CN115015918A - Broadband MIMO radar directional diagram obtaining method and device, electronic equipment and storage medium - Google Patents

Broadband MIMO radar directional diagram obtaining method and device, electronic equipment and storage medium Download PDF

Info

Publication number
CN115015918A
CN115015918A CN202210305599.4A CN202210305599A CN115015918A CN 115015918 A CN115015918 A CN 115015918A CN 202210305599 A CN202210305599 A CN 202210305599A CN 115015918 A CN115015918 A CN 115015918A
Authority
CN
China
Prior art keywords
function expression
sampling signal
expression
function
constraint condition
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN202210305599.4A
Other languages
Chinese (zh)
Other versions
CN115015918B (en
Inventor
巩朋成
吴云韬
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Wuhan Institute of Technology
Original Assignee
Wuhan Institute of Technology
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Wuhan Institute of Technology filed Critical Wuhan Institute of Technology
Priority to CN202210305599.4A priority Critical patent/CN115015918B/en
Publication of CN115015918A publication Critical patent/CN115015918A/en
Application granted granted Critical
Publication of CN115015918B publication Critical patent/CN115015918B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • 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
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/88—Radar or analogous systems specially adapted for specific applications
    • G01S13/89—Radar or analogous systems specially adapted for specific applications for mapping or imaging
    • 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
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/88—Radar or analogous systems specially adapted for specific applications
    • G01S13/93—Radar or analogous systems specially adapted for specific applications for anti-collision purposes
    • G01S13/931—Radar or analogous systems specially adapted for specific applications for anti-collision purposes of land vehicles
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G06F17/15—Correlation function computation including computation of convolution operations

Abstract

The invention relates to a method for acquiring a directional diagram of a broadband MIMO radar, which comprises the following steps: acquiring a sampling signal and a first function expression of a first direction graph; converting the first function expression based on the L1 norm to determine a second function expression; converting the second function expression into a third function expression containing a sampling signal sequence corresponding to the sampling signal, and determining a fourth function expression meeting PAPR constraint conditions and sidelobe control constraint conditions; converting the fourth function expression into a convex function; solving a fifth function expression in an iterative solution mode to obtain a target sampling signal sequence; determining a guide vector and a frequency domain signal; and determining a second directional diagram according to the steering vector, the frequency domain signal and the second function expression. The invention realizes the control of the main lobe to obtain the expected directional diagram; the null suppression effect of the expected space-frequency area of the radar beam directional diagram is realized, and the radar clutter interference suppression capability is improved.

Description

Broadband MIMO radar directional diagram obtaining method and device, electronic equipment and storage medium
Technical Field
The invention belongs to the technical field of radars, and particularly relates to a method and a device for acquiring a broadband MIMO radar directional diagram, electronic equipment and a storage medium.
Background
Compared with phased array and narrow-band multiple-input multiple-output (MIMO) radars, wideband MIMO radars have received more and more attention, and have been applied to automotive radars due to performance advantages such as higher resolution and parameter estimation in the range direction. However, the pattern of a wideband MIMO radar is also frequency dependent, with the main lobe width inversely proportional to frequency, i.e. the main lobe width narrows as frequency increases; in addition, radio signals generated by the automobile radar are mainly Frequency Modulated Continuous Wave (FMCW), and when a plurality of automobile radars in the same frequency band work in the same area, radio harmful interference can be generated among the automobile radars.
The norm indicates a degree of increase or a magnitude which is not zero in all vectors in a vector space, and different norms are given to all vectors, and the lengths or magnitudes of the vectors to be calculated are different. The L1 norm represents the sum of the absolute values of each element in the vector, and the L2 norm represents the sum of the squares of the individual elements in the weight vector and then the square root. In the process of fitting the training data by the function model, the complexity of the model is increased because of too many parameters, and overfitting is easy to occur, namely the training error is very small, so that the testing error of the model is large; utilize L1 norm and L2 norm to function model conversion can both prevent function model overfitting, compare in L2 norm, utilize L1 norm to function model conversion can keep the characteristics of function model sparse distribution.
In addition, radio signals generated by the automobile radar are mainly Frequency Modulated Continuous Wave (FMCW), and when a plurality of automobile radars in the same frequency band work in the same area, radio harmful interference can be generated among the automobile radars; when the peak-to-average ratio (PAPR) of a transmit waveform is large, the amplitude of the transmit signal fluctuates widely, possibly causing nonlinear distortion of the waveform.
In practice, the problem that a main lobe of a broadband MIMO radar transmitting signal cannot acquire an expected directional diagram exists, null suppression in an expected space-frequency region cannot be achieved, and radar clutter interference suppression capability is greatly influenced.
