Inter-carrier interference suppression method based on OFDM radar communication integrated system

Abstract

The invention discloses an inter-carrier interference suppression method based on an OFDM radar communication integrated system, and belongs to the technical field of radar communication integration. The method comprises the following steps: firstly, constructing an OFDM radar communication integrated transmitting signal; a target is preset in the space, and an OFDM radar communication integrated signal is transmitted to the target; after target reflection, a target echo signal is obtained, and down-conversion, sampling and cyclic prefix removal processing are sequentially carried out on the target echo signal; carrying out 2D-DFT processing to obtain an original distance-speed image of the target; non-fuzzy velocity estimation based on multi-hypothesis velocity compensation; estimating a target scattering coefficient; reconstructing an ICI-free target signal by using the estimated target scattering coefficient; and carrying out 2D-DFT processing on the target signal without ICI to obtain a target distance-speed image without ICI. According to the method, the problem of inter-carrier interference generated by high dynamic is solved without sacrificing the communication rate and the fuzzy distance.

Description

Technical Field

[0001] The present invention belongs to the technical field of radar communication integration, and in particular relates to an inter-carrier interference suppression method based on an OFDM radar communication integration system. Background Art

[0002] With the rapid development of intelligent driving technology, smart vehicles are placing higher demands on both radar detection and wireless communication performance. At the same time, the increasing number of onboard sensors will lead to a series of problems, including increased system size, increased energy consumption, and increased electromagnetic interference. Integrated radar and communication technology is an effective approach to addressing these issues. By sharing hardware and spectrum resources, it simultaneously implements communication and radar functions, significantly improving resource efficiency and achieving functional complementarity. Applying integrated radar and communication technology to smart vehicles will help achieve universality, miniaturization, and multifunctionality in onboard equipment, and has important theoretical and practical application value.

[0003] Integrated waveform design is a key technology for achieving integrated radar communication. Orthogonal Frequency Division Multiplex (OFDM), as a multi-carrier transmission technology commonly used in modern communication systems, has received widespread attention in radar communication integrated waveform design in recent years due to its advantages such as large time-bandwidth product, flexible parameter design and good anti-interception performance. For example, in the prior art, the Chinese patent with publication number CN104580052A discloses a new application of multi-carrier direct-spread signal in radar communication integration, which mentions combining orthogonal frequency division multiplexing (OFDM) with spread spectrum technology. However, OFDM signals are more sensitive to Doppler shift. The Doppler shift caused by high-speed vehicle movement will destroy the orthogonality between subcarriers and generate inter-carrier interference (ICI), resulting in an increase in the side lobes of the target range image, reducing the detection performance of weak targets.

[0004] In response to the ICI problem in the OFDM radar communication integrated system, the traditional two-dimensional discrete Fourier transform (2D-DFT) algorithm is tolerating the impact of ICI on the target imaging performance by setting parameters, such as increasing the subcarrier frequency spacing to keep the normalized Doppler below 0.1. Although the 2D-DFT algorithm can suppress the impact of ICI by increasing the subcarrier spacing, it will cause the maximum unambiguous distance to decrease. In addition to the 2D-DFT algorithm, the repeated symbol algorithm has also been proposed to suppress ICI. Related literature [Tian Xuanxuan, Hu Nianping. Design method of integrated UAV radar communication based on OFDM [J]. Signal Processing, 2020, 36 (10): 1714-1720.] studied the application of the repeated symbol algorithm in the OFDM radar communication integrated system. However, the repeated symbol algorithm has a defect, that is, due to the use of repeated symbols, the communication rate will be reduced.

[0005] All of these technical approaches have significant technical drawbacks and cannot simultaneously meet the performance requirements of radar and communications. Therefore, designing an ICI mitigation algorithm while maintaining unambiguous range without compromising communication speed is a core issue that needs to be addressed in this field. Summary of the Invention

[0006] In response to the problems in the related art, the present invention proposes an inter-carrier interference suppression method based on an OFDM radar communication integrated system to overcome the above-mentioned technical problems existing in the existing related art. The present invention solves the inter-carrier interference problem caused by high dynamics without sacrificing the communication rate and unambiguous distance, and at the same time realizes unambiguous estimation of target speed.

