CN116614161A - Radar communication integrated beam forming method based on linear constraint power distribution - Google Patents

Radar communication integrated beam forming method based on linear constraint power distribution Download PDF

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Publication number
CN116614161A
CN116614161A CN202310471127.0A CN202310471127A CN116614161A CN 116614161 A CN116614161 A CN 116614161A CN 202310471127 A CN202310471127 A CN 202310471127A CN 116614161 A CN116614161 A CN 116614161A
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radar
communication
matrix
user
beam forming
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刘亮
孙俊贤
甘露
廖红舒
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University of Electronic Science and Technology of China
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University of Electronic Science and Technology of China
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/0413—MIMO systems
    • H04B7/0426—Power distribution
    • H04B7/043—Power distribution using best eigenmode, e.g. beam forming or beam steering
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/03—Details of HF subsystems specially adapted therefor, e.g. common to transmitter and receiver
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/28—Details of pulse systems
    • G01S7/2813—Means providing a modification of the radiation pattern for cancelling noise, clutter or interfering signals, e.g. side lobe suppression, side lobe blanking, null-steering arrays
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/0413—MIMO systems
    • H04B7/0452—Multi-user MIMO systems
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

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  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Signal Processing (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Power Engineering (AREA)
  • Radio Transmission System (AREA)

Abstract

The invention belongs to the technical field of signal processing, and relates to a radar communication integrated beam forming method based on linear constraint power distribution. Firstly, constructing an MU-MIMO radar communication integrated system model, directly designing transmission covariance matrixes of a plurality of users, wherein the transmission covariance matrixes are required to meet radar pattern constraint, signal-to-noise-and-leakage-ratio maximization constraint and transmission power constraint, and performing rank-one decomposition on all the transmission covariance matrixes to obtain a beam forming weight vector. The beamforming weight vector obtained by the invention has no power loss before and after rank-one decomposition, and an effective radar communication integrated space power distribution effect is realized under a multi-user scene through a beamforming technology.