Disclosure of Invention
The invention provides a broadband MIMO radar directional diagram obtaining method, which aims to solve the problems that a main lobe cannot be matched with an expected directional diagram, the amplitude fluctuation of a transmitted signal is large, and null suppression of an expected space-frequency region cannot be realized.
The technical scheme for solving the technical problems is as follows:
the method for acquiring the directional diagram of the broadband MIMO radar comprises the following steps:
in a first aspect, the present disclosure provides a radar beam pattern acquisition method, including the steps of:
acquiring a sampling signal and a first function expression of a first direction graph; the first function expression is used for representing the relation among the steering vector of the sampling signal, the frequency domain signal and the first direction diagram;
converting the first function expression based on the L1 norm, and determining a second function expression of the first direction diagram;
converting the second function expression into a third function expression containing a sampling signal sequence corresponding to the sampling signal, and determining a fourth function expression meeting the PAPR constraint condition and the sidelobe control constraint condition according to the PAPR constraint condition, the sidelobe control constraint condition and the third function expression;
converting the fourth function expression into a convex function, and taking the convex function as a fifth function expression;
solving the fifth function expression in an iterative solution mode to obtain a target sampling signal sequence which enables the first direction diagram to meet a preset convergence condition;
determining the steering vector and the frequency domain signal according to the target sampling signal sequence;
and determining a second directional diagram according to the steering vector, the frequency domain signal and the second function expression.
In a second aspect, the present disclosure provides a radar beam pattern obtaining apparatus, including:
the first expression determining unit is used for acquiring the sampling signal and a first function expression of a first direction graph; the first function expression is used for representing the relation among the steering vector of the sampling signal, the frequency domain signal and the first direction diagram;
the first conversion unit is used for converting the first function expression based on the L1 norm and determining a second function expression of the first direction graph;
a second expression determining unit, configured to convert the second function expression into a third function expression including a sampling signal sequence corresponding to the sampling signal, and determine a fourth function expression satisfying a PAPR constraint condition and a sidelobe control constraint condition according to the PAPR constraint condition, the sidelobe control constraint condition, and the second function expression;
the second conversion unit is used for converting the fourth function expression into a convex function, and taking the convex function as a fifth function expression;
the iteration unit is used for solving the fifth function expression in an iteration solving mode to obtain a target sampling signal sequence which enables the first direction diagram to meet a preset convergence condition;
a first determining unit, configured to determine the steering vector and the frequency domain signal according to the target sampling signal sequence;
and the second determining unit is used for determining a second directional diagram according to the steering vector, the frequency domain signal and the second function expression.
In a third aspect, the present disclosure provides an electronic device, comprising:
a processor and a memory;
the memory is used for storing computer operation instructions;
the processor is used for executing the radar beam pattern obtaining method by calling the computer operation instruction.
In a fourth aspect, the present disclosure provides a storage medium having stored thereon computer instructions, the computer storage medium having stored thereon at least one instruction, at least one program, set of codes, or set of instructions, which is loaded and executed by the processor to implement the radar beam pattern acquisition method.
The invention has the beneficial effects that: according to the invention, through the PAPR constraint condition and the sidelobe control constraint condition, the amplitude control of the radar beam directional pattern is realized; based on the L1 norm, a sampling signal sequence is obtained in an iterative solution mode, a radar beam directional diagram is obtained through the sampling signal sequence, and control of obtaining an expected directional diagram through a main lobe is achieved; the null suppression effect of the expected space-frequency area of the radar beam directional diagram is realized, and the radar clutter interference suppression capability is improved.
On the basis of the technical scheme, the invention can be further improved as follows.
Further, the first functional expression is determined by:
acquiring a sampling signal of a baseband signal and a guide vector of an antenna array;
performing discrete Fourier transform on the sampling signal of the baseband signal to obtain a frequency domain signal;
and determining a first function expression of the first direction diagram according to the steering vector of the antenna array and the frequency domain signal.
The method has the advantage that the first function expression of the first direction diagram of the radar beam transmission signal is accurately obtained.
Further, the converting, according to the PAPR constraint condition, the sidelobe control constraint condition, and the second function expression, the second function expression into a third function expression including a sampling signal sequence corresponding to the sampling signal, and determining a fourth function expression satisfying the PAPR constraint condition and the sidelobe control constraint condition includes:
acquiring the PAPR constraint condition and the sidelobe control constraint condition;
converting the second function expression into a third function expression containing a sampling signal sequence corresponding to the sampling signal;
converting the PAPR constraint condition under the condition that the total emission energy is 1 to obtain the converted PAPR constraint condition;
and determining a fourth function expression meeting the PAPR constraint condition and the sidelobe control constraint condition according to the converted PAPR constraint condition, the sidelobe control constraint condition and the third function expression.