[0007] The technical solution of the present invention is achieved as follows: a method for suppressing inter-carrier interference based on an OFDM radar communication integrated system, the method comprising the following steps:

[0008] Step S1: First construct an OFDM radar communication integrated transmission signal;

[0009] Step S2: A target is preset at a distance r and has a radial velocity v. The OFDM radar communication integrated signal is transmitted toward the target. After reflection from the target, the target echo signal is obtained. The received target echo signal is sequentially down-converted, sampled, and cyclic prefix removed, and described in matrix form.

[0010] Step S3: Perform 2D-DFT processing on the signal described in matrix form in step S2 to obtain the original range-velocity image of the target;

[0011] Step S4: unambiguous velocity estimation based on multi-hypothesis velocity compensation;

[0012] Step S5: estimation of target scattering coefficient;

[0013] Step S6: Using the estimated target scattering coefficient, reconstruct the target signals with and without ICI; then perform 2D-DFT processing on the target signal without ICI to obtain the target range-velocity image without ICI.

[0014] Furthermore, in step S1, the OFDM radar communication integrated transmission signal is expressed by formula (1), which is:

[0015]

[0016] Among them, N c is the number of subcarrier frequencies, N s is the number of OFDM symbols, A n，m is the communication data on the mth OFDM symbol of the nth subcarrier frequency; j is the imaginary unit, t is the time, f c is the carrier frequency; T s =T+T g Represents a complete OFDM symbol period, T = 1 / Δf is the effective OFDM symbol period, Δf is the subcarrier frequency interval, T g is the cyclic prefix (CP) period; rect(t) is the unit rectangular window function, when 0 <t<T s 1 when t≤0 or t≥T s Time is 0.

[0017] Furthermore, in step S2, the target scattering coefficient is α, the target normalized delay is represented by τ=2rΔf / c, and the normalized Doppler shift is represented by f d =2vTf c / c, where c is the speed of light;

[0018] After the OFDM radar communication integrated signal is reflected by the target, the received target echo signal is processed by down-conversion, sampling and cyclic prefix removal, and is expressed by formula (2), which is as follows:

[0019]

[0020] Where i∈[0, N c -1] is the fast time, m∈[0, N s -1] is the slow time, ρ=αexp(-j2πf c τT), β=T s / T;

[0021] In formula (2), the second exponential term exp(-j2πnτ) contains the time delay information, which is used for distance estimation; the last two exponential terms contain Doppler information, exp(j2πmf d β) is the Doppler information between symbols, which is used for velocity estimation; It is the ICI generated by Doppler, which raises the range image sidelobes.

[0022] Furthermore, in step S2, in order to make the algorithm process based on the modulation symbol clearer and simpler, formula (2) is described in matrix form and expressed by formula (3), which is as follows:

[0023]

[0024] In formula (3), is the modulation symbol matrix at the transmitter, is the ICI generated by Doppler, and the other parameters are expressed by formulas (4), (5), and (6), which are as follows:

[0025]

[0026] Where, diag[·] represents a diagonal matrix, * represents conjugation, and F N is the N×N DFT matrix, is an N×N IDFT matrix.

[0027] Furthermore, in step S3, the 2D-DFT processing refers to performing the following processing on formula (3) in step S2:

[0028] Step S3a: Perform DFT processing on the fast time domain to obtain the frequency domain signal on each subcarrier;

[0029] Step S3b: Matrix division is used to eliminate the influence of communication data on radar performance;

[0030] Step S3c: velocity-dimensional DFT processing to obtain a velocity image;

[0031] Step S3d: Perform distance-dimensional IDFT processing to obtain a range image.

[0032] Furthermore, the 2D-DFT process is expressed by formula (7), which is as follows:

[0033]

[0034] Where G represents the original range-velocity image of the target.