Description

Radar communication integrated beam forming method based on linear constraint power distribution
Technical Field
The invention belongs to the technical field of signal processing, and relates to a radar communication integrated beam forming method based on linear constraint power distribution.
Background
The number of devices in radar and communication systems in the society of today is increasing, wireless spectrum resources are increasingly tense, and the hardware cost of the devices is rising. In order to solve these problems, radar communication integration technology has become a mainstream research direction. As a cross problem of combining radar and communication, the radar communication integration technology is expected to achieve the goal of coexistence of radar detection and wireless communication by uniformly designing levels such as signals, channels and the like under the conditions of sharing resources such as frequency spectrum, energy, space, time and the like, and finally improve the frequency spectrum utilization efficiency and the system integration level.
The beam forming technology is a core technology in the field of array signal processing, and can realize space power distribution of a transmitted signal, when the beam forming technology is applied to the field of radar communication integration, a radar target can be regarded as a unit in a line-of-sight channel, a communication receiver is a unit in a non-line-of-sight channel, the radar communication integration problem can be regarded as a beam forming weight vector for designing a transmitting array, and space power distribution is carried out on each unit in the line-of-sight channel and the non-line-of-sight channel so as to simultaneously meet the requirements of a radar expected directional diagram and the communication performance of a communication user.
There are methods for spatial power allocation for radar and communication by beamforming technology, and a typical method is a multi-user multiple input multiple output (MU-MIMO) radar communication joint beamforming method, which aims at radar target detection and multi-user downlink communication scenes, and takes communication signals as radar detection signals. The MU-MIMO radar communication joint beam forming method comprises the steps of firstly designing a radar transmission covariance matrix meeting power constraint and radar pattern constraint, then designing a multi-user transmission covariance matrix meeting signal-to-interference-and-noise ratio constraint, and enabling the sum of all the user transmission covariance matrices to approach the radar transmission covariance matrix. However, the performance of the beam forming weight vector obtained after the covariance matrix rank-one decomposition of the method is greatly attenuated, and the method cannot be applied to an actual scene and cannot realize high-efficiency radar communication integration.
Disclosure of Invention
Aiming at the existing problems, the invention aims to provide an MU-MIMO radar communication integrated beam forming method based on linear constraint power distribution, and aims at radar target detection and multi-user downlink communication scenes, a multi-user transmission covariance matrix which simultaneously meets radar pattern constraint, signal to noise ratio (SLNR) constraint and transmission power constraint is designed, the covariance matrix designed by the invention has no power loss before and after rank decomposition, and a beam forming weight vector obtained after rank decomposition can be applied to actual scenes and can realize effective MU-MIMO radar communication integrated space power distribution effect.
In order to achieve the above object, the present invention adopts the following technical scheme:
a radar communication integrated beam forming method based on linear constraint power distribution considers an MU-MIMO radar communication integrated system, which comprises N t Uniform linear array emission array of each array element and N r Uniform linear array radar receiving array of each array element and K communication users provided with single antennas, wherein the number of radar expected main lobes is Q, and the expected main lobe is pointed to be theta q Q=1. The channel information between the communicating user and the transmitting array is accurately estimated and known by the transmitting end, comprising the steps of:
s1, adopting a communication signal as a radar detection signal, and receiving a signal y at an ith communication user i (t) is:
wherein t is a time parameter, and considering that a channel between a transmitting array and a single-antenna communication user is a flat Rayleigh fading channel, and H is KxN without losing generality t Channel matrix of dimension, h i I-th row of H. w (w) k Forming a weight vector, s, for a transmit beam of a kth user signal k (t) communication signal for kth user, n i And (t) is the received noise of the ith communication user.
Transmit covariance matrix for kth communication userThe transmit power P of the radar communication combination t The method comprises the following steps:
wherein, |·| represents the two norms of the vector, tr (·) represents the trace of the matrix.
S2, designing a multi-user transmission covariance matrix
For K communication users under non-line-of-sight channels, K user transmission covariance matrices W are required to be solved k K=1,..k, the transmission covariance matrix W of the kth communication user, K k To meet the received SLNR maximization constraint for the kth communication user while W k The corresponding radar transmit pattern needs to meet the desired radar pattern constraint and the sum of all transmit covariance matrices needs to meet the overall transmit power constraint. Consider the transmit power to be P 0 The number of main lobes of the radar expected directional diagram is Q, and the expected main lobe is pointed to be theta q Q=1,..q, the pattern is in the side lobe areaThe inner need is smaller than a preset sidelobe level p. The demand solution is the following optimization problem:
s.t.diag(G H W k G)＝f k
rank(W k )＝1
the above problem is a non-convex optimization problem, and the rank-one constraint can be ignored for solving. Wherein ( H Is conjugate transpose (.) T For transpose, diag (·) represents taking diagonal elements of the matrix side by side as column vectors. Alpha and epsilon are the power coefficients of the radar target and the communication user, respectively. Matrix g= [ C H ] H ]Wherein c= [ a (θ) 1 ) … a(θ Q )]，a(θ q ) Q=1,..q is the desired main lobe direction θ q And the corresponding steering vector, H, is a channel matrix. f (f) k ＝[f r,k f c,k ] T For power allocation vector, where f r,k Controlling radar target power, which is 1 XQ dimension elementLine vector f of (f) c,k The communication user power is controlled to be a row vector of 1 xk dimensions and K-th element is epsilon and the remaining elements are 0. Radar pattern sidelobe region->Presence of L s Angular sampling, a (θ l ) For sampling angle theta l Corresponding steering vectors. And (c) the sum is equal to or greater than half positive determination, and rank (·) is the rank of the matrix.
S3, decomposing the multi-user emission covariance matrix rank to obtain multi-user wave beam forming weight vector
Transmit covariance matrix W for K users k K=1,..k performs rank-one decomposition to obtain beamformed weight vectors w for K users k K=1,..k, K, with the transmission covariance matrix W of the kth user k For example, first to matrix W k Singular value decomposition is carried out to obtain:
wherein U is a matrix formed by singular vectors, and Λ is N t Singular values ofAnd forming an actual diagonal matrix. Taking the first column of matrix Λ and root-marking the first element to get vector σ:
the beam forming weight vector w of the kth user k Can be expressed as:
w k ＝Uσ
after K times rank one decomposition, beam forming weight vectors of K users are obtained, and the beam forming weight vectors contribute to the same weight vector w in the range of a radar main lobe k The received SLNR maximization for the kth user can be achieved while satisfying the transmit power constraint.
The method has the beneficial effects that the method for forming the MU-MIMO radar communication integrated beam based on linear constraint power distribution directly designs the transmission covariance matrixes of a plurality of users, the transmission covariance matrixes are required to meet radar pattern constraint, signal-to-noise ratio maximization constraint and transmission power constraint, and rank-one decomposition is carried out on all the transmission covariance matrixes to obtain a beam forming weight vector. The finally obtained beam forming weight vector has no power loss before and after rank-one decomposition, and can realize the effective radar target detection and space power distribution effect required by multi-user downlink communication.
Drawings
FIG. 1 is a flow chart of an implementation process of the present invention;
FIG. 2 is a schematic diagram of an MU-MIMO radar communication integrated system according to the present invention;
FIG. 3 is a diagram of a radar emission pattern and sub-patterns corresponding to each user obtained by the method of the present invention;
fig. 4 shows a comparison of a radar transmission pattern obtained by the method according to the present invention and a radar transmission pattern obtained by the method according to MU-MIMO radar communication joint beam forming method, (a) shows a radar transmission pattern obtained by the method according to the present invention, and (b) shows a radar transmission pattern obtained by the method according to MU-MIMO radar communication joint beam forming method.
Detailed Description
The technical scheme of the invention will be further described with reference to the accompanying drawings and the specific embodiments.
The aim of the embodiment is to simulate and verify the feasibility and effectiveness of the MU-MIMO radar communication integrated beam forming method based on linear constraint power distribution. The MU-MIMO radar communication integrated beam forming method based on linear constraint power distribution in the embodiment is shown in fig. 1, and a schematic diagram of the MU-MIMO radar communication integrated system constructed in the embodiment is shown in fig. 2. In the embodiment, the simulation condition is set to be the transmission power P 0 Noise power n=20 dBm 0 A uniform linear array with half-wavelength array element spacing of 0dBm is used as a transmitting array, and the number of transmitting array elements is N t =20. The radar expected directional diagram is a multi-main-lobe directional diagram, the number of expected main lobes Q=3, and the expected main lobe pointing to theta q ＝[-45° 0° 45°]Preset sidelobe level ρ= -10dB.
The radar emission pattern obtained by the method is shown in figure 3. The radar emission directional diagram obtained by the method achieves the purpose of the expected multi-main-lobe directional diagram, and successfully achieves control of main-lobe pointing and suppression of side lobe level. The sub-directional diagrams of all users are restrained by equal contribution, the sub-directional diagrams of all the users are effectively controlled to be in the same main lobe level, and side lobe levels are restrained. Therefore, the radar emission pattern obtained by the method and the sub-patterns of all users meet the expectations.
The radar emission directional diagram obtained by combining the method and the MU-MIMO radar communication combined beam forming method is shown in figure 4. It can be found that the performance of the radar pattern obtained by the method is not reduced before and after rank-one decomposition, and the power of the finally obtained beam forming weight vector is 20dBm, and the constraint of the transmitting power is still satisfied. The radar pattern rank-one decomposition front-rear performance obtained by the MU-MIMO radar communication combined beam forming method transmits larger attenuation, and the power of the finally obtained beam forming weight vector is 7.8032dBm and does not accord with the constraint of the transmitting power. The receiving SLNR of each user realized by the method provided by the invention reaches 22.9668dB, thereby meeting the communication requirement. In summary, the beamforming weight vector obtained by the invention can effectively realize the space power distribution effect required by radar target detection and multi-user downlink communication, always meets the transmitting power constraint, and is more beneficial to being applied in actual scenes.

