the data was multiplied with the frequency domain form of the target linear frequency modulation echo signal in step S1, and the result was transformed back to the time domain to obtain the target echo signal.

[0067] S3. Import the 10m×10m grid data of the digital elevation map and the surface landform coverage data. Divide the ground unit according to the distance resolution and azimuth resolution. According to the coordinates of the center of each ground unit, first determine its row and column index range in the DEM grid. Find the elevation values ​​of the four grid points (upper left, upper right, lower left, and lower right) adjacent to the center point in the DEM. According to the distance ratio between the center point and the four grid points in the horizontal and vertical directions, perform bilinear interpolation on these four elevation values ​​to obtain the elevation data of the ground unit point. According to the elevation data of each ground point, calculate the terrain undulation, consider the obstruction caused by terrain obstacles during the propagation of the radar beam, and eliminate the ground unit that cannot receive the echo. At the same time, find the grid node closest to the point in the surface coverage data to determine the landform type of the ground unit. Substitute the incident angle and landform type of each unit into the modified Morchin scattering coefficient model. For the water unit, set the sea clearness coefficient ss=2 to calculate the scattering coefficient of each unit. To simplify the calculation, the radar transmitter power P t =1, power gain Using the sinc function antenna pattern, the generated signal is convolved with the specific transmit signal sequence to obtain the clutter signal.

[0068] S4. Coherently process the 2200 pulses, and according to the preset signal-to-clutter ratio SCR = 20dB and signal-to-noise ratio SNR = 20dB, superimpose the echo signal, clutter signal and noise to obtain the drone airborne radar echo signal in complex scenes, and arrange the echo signal into a two-dimensional matrix. Process the drone echo sequence matrix in complex environments, perform pulse compression on the distance dimension, and perform FFT transformation on the Doppler dimension at the same time to obtain the following: Figure 1 Range-Doppler plot shown.

[0069] The simulated echo data is processed by clutter removal, and after filtering, CFAR detection is performed to obtain the distance unit where the target is located. The distance unit where the target is located is extracted, and the target speed or Doppler frequency shift is preliminarily estimated. Through phase compensation, the target echo is moved to the vicinity of zero Doppler frequency, and the result is subjected to time-frequency analysis, such as Figure 2 As shown, the extracted target micro-Doppler characteristics are consistent with the preset ones.