[0035] Furthermore, in step S4, when the target real speed v a Greater than the maximum unambiguous speed v max When v a The calculation of is expressed by formula (8), which is:

[0036] v a =v0+2ξv max (8);

[0037] Among them, v0 is the fuzzy estimate of the target's true speed, v max =c / (4f c T s ) is the maximum unambiguous velocity of the radar, and ξ is the velocity ambiguity number; then the ICI generated by the target Doppler in formula (3) satisfies the following formula (9):

[0038]

[0039] Among them, f d (v a )=2f c v a T / c,f d (v0)=2f c v0T / c.

[0040] Furthermore, in step S4, the following steps are also included:

[0041] Step S4a: Set the value range of the velocity ambiguity number; assuming that ξ∈{-Z, -Z+1, ..., Z}, and Z is a positive integer, the maximum unambiguous velocity of the radar is from [-v max , v max ] increases to [-(2Z+1)v max , (2Z+1)v max ];

[0042] Step S4b: Construct compensation matrix D Nc (-ξ / (βN c )), between y and D Nc (-ξ / (βN c )) are multiplied to suppress the ICI generated by the target blur speed; then 2D-DFT processing is performed to obtain the compensated two-dimensional range-velocity image G(ξ). The above operation is expressed by formula (10), which is as follows:

[0043]

[0044] Step S4c: Target detection and unambiguous velocity estimation; G(ξ) is tested with a constant false alarm rate (CFAR) to extract the distance and velocity index of potential targets; the target distance and velocity index set corresponding to all ξ detected by CFAR is expressed as The corresponding normalized delay and normalized Doppler sets are Among them, I is the set The number of elements in , that is, the number of detected targets, and I is a positive integer.

[0045] The unambiguous velocity estimation of the present invention adopts the maximum Peak Side Lobe Ratio (PSLR) criterion of the range image; for each detected target, the PSLR corresponding to different ξ is compared to determine the one with the maximum PSLR. is the true fuzzy number of the target velocity to achieve unambiguous estimation of the target velocity.

[0046] Furthermore, in step S5, the following processing is included:

[0047] Step S5a: Based on the previously detected target, the target signal value is extracted from G in formula (7), which is expressed by formula (11). The formula (11) is as follows:

[0048]

[0049] Step S5b: construct a target signal containing ICI and a target signal without ICI, which are respectively expressed by formulas (12) and (13). The formulas (12) and (13) are as follows:

[0050]

[0051] The target signal in formula (12) is processed by 2D-DFT to obtain the target range-velocity image, which is expressed by formula (14). Formula (14) is as follows:

[0052]

[0053] Then extract the target signal value and express it through formula (15), which is:

[0054]

[0055] Based on the mathematical relationship between formula (11) and formula (15), q can be expressed as The linear combination of Q is the target scattering coefficient; by solving the linear equations, the target scattering coefficient is obtained, which is expressed by formula (16). The formula (16) is: α=(QT Q) -1 Q T q(16);

[0056] Where T represents the transposition operation, α=[α0,α1,…,α I-1 ] T ,

[0057] Furthermore, in step S6, the estimated target scattering coefficient is used to reconstruct the target signals with and without ICI. The ICI signal in the original received signal in formula (3) is replaced with the reconstructed ICI-free signal. Finally, the target echo after ICI suppression is obtained, which is expressed by formula (17). Formula (17) is as follows:

[0058]

[0059] y m Further 2D-DFT processing is performed to obtain the target range-velocity image without ICI.

[0060] Through the above processing, the present invention effectively suppresses ICI without sacrificing the communication rate and the maximum unambiguous distance, and simultaneously realizes unambiguous estimation of the target speed.