The further scheme has the advantages that the amplitude fluctuation control of the transmitted signal is realized by setting the PAPR constraint condition, and the nonlinear waveform distortion caused by the large-range amplitude fluctuation of the transmitted signal is avoided; by setting a side lobe control constraint condition, radar clutter interference is reduced.
Further, the method also includes:
converting the fifth function expression by using a preset intermediate variable to obtain a sixth function expression; the sixth functional expression is used for representing the relation between the intermediate variable and the first direction diagram, and the intermediate variable is used for representing the relation between the sampling signal sequence and the guide vector;
the solving the fifth function expression in an iterative solution manner to obtain a target sampling signal sequence which enables the first direction graph to meet a preset convergence condition includes:
and solving the sixth function expression in an iterative solution mode to obtain a target sampling signal sequence which enables the first direction diagram to meet a preset convergence condition.
The method has the advantages that the second function expression is converted through the intermediate variable, and the second function expression is converted into the solvable convex function.
Further, the solving the sixth function expression in an iterative solution manner to obtain a target sampling signal sequence which enables the first direction diagram to satisfy a preset convergence condition includes:
constructing an augmented Lagrangian function of the sixth function expression;
solving an intermediate variable in the augmented Lagrange function by using a parallel iteration mode based on an ADMM method;
and determining the target sampling signal sequence according to the intermediate variable obtained by solving.
The beneficial effect of adopting the further scheme is that the sampling signal sequence meeting the convergence condition can be obtained by an iterative solution mode.
Drawings
FIG. 1 is a flow chart of a method of obtaining a wideband MIMO radar pattern in accordance with the present invention;
FIG. 2 is a diagram of a wideband MIMO radar antenna array (ULA) of the present invention;
FIG. 3 is a schematic diagram of an apparatus for obtaining a directional diagram of a broadband MIMO radar according to the present invention;
fig. 4 is a schematic diagram of an electronic device according to embodiment 3;
FIG. 5 is a graph of the variation of residual error with iteration number in experiment one;
fig. 6(a) is a simulation diagram of a waveform pattern in the first experiment when PAPR is 1.0;
fig. 6(b) is a simulation diagram of the waveform pattern in the first experiment when the PAPR is 1.5;
fig. 7(a) is a 3D simulation diagram of a directional diagram obtained in experiment two when the design waveform PAPR is 1;
fig. 7(b) is a 2D simulation diagram of a directional diagram obtained by setting PAPR 1 as a design waveform in experiment two;
fig. 8(a) is a 3D simulation diagram of a directional diagram obtained by setting the PAPR 1.5 in the second experiment;
fig. 8(b) is a 2D simulation diagram of a directional diagram obtained by setting the PAPR of the design waveform to 1.5 in experiment two.
In the figure: q1-first residual variation curve; q2-second residual variation curve; q3-third residual variation curve; q4-fourth residual variation curve; q5-fifth residual variation curve; q6-sixth residual variation curve; d1-null region formed by the pattern with PAPR 1 in experiment one; d2-null region formed by the pattern with PAPR 1.5 in experiment one; d3 and D4-null region formed by the pattern with PAPR 1 in experiment II; d5 and D6 — null region formed by the pattern with PAPR 1.5 in experiment two.
Detailed Description
Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present disclosure are shown in the drawings, it is to be understood that the present disclosure may be embodied in various forms and should not be construed as limited to the embodiments set forth herein, but rather are provided for a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the disclosure are for illustration purposes only and are not intended to limit the scope of the disclosure.
In practice, the problem that a main lobe of a broadband MIMO radar transmitting signal cannot acquire an expected directional diagram exists, null suppression in an expected space-frequency region cannot be achieved, and radar clutter interference suppression capability is greatly influenced.
The technical solutions of the present disclosure and how to solve the above technical problems are described in detail below with specific embodiments, and the examples are only used for explaining the present invention and are not used for limiting the scope of the present invention. The following several specific embodiments may be combined with each other, and details of the same or similar concepts or processes may not be repeated in some embodiments. Embodiments of the present disclosure will be described below with reference to the accompanying drawings.
Example 1
As an embodiment, as shown in fig. 1, to solve the above technical problem, this embodiment provides a Wideband MIMO radar pattern obtaining method, that is, a Wideband pattern matching design (Wideband antenna matching design, L) with L1 norm 1 -WBMD) method comprising the following steps:
acquiring a sampling signal and a first function expression of a first direction graph; the first function expression is used for representing the relation among the steering vector of the sampling signal, the frequency domain signal and the first direction diagram;
converting the first function expression based on the L1 norm, and determining a second function expression of the first direction graph;
converting the second function expression into a third function expression containing a sampling signal sequence corresponding to the sampling signal, and determining a fourth function expression meeting the PAPR constraint condition and the sidelobe control constraint condition according to the PAPR constraint condition, the sidelobe control constraint condition and the second function expression;
converting the fourth function expression into a convex function, and taking the convex function as a fifth function expression;
solving a fifth function expression in an iterative solution mode to obtain a target sampling signal sequence which enables the first direction graph to meet a preset convergence condition;
determining a guide vector and a frequency domain signal according to a target sampling signal sequence;
and determining a second directional diagram according to the steering vector, the frequency domain signal and the second function expression.