Claims

1. A target and background joint simulation method based on target echo and clutter model, characterized in that: Here are the steps: (1) Radar transmission signal generation Assume that the radar transmits a linear frequency modulated pulse. At time t, the transmitted signal S(t) is expressed as: Among them, rect(t) is the rectangular window function, T p is the pulse width of the transmitted signal, j is the imaginary unit; f0 is the carrier frequency, B is the frequency modulation bandwidth, and the linear modulation rate (2) Point target echo signal generation At time t, the echo signal received from a point target P in space is expressed as: Among them, the delay time from radar echo to radar receiver is The speed of light c = 3 × 10 8 m / s, the distance between point P and the radar is R; Considering the modulation of the radar echo amplitude by the target, the point target echo signal is obtained: The distance voltage coefficient of the scatterer, i.e. the amplitude Among them, P t is the radar transmitter power, wavelength Complex scattering coefficient of the target σ is the radar cross section (RCS), φ is the phase term when the signal is reflected; antenna power gain Antenna pattern using sinc function: In the formula, θ and are the azimuth and elevation angles of the corresponding scattering unit, θ0 and is the beam direction of the radar antenna, θ 3dB and is the 3dB main lobe width of the antenna; (3) Extended target echo signal generation For ships or other large and complex targets that cannot be regarded as point targets, the full-wave simulation software is used to obtain the frequency response sequence F(ω) at the corresponding viewing angle, which contains the scattering information of the target at each frequency point; the inverse Fourier transform is applied to the frequency response sequence to obtain the one-dimensional range image sequence of the target; The scattered electric field data E of the target at each frequency point is extracted from the scattering data obtained by simulation: Where j is the imaginary unit; let θ E , are the angles between the plane wave irradiation direction and the XOZ plane and the XOY plane in the ground coordinate system, with the target mass center as the center. are the real and imaginary parts of the electric field obtained under horizontal polarization and vertical polarization at the corresponding angles, respectively; The UAV cluster is modeled as a large extended target, and the electromagnetic scattering behavior of the multi-target cluster is described using a unified geometric model and scattering characteristics. Considering its position information, the center point of the target model is set as point P, and the frequency domain scattering data H(ω) is combined with the frequency domain form S of the point target echo signal p (ω) to obtain the target echo signal in the frequency domain: S target (ω)=S P (ω)H(ω) The time domain target echo signal is obtained by inverse Fourier transform: S target (t)=IFFT[S target (ω)] (4) Clutter model establishment For the ground area, the equidistance-equiazimuth division method is used to divide the ground units. First, the ground is divided into range rings according to the range resolution ΔR = c / 2B, and then the azimuth resolution Each range ring is divided into multiple units; where V is the absolute velocity of the radar platform, ω is the pitch angle of the radar platform velocity in the inertial reference coordinate system, is the pitch angle of the ground unit, Δf d is the Doppler resolution; When simulating clutter signals, a digital elevation map is introduced to obtain the incident angle between the radar beam and the ground according to the geographical location of each ground unit and the radar position, and to determine whether the ground area is blocked; Combined with digital elevation data, terrain undulations are calculated, and the shielding of radar beams caused by terrain obstacles during propagation is considered to eliminate ground units that cannot receive echoes; By introducing the surface landform coverage data to extract the surface coverage type parameters, the landform types are reclassified; the incident angle and landform type of each unit are brought into the Morchin sea clutter model and the modified Morchin model to calculate the scattering coefficient of the scattering unit; The ground unit scattering coefficient of the mth ground scattering unit on the nth range ring is the reflectivity coefficient of the unit, S mn is the area of ​​the ground scattering unit, R mn The distance from the radar to the ground unit; The ground scattering unit echo signal is expressed as: S c (t) is convolved with the linear frequency modulation signal S(t) in the time domain to obtain the clutter scattering echo S clutter (t); (5) Echo signal output and analysis Random noise is expressed as: S noise (t)=rand(t) Among them, rand(t) represents a function for generating random numbers uniformly distributed in the interval [0,1]; First, according to the preset signal-to-noise ratio, the target echo signal and the clutter echo signal are weightedly superimposed at the amplitude or power level; then, according to the set signal-to-noise ratio, a random noise signal of the corresponding amplitude or power level is added; the superimposed signal is convolved with the transmitted signal sequence to obtain the UAV airborne radar echo signal in a complex scene including the target echo, ground clutter and random noise; the radar receiving signal S r (t) is represented by the target scattered echo S target (t), clutter scatter echo S clutter (t) and random noise S noise The vector sum of (t): S r (t)=S target (t)+S clutter (t)+S noise (t) S r (t) is a received signal in the form of linear frequency modulation, which needs to be subjected to pulse compression processing. The matched filter is expressed as: h(t)=exp(-jπμt 2 ) Get the echo signal after pulse compression: The echo signal matrix after pulse compression contains the one-dimensional range image of the target. The time-frequency analysis of the echo signal matrix is ​​performed, and the target micro-Doppler effect is observed. The simulated radar echo signal is used for further signal processing and analysis.

2. The target and background joint simulation method based on target echo and clutter model according to claim 1 is characterized in that: In step (4), The imported target area may contain water. The scattering coefficient of the scattering unit in the water area uses the Morchin sea clutter model: For non-water areas, the scattering coefficient uses the modified Morchin model: Among them, σ 0 is the reflectivity coefficient, A, B, β0, is the coefficient related to land type; ss is the sea condition coefficient; When the terrain type is desert, θ is the ground rubbing angle of the unit under test,

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