[0061] Beneficial effects of the present invention:

[0062] This invention provides a method for suppressing inter-carrier interference (ICI) based on an integrated OFDM radar communication system. Compared to existing 2D-DFT and repeated symbol algorithms, this method can be applied to integrated millimeter-wave vehicle-mounted radar communication scenarios, particularly in high-dynamic scenarios. Without sacrificing communication speed or unambiguous distance, it effectively suppresses ICI generated by high dynamics while achieving unambiguous estimation of target velocity. This method clearly has great application value. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] Figure 1 Schematic diagram of the ICI suppression algorithm of the present invention;

[0064] Figure 2 Parameter setting table for the OFDM radar communication integrated system of the present invention;

[0065] Figure 3 is the target parameter table of the present invention;

[0066] Figure 4 It is the target range-velocity image of the 2D-DFT algorithm;

[0067] Figure 5 The target range-velocity image of the repeated symbol algorithm;

[0068] Figure 6 The target range-speed image of the ICI suppression algorithm of the present invention;

[0069] Figure 7 The graph shows the functional relationship between the range image peak sidelobe ratio and the normalized Doppler under three different algorithms. DETAILED DESCRIPTION

[0070] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0071] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", "clockwise", "counterclockwise" and the like to indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as limiting the present invention.

[0072] In this embodiment, if Figure 1 As shown, this embodiment provides an inter-carrier interference suppression method based on an OFDM radar communication integrated system, and the inter-carrier interference suppression method includes the following steps:

[0073] Step S1: First construct an OFDM radar communication integrated transmission signal;

[0074] Step S2: A target is preset at a distance r and has a radial velocity v. The OFDM radar communication integrated signal is transmitted toward the target. After reflection from the target, the target echo signal is obtained. The received target echo signal is sequentially down-converted, sampled, and cyclic prefix removed, and described in matrix form.

[0075] Step S3: Perform 2D-DFT processing on the signal described in matrix form in step S2 to obtain the original range-velocity image of the target;

[0076] Step S4: unambiguous velocity estimation based on multi-hypothesis velocity compensation;

[0077] Step S5: estimation of target scattering coefficient;

[0078] Step S6: Using the estimated target scattering coefficient, reconstruct the target signals with and without ICI; then perform 2D-DFT processing on the target signal without ICI to obtain the target range-velocity image without ICI.

[0079] In this embodiment, compared with the existing 2D-DFT algorithm and repeated symbol algorithm, the inter-carrier interference suppression method described in this embodiment adds multiple steps, such as unambiguous velocity estimation based on multi-hypothesis velocity compensation, estimation of target scattering coefficient, and reconstruction of ICI-free target signal using the estimated target scattering coefficient. This achieves the acquisition of an ICI-free target range-velocity profile without sacrificing communication rate and unambiguous range, thereby meeting the performance requirements of both radar and communication.

[0080] Specifically, in step S1, the OFDM radar communication integrated transmission signal is expressed by formula (1), which is:

[0081]

[0082] Among them, N c is the number of subcarrier frequencies, N s is the number of OFDM symbols, A n,m is the communication data on the mth OFDM symbol of the nth subcarrier frequency; j is the imaginary unit, t is the time, f c is the carrier frequency; T s =T+T g Represents a complete OFDM symbol period, T = 1 / Δf is the effective OFDM symbol period, Δf is the subcarrier frequency interval, T g is the cyclic prefix (CP) period; rect(t) is the unit rectangular window function, when 0<t<T s 1 when t≤0 or t≥T s Time is 0.

[0083] Specifically, in step S2, the target scattering coefficient is α, the target normalized delay is represented by τ=2rΔf / c, and the normalized Doppler shift is represented by f d =2vTf c / c, where c is the speed of light;

[0084] After the OFDM radar communication integrated signal is reflected by the target, the received target echo signal is processed by down-conversion, sampling and cyclic prefix removal, and is expressed by formula (2), which is as follows:

[0085]

[0086] Among them, i∈[0,Nc -1] is the fast time, m∈[0,N s -1] is the slow time, ρ=αexp(-j2πf c τT), β=T s / T;

[0087] In formula (2), the second exponential term exp(-j2πnτ) contains the time delay information, which is used for distance estimation; the last two exponential terms contain Doppler information, exp(j2πmf d β) is the Doppler information between symbols, which is used for velocity estimation; It is the ICI generated by Doppler, which raises the range image sidelobes.