According to the invention, through the PAPR constraint condition and the sidelobe control constraint condition, the amplitude control of the radar beam directional pattern is realized; based on the L1 norm, a sampling signal sequence is obtained in an iterative solution mode, a radar beam directional diagram is obtained through the sampling signal sequence, and control of obtaining an expected directional diagram through a main lobe is achieved; the null suppression effect of the expected space-frequency area of the radar beam directional diagram is realized, and the radar clutter interference suppression capability is improved.
Optionally, the first functional expression is determined by:
acquiring a sampling signal of a baseband signal and a guide vector of an antenna array;
performing discrete Fourier transform on a sampling signal of the baseband signal to obtain a frequency domain signal;
and determining a first function expression of the first direction diagram according to the steering vector of the antenna array and the frequency domain signal.
In practical application, in this embodiment, M transmitting antennas are configured to form a uniform linear array through the MIMO radar system, as shown in fig. 2, the wideband MIMO radar is according to a linear antenna array (ULA) diagram, the wideband MIMO radar system forms a uniform linear array by M transmitting antennas, an array spacing is set to be d, and a transmitting signal z is transmitted on each antenna m (t) is derived from the baseband signal x m (t) via carrier frequency f c Is prepared by
Figure RE-GDA0003776430150000081
z 0 (t) is a transmission signal of the 1 st transmission antenna, z M-1 And (t) is a transmission signal of the Mth transmission antenna. Suppose a baseband signal x m (t) has a frequency spectrum of y m (f) Wherein the frequency range is f E [ -B/2, B/2]And B is the bandwidth of the baseband signal. In practical application, the time and the angle need to be discretizedProcessing, so that the baseband signal x m (t) sampling signal x m (n) is:
x m (n)＝x m (t＝nT s ) N is 0, …, N-1, where N is the number of samples, T S Is a symbol period, satisfies T s ＝1/B；
Discrete Fourier transform of sampled signal to y m (p)：
Figure RE-GDA0003776430150000082
Where the number of samples N is an even number.
Let a kp Is a direction guide vector, y p For frequency domain signals, the discretized space angle is theta k Carrier frequency of f c Discretized spatial angle θ k Is in the range of [0 DEG, 180 DEG ]]To obtain a set of discrete spatial angles
Figure RE-GDA0003776430150000083
Figure RE-GDA0003776430150000084
Is the number of discrete points of the space angle, defines the discretized space angle theta k Frequency of
Figure RE-GDA0003776430150000085
The wideband MIMO radar beam pattern at is:
Figure RE-GDA0003776430150000086
wherein, (.) H Representing a conjugate transpose.
Converting the target function into a function of a quadratic term, wherein quadratic equality constraint and quadratic inequality constraint are converted into affine equality constraint and linear inequality constraint respectively:
Figure RE-GDA0003776430150000091
y p ＝[y 0 (p),y 1 (p),…,y m (p),…,y M-1 (p)] T ；
wherein, tau m ＝md cosθ k /c,(m＝0,…M-1)，τ m For propagation delay between different antennas, c is the propagation velocity of the incident wave, d represents the distance between two array elements, y p Representing a frequency signal, y M-1 (p) represents the M-1 frequency signal.
And converting the first function expression based on the L1 norm, and determining a second function expression of the first direction graph:
Figure RE-GDA0003776430150000092
optionally, the converting the second function expression into a third function expression including a sampling signal sequence corresponding to the sampling signal, and determining a fourth function expression satisfying a PAPR constraint condition and a sidelobe control constraint condition according to the PAPR constraint condition, the sidelobe control constraint condition, and the second function expression includes:
obtaining PAPR constraint conditions and sidelobe control constraint conditions;
converting the second function expression into a third function expression containing a sampling signal sequence corresponding to the sampling signal;
converting the PAPR constraint condition under the condition that the total emission energy is 1 to obtain the converted PAPR constraint condition;
and determining a fourth function expression meeting the PAPR constraint condition and the sidelobe control constraint condition according to the converted PAPR constraint condition, the sidelobe control constraint condition and the third function expression.
In the practical application process, the amplitude of the transmitted signal fluctuates in a large range, which may cause waveform nonlinear distortion, so the transmitted waveform should have a low PAPR; in addition, low peak side lobe levels (PSLs) are required to reduce radar clutter interference, and therefore, the embodiments of the present invention consider wideband MIMO radar beam patterns under PAPR and side lobe control constraints.