Claims (1)

1. Radar communication integrated beam forming method based on linear constraint power distribution and used for MU-MIMO radar communication integrated system, wherein the definition system comprises N t Uniform linear array emission array of each array element and N r Uniform linear array radar receiving array of each array element and K communication users provided with single antennas, wherein the number of radar expected main lobes is Q, and the expected main lobe is pointed to be theta q Q=1, Q, the channel information between the communicating user and the transmitting array being accurately estimated and known to the transmitting end, characterized in that the beamforming method comprises the steps of:
s1, adopting a communication signal as a radar detection signal to define a received signal y at an ith communication user i (t) is:
wherein t is a time parameter, h i The ith row of H, H is KXN t Channel matrix of dimension, w k Forming a weight vector, s, for a transmit beam of a kth user signal k (t) communication signal for kth user, n i (t) is the reception noise of the ith communication user;
transmit covariance matrix for kth communication userThe transmit power P of the radar communication combination t The method comprises the following steps:
wherein, |·| represents the two norms of the vector, tr (·) represents the trace of the matrix;
s2, obtaining a multi-user transmission covariance matrix by solving the following optimization problem:
s.t.diag(G H W k G)＝f k
rank(W k )＝1
wherein ,(·)H Is conjugate transpose (.) T For transposition, diag (·) represents taking diagonal elements of a matrix side by side as column vectors, α and ε are power coefficients of a radar target and a communication user, respectively, and the matrix g= [ C H ] H ]Wherein c= [ a (θ) 1 ) … a(θ Q )]，a(θ q ) To the desired main lobe direction theta q The corresponding steering vector, q=1, Q, H is a channel matrix, f k ＝[f r,k f c,k ] T For power allocation vector, where f r,k Controlling radar target power to be 1 XQ dimension elementLine vector f of (f) ck Controlling communication user power to be 1 XK dimension line directionThe k element is epsilon, and the rest elements are 0; p (P) 0 For the transmit power, ρ is the preset sidelobe level, radar pattern sidelobe region +.>Presence of L s Angular sampling, a (θ l ) For sampling angle theta l A corresponding steering vector; more than or equal to the sum of the two values, wherein the sum of the two values is equal to or greater than the sum of the two values;
s3, transmitting covariance matrix W of K users k Performing rank first decomposition to obtain beam forming weight vectors w of K users k K=1,..k, transmit covariance matrix W for the kth user k First to matrix W k Singular value decomposition is carried out to obtain:
wherein U is a matrix formed by singular vectors, and Λ is N t Singular values ofA real diagonal matrix is formed; taking the first column of matrix Λ and root-marking the first element to get vector σ:
the beam forming weight vector w of the kth user k Expressed as:
w k ＝Uσ
after K times rank one decomposition, beam forming weight vectors of K users are obtained, and the beam forming weight vectors contribute to the same weight vector w in the range of a radar main lobe k The received SLNR maximization for the kth user is achieved while satisfying the transmit power constraint.
CN202310471127.0A 2023-04-27 2023-04-27 Radar communication integrated beam forming method based on linear constraint power distribution Pending CN116614161A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117411524A (en) * 2023-10-17 2024-01-16 华中科技大学 Method and device for determining radar communication integrated transmitting signals

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117411524A (en) * 2023-10-17 2024-01-16 华中科技大学 Method and device for determining radar communication integrated transmitting signals

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