[0088] Specifically, in step S2, in order to make the algorithm process based on the modulation symbol clearer and simpler, formula (2) is described in matrix form and expressed by formula (3), which is as follows:

[0089]

[0090] In formula (3), is the modulation symbol matrix at the transmitter, is the ICI generated by Doppler, and the other parameters are expressed by formulas (4), (5), and (6), which are as follows:

[0091]

[0092] Where, diag[·] represents a diagonal matrix, * represents conjugation, and F N is the N×N DFT matrix, is an N×N IDFT matrix.

[0093] Specifically, in step S3, the 2D-DFT processing refers to performing the following processing on formula (3) in step S2:

[0094] Step S3a: Perform DFT processing on the fast time domain to obtain the frequency domain signal on each subcarrier;

[0095] Step S3b: Matrix division is used to eliminate the influence of communication data on radar performance;

[0096] Step S3c: velocity-dimensional DFT processing to obtain a velocity image;

[0097] Step S3d: Perform distance-dimensional IDFT processing to obtain a range image.

[0098] Specifically, the 2D-DFT process is expressed by formula (7), which is as follows:

[0099]

[0100] Where G represents the original range-velocity image of the target.

[0101] Specifically, in step S4, when the target real speed v a Greater than the maximum unambiguous speed v max When v a The calculation of is expressed by formula (8), which is:

[0102] v a =v0+2ξv max (8);

[0103] Among them, v0 is the fuzzy estimate of the target's true speed, v max =c / (4f c T s ) is the maximum unambiguous velocity of the radar, and ξ is the velocity ambiguity number; then the ICI generated by the target Doppler in formula (3) satisfies the following formula (9):

[0104]

[0105] Among them, fd(v a )=2f c v a T / c,fd(v0)=2f c v0T / c.

[0106] Specifically, in step S4, the following steps are also included:

[0107] Step S4a: Set the value range of the velocity ambiguity number; assuming that ξ∈{-Z, -Z+1, ..., Z}, and Z is a positive integer, the maximum unambiguous velocity of the radar is from [-v max , v max ] increases to [-(2Z+1)v max , (2Z+1)v max ];

[0108] Step S4b: Construct compensation matrix D Nc (-ξ / (βN c )), between y and D Nc (-ξ / (βN c )) are multiplied to suppress the ICI generated by the target blur speed; then 2D-DFT processing is performed to obtain the compensated two-dimensional range-velocity image G(ξ). The above operation is expressed by formula (10), which is as follows:

[0109]

[0110] Step S4c: Target detection and unambiguous velocity estimation; G(ξ) is tested with a constant false alarm rate (CFAR) to extract the distance and velocity index of potential targets; the target distance and velocity index set corresponding to all ξ detected by CFAR is expressed as The corresponding normalized delay and normalized Doppler sets are Among them, I is the set The number of elements in , that is, the number of detected targets, and I is a positive integer.

[0111] Among them, the unambiguous velocity estimation of this embodiment adopts the maximum Peak Side Lobe Ratio (PSLR) criterion of the range image; for each detected target, the PSLR corresponding to different ξ is compared to determine the one with the maximum PSLR. is the true fuzzy number of the target velocity to achieve unambiguous estimation of the target velocity.

[0112] Specifically, step S5 includes the following processing steps:

[0113] Step S5a: Based on the previously detected target, the target signal value is extracted from G in formula (7), which is expressed by formula (11). The formula (11) is as follows:

[0114]

[0115] Step S5b: construct a target signal containing ICI and a target signal without ICI, which are respectively expressed by formulas (12) and (13). The formulas (12) and (13) are as follows:

[0116]

[0117] The target signal in formula (12) is processed by 2D-DFT to obtain the target range-velocity image, which is expressed by formula (14). Formula (14) is as follows:

[0118]

[0119] Then extract the target signal value and express it through formula (15), which is:

[0120]

[0121] Based on the mathematical relationship between formula (11) and formula (15), q can be expressed as The linear combination of Q is the target scattering coefficient; by solving the linear equations, the target scattering coefficient is obtained, which is expressed by formula (16). The formula (16) is: α=(Q T Q) -1 Q T q(16);

[0122] Where T represents the transposition operation, α=[α0,α1,…,α I-1 ] T ,

[0123] Specifically, in step S6, the estimated target scattering coefficient is used to reconstruct the target signals with and without ICI. The ICI signal in the original received signal in formula (3) is replaced with the reconstructed ICI-free signal. Finally, the target echo after ICI suppression is obtained, which is expressed by formula (17). Formula (17) is as follows:

[0124]

[0125] y m Further 2D-DFT processing is performed to obtain the target range-velocity image without ICI.

[0126] Through the above processing, this embodiment effectively suppresses ICI without sacrificing the communication rate and the maximum unambiguous distance, and simultaneously achieves unambiguous estimation of the target speed.

[0127] like Figure 2-7 As shown, in order to more clearly highlight the technical effect that can be achieved by the inter-carrier interference suppression method described in this embodiment, the inter-carrier interference suppression method of this embodiment is compared with the methods of the prior art (2D-DFT algorithm, repeated symbol algorithm) by simulation experiments.

[0128] Specifically, Figure 2 This is the parameter setting table for the OFDM radar communication integrated system. The communication data is randomly generated and modulated using Binary Phase Shift Keying (BPSK). Hamming window functions are used in the range and velocity dimensions to suppress sidelobes. The channel model is a Gaussian white noise channel.

[0129] More specifically, according to Figure 2 The system parameter settings in the radar are as follows: the maximum unambiguous speed is 84.55 m / s; in order to cover the possible speeds in the automotive application scenario, the value range of the speed ambiguity number ξ is set to {-1, 0, 1}; the target parameters are as follows Figure 3 shown.

[0130] like Figure 4-7As shown in the figure, the content and results of the simulation experiment are analyzed as follows:

[0131] Figure 4 The target range-velocity image of the 2D-DFT algorithm is shown in Figure 2. No ICI suppression is observed, but it can be seen that when the normalized Doppler is not greater than 0.1, the impact of ICI on the target imaging performance is small; when the normalized Doppler is greater than 0.1, Figure 4 Targets 3, 4, and 5 in the image have higher side lobes in the range dimension, resulting in reduced imaging resolution.

[0132] Figure 5 The target range-velocity image of the repeated symbol algorithm. Figure 5 As can be seen in the figure, for targets 1, 2, and 3 (with speeds within the maximum unambiguous speed range), the algorithm can effectively suppress ICI, significantly reducing the range-dimension sidelobe amplitude. However, for targets 4 and 5 (with speeds exceeding the maximum unambiguous speed), ICI is not effectively suppressed, and high sidelobes exist in the range dimension, which also leads to reduced imaging resolution.

[0133] Figure 6 is the target range-speed image of the ICI suppression algorithm of the present invention. Figure 6 Effective ICI suppression is achieved for all targets (including those exceeding the maximum unambiguous speed). The sidelobe amplitudes of all targets in the range dimension are significantly reduced, improving target imaging resolution. Furthermore, the velocity ambiguity estimates for all targets are 0, 0, 0, -1, and 1, respectively. This demonstrates that the inter-carrier interference suppression method described in this embodiment can simultaneously address both ICI and velocity ambiguity issues.

[0134] Figure 7 Figure 2 shows the peak sidelobe ratio (PSLR) of the three algorithms at different normalized Dopplers, with a simulation count of 1000. It can be seen that the PSLR of the 2D-DFT algorithm decreases significantly with increasing normalized Doppler, especially in the region where the normalized Doppler is greater than 0.1. The repeated symbol algorithm can maintain a high PSLR only within the unambiguous velocity range, with performance dropping sharply beyond this range. The ICI mitigation algorithm described in this embodiment maintains a relatively stable PSLR across the entire Doppler range, demonstrating its robustness to Doppler shifts.