The PAPR constraint and the sidelobe control constraint are:
θ k ∈Θ KL (k＝1,...,K)；
Figure RE-GDA0003776430150000101
PAPR(x)≤η，η∈[1，MN]；
wherein, theta k ∈Θ KL (K1.., K) denotes a main lobe region, θ s ∈Θ SL (S1.., S) denotes a side lobe region, where K denotes a maximum discrete number of a main lobe region; s represents the maximum discrete number of the sidelobe region;
and is
Figure RE-GDA0003776430150000102
Indicating compression of the side lobe below δ, θ s ∈Θ SL The PAPR constraint is expressed and the PAPR is defined as:
Figure RE-GDA0003776430150000103
wherein, | | | represents a 2-norm.
Let x be the sampling signal sequence, and x (n) be the sampling signal;
converting the second functional expression into a third functional expression containing a sampling signal sequence corresponding to the sampling signal:
Figure RE-GDA0003776430150000104
setting:
Figure RE-GDA0003776430150000105
Figure RE-GDA0003776430150000106
denotes the kronecker product, I M Is an M × M identity matrix, x (n) ═ x 0 (n),x 1 (n),…,x m (n),…,x M-1 (n)] T ，
Figure RE-GDA0003776430150000107
α sp Representing a guide vector, d kp Indicating that waveform x approaches the desired radar beam desired pattern in the main lobe region.
PAPR conversion: under the condition that the total transmitted energy is 1, the PAPR constraint is re-expressed as:
Figure RE-GDA0003776430150000108
wherein the content of the first and second substances,
Figure RE-GDA0003776430150000109
E n (i, j) is the (i, j) th element;
combining wideband MIMO radar beam pattern conversion and PAPR conversion, the fourth function expression is as follows:
Figure RE-GDA0003776430150000111
Figure RE-GDA0003776430150000112
by setting PAPR constraint conditions, the amplitude fluctuation control of the transmitted signal is realized, and the nonlinear waveform distortion caused by the large-range fluctuation of the amplitude of the transmitted signal is avoided; by setting a side lobe control constraint condition, radar clutter interference is reduced.
Let s r Representing a real signal comprising a baseband signal,
Figure RE-GDA0003776430150000113
a transformation matrix is represented that is,
Figure RE-GDA0003776430150000114
the intermediate matrix is represented by a matrix of,
Figure RE-GDA0003776430150000115
it is shown that,
Figure RE-GDA0003776430150000116
represents a real matrix comprising an identity matrix and a zero vector, (. cndot.) H Represents a conjugate transpose; due to l 1 Norm objective function and PAPR constraint, the above equation is non-convex, and is first transformed into a solvable real-valued optimization problem:
order to
Figure RE-GDA0003776430150000117
The fifth functional expression is:
Figure RE-GDA0003776430150000118
Figure RE-GDA0003776430150000119
optionally, the method further includes:
converting the fifth function expression by using a preset intermediate variable to obtain a sixth function expression; the sixth function expression is used for representing the relation between an intermediate variable and the first direction diagram, and the intermediate variable is used for representing the relation between the sampling signal sequence and the guide vector;
introduction of an auxiliary variable, h r 、
Figure RE-GDA00037764301500001110
Is provided with
Figure RE-GDA00037764301500001111
Represents a real matrix containing only 0 and 1; let h r ＝s r ，
Figure RE-GDA00037764301500001112
The fifth functional expression is converted into a sixth functional expression:
Figure RE-GDA0003776430150000121
Figure RE-GDA0003776430150000122
Figure RE-GDA0003776430150000123
let the sixth expression be
Figure RE-GDA0003776430150000124
Let Θ (h) r )、Φ(s r ) As an auxiliary matrix, then:
Figure RE-GDA0003776430150000125
||·|| 1 represents 1 norm operation, (·) T Representing a transpose operation, let Θ be kp (h r ) Representing the transposition of auxiliary variables and multiplication of transformation matrices, phi kp (s r ) Representing the multiplication of auxiliary variable transposition and transformation matrix transposition;
wherein, theta (h) r )＝[Θ 11 (h r )；Θ 12 (h r )；…；Θ 1N (h r )；Θ 2N (h r )；…Θ kp (h r )；…；Θ KN (h r )]And is and
Figure RE-GDA0003776430150000126
Φ(s r )＝[Φ 11 (s r )；Φ 12 (s r )；…；Φ 1N (s r )；Φ 2N (s r )；…Φ kp (s r )；…；Φ KN (s r )]and is and
Figure RE-GDA0003776430150000127
optionally, solving the sixth function expression in an iterative solution manner to obtain a target sampling signal sequence enabling the first direction graph to satisfy a preset convergence condition, where the method includes:
constructing an augmented Lagrangian function of a sixth function expression;
based on an ADMM method, solving an intermediate variable in an augmented Lagrange function by using a parallel iteration mode;
and determining a target sampling signal sequence according to the intermediate variable obtained by solving.
In the practical application process, let mu r It is possible to represent the auxiliary variable,
Figure RE-GDA0003776430150000128
it is possible to represent the auxiliary variable,
Figure RE-GDA0003776430150000129
representing an auxiliary variable;
based on the ADMM framework, the augmented Lagrangian function translates into:
Figure RE-GDA00037764301500001210
wherein ρ > 0 is a penalty parameter;
the augmented lagrangian function of the sixth functional expression translates to:
Figure RE-GDA0003776430150000131
Figure RE-GDA0003776430150000132
solving the obtained above formula by loop iteration by using an ADMM method:
is provided with
Figure RE-GDA0003776430150000133
Denotes s r The initial value for the m-th iteration,
Figure RE-GDA0003776430150000134
represents μ r The initial value for the m-th iteration,
Figure RE-GDA0003776430150000135
denotes v r The initial value for the m-th iteration,
Figure RE-GDA0003776430150000136
the auxiliary variable is represented by a number of variables,
Figure RE-GDA0003776430150000137
a transformation matrix is represented that is,
Figure RE-GDA0003776430150000138
to represent
Figure RE-GDA0003776430150000139
The value after the m-th iteration,
Figure RE-GDA00037764301500001310
to represent
Figure RE-GDA00037764301500001311
The value after the mth iteration; according to the m-th iteration value
Figure RE-GDA00037764301500001312
Solving for h m+1 ：
Order to
Figure RE-GDA00037764301500001313
The augmented lagrange function translates into:
Figure RE-GDA00037764301500001314
Figure RE-GDA00037764301500001315
by using the ADMM method, an auxiliary variable b is introduced 1 Let m denote the number of outer iterations, n denote the number of inner iterations,
Figure RE-GDA00037764301500001316
representing the result after iterative update to obtain
Figure RE-GDA00037764301500001317
Expression (c):
Figure RE-GDA00037764301500001318
Figure RE-GDA00037764301500001319
Figure RE-GDA00037764301500001320
repeated iterative update
Figure RE-GDA00037764301500001321
To obtain
Figure RE-GDA00037764301500001322
Is provided with
Figure RE-GDA00037764301500001323
Initial value of (2)
Figure RE-GDA00037764301500001324
Initial value of (2)
Figure RE-GDA00037764301500001325
The penalty value parameter p is a function of,
Figure RE-GDA00037764301500001326
to represent
Figure RE-GDA00037764301500001327
The value after the mth iteration, the initialization iteration number n is 0, and an initial value is set
Figure RE-GDA00037764301500001328
And rho;
s11: according to
Figure RE-GDA00037764301500001329
Is obtained by the expression
Figure RE-GDA00037764301500001330
S12: according to
Figure RE-GDA00037764301500001331
Is obtained by the expression
Figure RE-GDA00037764301500001332
S13: according to
Figure RE-GDA00037764301500001333
Is updated by the expression of
Figure RE-GDA00037764301500001334
S14: repeating the iteration steps S11-S13, setting the iteration times T1, and outputting after the iteration is finished
Figure RE-GDA0003776430150000141
S15 according to the iteration value
Figure RE-GDA0003776430150000142
Solving for
Figure RE-GDA0003776430150000143
Is provided with
Figure RE-GDA0003776430150000144
Represents the result after iterative update, namely:
Figure RE-GDA0003776430150000145
like updating
Figure RE-GDA0003776430150000146
Repeated iterative update
Figure RE-GDA0003776430150000147
To obtain
Figure RE-GDA0003776430150000148
The expression for the closed solution of (c) is:
Figure RE-GDA0003776430150000149
wherein:
Figure RE-GDA00037764301500001410
Figure RE-GDA00037764301500001411
wherein:
Figure RE-GDA00037764301500001412
Figure RE-GDA00037764301500001413
it is possible to represent the auxiliary variable,
Figure RE-GDA00037764301500001414
the expression of the operator is carried out by,
Figure RE-GDA00037764301500001415
the dual-mode variable is represented by a dual-mode variable,
Figure RE-GDA00037764301500001416
the dual-mode variable is represented by a dual-mode variable,
Figure RE-GDA00037764301500001417
is provided with
Figure RE-GDA00037764301500001418
Represents μ r The value after the m-th iteration,
Figure RE-GDA00037764301500001419
denotes v r The value after the mth iteration;
Figure RE-GDA00037764301500001420
represent
Figure RE-GDA00037764301500001421
To represent
Figure RE-GDA00037764301500001422
The value after the m-th iteration,
Figure RE-GDA00037764301500001423
to represent
Figure RE-GDA00037764301500001424
The value after the m-th iteration is,
Figure RE-GDA00037764301500001425
to represent
Figure RE-GDA00037764301500001426
The value after the mth iteration;
updating
Figure RE-GDA00037764301500001427
And
Figure RE-GDA00037764301500001428
namely:
Figure RE-GDA00037764301500001429
the expression of (a) is:
Figure RE-GDA00037764301500001430