[0135] Therefore, compared with the existing 2D-DFT algorithm and repeated symbol algorithm, the inter-carrier interference suppression method described in this embodiment can be applied to the integrated millimeter-wave vehicle-mounted radar communication scenario, especially in high-dynamic scenarios. It solves the inter-carrier interference problem caused by high dynamics without sacrificing the communication rate and unambiguous distance, and at the same time realizes unambiguous estimation of target speed, which obviously has great application value.

[0136] Based on the disclosure and teachings of the above description, those skilled in the art may also make changes and modifications to the above embodiments. Therefore, the present invention is not limited to the specific embodiments disclosed and described above, and modifications and variations of the present invention should also fall within the scope of protection of the claims of the present invention. In addition, although certain specific terms are used in this description, these terms are only for convenience of description and do not constitute any limitation to the present invention.

Claims

1. A method for suppressing inter-carrier interference based on an OFDM radar communication integrated system, characterized in that: The inter-carrier interference suppression method comprises the following steps: Step S1: First construct an OFDM radar communication integrated transmission signal; Step S2: A target is preset at a distance r and has a radial velocity v. The OFDM radar communication integrated signal is transmitted toward the target. After reflection from the target, the target echo signal is obtained. The received target echo signal is sequentially down-converted, sampled, and cyclic prefix removed, and described in matrix form. Step S3: Perform 2D-DFT processing on the signal described in matrix form in step S2 to obtain the original range-velocity image of the target; Step S4: unambiguous velocity estimation based on multi-hypothesis velocity compensation; Step S5: estimation of target scattering coefficient; Step S6: Using the estimated target scattering coefficient, reconstruct the target signals with and without ICI; then perform 2D-DFT processing on the target signal without ICI to obtain the target range-velocity image without ICI.

2. The method for suppressing inter-carrier interference according to claim 1, wherein: In step S1, the OFDM radar communication integrated transmission signal is expressed by formula (1), which is: Among them, N c is the number of subcarrier frequencies, N s is the number of OFDM symbols, A n，m is the communication data on the mth OFDM symbol of the nth subcarrier frequency; j is the imaginary unit, t is the time, f c is the carrier frequency; T s =T+T g Represents a complete OFDM symbol period, T1 / Δf is the effective OFDM symbol period, Δf is the subcarrier frequency interval, T g is the cyclic prefix period; rect(t) is the unit rectangular window function, when 0<t<T s 1 when t≤0 or t≥T s Time is 0.

3. The method for suppressing inter-carrier interference according to claim 2, wherein: In step S2, the target scattering coefficient is α, the target normalized delay is represented by τ=2rΔf / c, and the normalized Doppler shift is represented by f d =2vTf c / c, where c is the speed of light; After the OFDM radar communication integrated signal is reflected by the target, the received target echo signal is processed by down-conversion, sampling and cyclic prefix removal, and is expressed by formula (2), which is as follows: Where i∈, N c -1] is the fast time, m∈[0, N s -1] is the slow time, ρ=αexp(-j2πf c τT), β=T s / T; In formula (2), the second exponential term exp(-j2πnτ) contains the time delay information, which is used for distance estimation; the last two exponential terms contain Doppler information, exp(j2πmf d β) is the Doppler information between symbols, which is used for velocity estimation; It is the ICI generated by Doppler, which raises the range image sidelobes.

4. The method for suppressing inter-carrier interference according to claim 3, wherein: In step S2, formula (2) is described in matrix form and expressed by formula (3), which is as follows: In formula (3), is the modulation symbol matrix at the transmitter, is the ICI generated by Doppler, and the other parameters are expressed by formulas (4), (5), and (6), which are as follows: Where, diag[·] represents a diagonal matrix, * represents conjugation, and F N is the N×N DFT matrix, is an N×N IDFT matrix.