Figure RE-GDA00037764301500001431
the expression of (a) is:
Figure RE-GDA00037764301500001432
it is known that
Figure RE-GDA00037764301500001433
Solving for
Figure RE-GDA00037764301500001434
The description is as follows:
Figure RE-GDA0003776430150000151
Figure RE-GDA0003776430150000152
Figure RE-GDA0003776430150000153
expression (c):
Figure RE-GDA0003776430150000154
Figure RE-GDA0003776430150000155
expression (c):
Figure RE-GDA0003776430150000156
solving to obtain:
Figure RE-GDA0003776430150000157
expression (c):
Figure RE-GDA0003776430150000158
Figure RE-GDA0003776430150000159
the expression of (c):
Figure RE-GDA00037764301500001510
wherein:
Figure RE-GDA00037764301500001511
and S21, setting an iteration initial value, enabling m to be 0,
Figure RE-GDA00037764301500001512
is at an initial value of
Figure RE-GDA00037764301500001513
Is as follows,
Figure RE-GDA00037764301500001514
Is initially of
Figure RE-GDA00037764301500001515
S22 utilization of
Figure RE-GDA00037764301500001516
Is obtained by the expression
Figure RE-GDA00037764301500001517
S23 utilization of
Figure RE-GDA00037764301500001518
Expression update of closed solutions of
Figure RE-GDA00037764301500001519
S24 utilization of
Figure RE-GDA00037764301500001520
Is updated by the expression of
Figure RE-GDA00037764301500001521
By using
Figure RE-GDA00037764301500001522
Is updated by the expression of
Figure RE-GDA00037764301500001523
S25 utilization of
Figure RE-GDA00037764301500001524
Is updated by the expression of
Figure RE-GDA00037764301500001525
By using
Figure RE-GDA00037764301500001526
Is updated by the expression of
Figure RE-GDA00037764301500001527
By using
Figure RE-GDA00037764301500001528
Is updated by the expression of
Figure RE-GDA00037764301500001529
By using
Figure RE-GDA00037764301500001530
Is updated by the expression of
Figure RE-GDA00037764301500001531
S26, repeating the iteration steps S21-S25, setting the iteration times as T2, and outputting after the iteration is finished
Figure RE-GDA00037764301500001532
According to a sampling signal sequence which enables a first direction diagram to meet convergence performance, determining a guide vector and a frequency domain signal corresponding to the sampling signal sequence, specifically comprising: according to the relation between the sampling signal sequence and the guide vector:
Figure RE-GDA00037764301500001533
obtaining a sampling signal sequence x, x ═ x T (0)，…，x T (n)，…，x T (N-1)] T Wherein, wherein T Representing a transpose operation, x T (N-1) denotes the N-1 th sampling signal, x (N) denotes the nth sampling signal, x m (n) represents a sampling signal, x M-1 (n) denotes an nth sample signal on the M-1 th antenna, and x (n) ═ x 0 (n),x 1 (n),…,x m (n),…,x M-1 (n)] T 。
And determining a second directional diagram according to the time domain signal, the frequency domain signal and the first function expression.
Example 2
Based on the same principle as the method shown in embodiment 1 of the present invention, an embodiment of the present invention further provides a wideband MIMO radar pattern obtaining apparatus, as shown in fig. 3, where the apparatus includes:
the first expression determining unit is used for acquiring the sampling signal and a first function expression of a first direction graph; the first function expression is used for representing the relation among the steering vector of the sampling signal, the frequency domain signal and the first direction diagram;
the first conversion unit is used for converting the first function expression based on the L1 norm and determining a second function expression of the first direction diagram;
a second expression determining unit, configured to convert the second function expression into a third function expression including a sampling signal sequence corresponding to the sampling signal, and determine a fourth function expression satisfying a PAPR constraint condition and a sidelobe control constraint condition according to the PAPR constraint condition, the sidelobe control constraint condition, and the second function expression;
the second conversion unit is used for converting the fourth function expression into a convex function to obtain a fifth function expression;
the iteration unit is used for solving the fifth function expression in an iteration solving mode to obtain a target sampling signal sequence which enables the first direction diagram to meet a preset convergence condition;
the first determining unit is used for determining a guide vector and a frequency domain signal according to the target sampling signal sequence;
and the second determining unit is used for determining a second directional diagram according to the steering vector, the frequency domain signal and the second function expression.