5. The method for suppressing inter-carrier interference according to claim 4, wherein: In step S3, the 2D-DFT processing refers to performing the following processing on formula (3) in step S2: Step S3a: Perform DFT processing on the fast time domain to obtain the frequency domain signal on each subcarrier; Step S3b: Matrix division is used to eliminate the influence of communication data on radar performance; Step S3c: velocity-dimensional DFT processing to obtain a velocity image; Step S3d: Perform distance-dimensional IDFT processing to obtain a range image.

6. The method for suppressing inter-carrier interference according to claim 5, wherein: The 2D-DFT process is expressed by formula (7), which is as follows: Where G represents the original range-velocity image of the target.

7. The method for suppressing inter-carrier interference according to claim 4, wherein: In step S4, When the target's true speed v a Greater than the maximum unambiguous speed v max When v a The calculation of is expressed by formula (8), which is: v a =v0+2ξv max (8); Among them, v0 is the fuzzy estimate of the target's true speed, v max =c / (4f c T s ) is the maximum unambiguous velocity of the radar, and ξ is the velocity ambiguity number; then the ICI generated by the target Doppler in formula (3) satisfies the following formula (9): Among them, f d (v a )=2f c v a T / c,f d (v0)=2f c v0T / c.

8. The method for suppressing inter-carrier interference according to claim 7, wherein: In the step S4, the following steps are also included: Step S4a: Set the value range of the velocity ambiguity number; assuming that ξ∈{-Z, -Z+1, ..., Z}, and Z is a positive integer, the maximum unambiguous velocity of the radar is from [-v max , v max ] increases to [-(2Z+1)v max , (2Z+1)v max ]; Step S4b: Construct compensation matrix D Nc (-ξ / (βN c )), between y and D Nc (-ξ / (βN c )) are multiplied to suppress the ICI generated by the target blur speed; then 2D-DFT processing is performed to obtain the compensated two-dimensional range-velocity image G(ξ). The above operation is expressed by formula (10), which is as follows: Step S4c: Target detection and unambiguous velocity estimation; G(ξ) is tested with constant false alarm rate to extract the distance and velocity index of potential targets; the target distance and velocity index set corresponding to all ξ detected by CFAR is expressed as The corresponding normalized delay and normalized Doppler sets are Among them, I is the set The number of elements in , that is, the number of detected targets, and I is a positive integer; Among them, the unambiguous velocity estimation adopts the maximum peak sidelobe ratio criterion of the range image; for each detected target, the PSLR corresponding to different ξ is compared to determine the one with the maximum PSLR. is the true fuzzy number of the target velocity to achieve unambiguous estimation of the target velocity.

9. The method for suppressing inter-carrier interference according to claim 6, wherein: In step S5, the following processing is included: Step S5a: Based on the previously detected target, the target signal value is extracted from G in formula (7), which is expressed by formula (11). The formula (11) is as follows: Step S5b: construct a target signal containing ICI and a target signal without ICI, which are respectively expressed by formulas (12) and (13). The formulas (12) and (13) are as follows: The target signal in formula (12) is processed by 2D-DFT to obtain the target range-velocity image, which is expressed by formula (14). Formula (14) is as follows: Then extract the target signal value and express it through formula (15), which is: Based on the mathematical relationship between formula (11) and formula (15), q can be expressed as The linear combination of Q is the target scattering coefficient; by solving the linear equations, the target scattering coefficient is obtained, which is expressed by formula (16). The formula (16) is: α=(Q T Q) -1 Q T q(16); Where T represents the transposition operation, α=[α0,α1,…,α I-1 ] T , 10. The method for suppressing inter-carrier interference according to claim 9, wherein: In step S6, The estimated target scattering coefficient is used to reconstruct the target signals with and without ICI. The ICI signal in the original received signal in formula (3) is replaced with the reconstructed ICI-free signal. Finally, the target echo after ICI suppression is obtained, which is expressed by formula (17). Formula (17) is as follows: y m Further 2D-DFT processing is performed to obtain the target range-velocity image without ICI.

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