Optionally, the first expression determining unit includes:
the first acquisition unit is used for acquiring a sampling signal of a baseband signal and a guide vector of the antenna array;
the conversion unit is used for carrying out discrete Fourier transform on the sampling signal of the baseband signal to obtain a frequency domain signal;
and the first expression determining subunit determines a first function expression of the first direction diagram according to the steering vector of the antenna array and the frequency domain signal.
Optionally, the second expression determining unit includes:
a second obtaining unit, configured to obtain a PAPR constraint condition and a sidelobe control constraint condition;
the third conversion unit is used for converting the second function expression into a third function expression containing a sampling signal sequence corresponding to the sampling signal;
the fourth conversion unit is used for converting the PAPR constraint condition under the condition that the total emission energy is 1 to obtain the converted PAPR constraint condition;
a second expression determining subunit, configured to convert the second function expression into a third function expression including a sampling signal sequence corresponding to the sampling signal, and determine a fourth function expression satisfying a PAPR constraint condition and a sidelobe control constraint condition according to the PAPR constraint condition, the sidelobe control constraint condition, and the second function expression;
optionally, the apparatus further comprises:
the fifth conversion unit is used for converting the fifth function expression by using a preset intermediate variable to obtain a sixth function expression; the sixth function expression is used for representing the relation between an intermediate variable and the first direction diagram, and the intermediate variable is used for representing the relation between the sampling signal sequence and the guide vector; at this time, the iteration unit is configured to solve the sixth function expression in an iterative solution manner, and acquire a target sampling signal sequence that enables the first direction graph to satisfy a preset convergence condition.
Optionally, the iteration unit includes:
a constructing unit, configured to construct an augmented lagrangian function of the fifth function expression;
the iteration subunit is used for solving the intermediate variable in the augmented Lagrangian function by utilizing a parallel iteration mode based on an ADMM method;
and the third determining unit is used for determining the target sampling signal sequence according to the intermediate variable obtained by solving.
Example 3
Based on the same principle as the method shown in the embodiment of the present invention, an embodiment of the present invention further provides an electronic device, as shown in fig. 4, which may include but is not limited to: a processor and a memory; a memory for storing a computer program; a processor for executing the method according to any of the embodiments of the present invention by calling the computer program.
In an alternative embodiment, an electronic device is provided, the electronic device 30 shown in fig. 4 comprising: a processor 310 and a memory 330. Wherein the processor 310 is coupled to the memory 330, such as via a bus 320.
Optionally, the electronic device 30 may further include a transceiver 340, and the transceiver 340 may be used for data interaction between the electronic device and other electronic devices, such as transmission of data and/or reception of data. It should be noted that the transceiver 340 is not limited to one in practical application, and the structure of the electronic device 30 does not limit the embodiment of the present invention.
The Processor 310 may be a CPU (Central Processing Unit), a general-purpose Processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array) or other Programmable logic device, a transistor logic device, a hardware component, or any combination thereof. Which may implement or perform the various illustrative logical blocks, modules, and circuits described in connection with the disclosure. The processor 310 may also be a combination of computing functions, e.g., comprising one or more microprocessors, a combination of a DSP and a microprocessor, or the like.
Bus 320 may include a path that transfers information between the above-described components. The bus 320 may be a PCI (Peripheral Component Interconnect) bus, an EISA (Extended Industry Standard Architecture) bus, or the like. The bus 320 may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, only one thick line is shown in FIG. 4, but this does not indicate only one bus or one type of bus.
The Memory 330 may be a ROM (Read Only Memory) or other type of static storage device that can store static information and instructions, a RAM (Random Access Memory) or other type of dynamic storage device that can store information and instructions, an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical Disc storage, optical Disc storage (including Compact Disc, laser Disc, optical Disc, digital versatile Disc, blu-ray Disc, etc.), a magnetic Disc storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer, but is not limited to these.
The memory 330 is used for storing application program codes (computer programs) for performing aspects of the present invention and is controlled to be executed by the processor 310. The processor 310 is configured to execute application program code stored in the memory 330 to implement the aspects illustrated in the foregoing method embodiments.
Example 4
The present invention proposes a storage medium, and in particular relates to a computer-readable storage medium storing at least one instruction, at least one program, code set, or instruction set, which is loaded and executed by a processor to implement the radar beam pattern acquisition method according to any one of the above embodiments.
The effectiveness of the design is verified through specific simulation:
the number of transmitting antennas of the broadband MIMO radar system is M to 10, the antenna arrays are arranged according to a uniform linear array, and the array element spacing is half wavelength, namely d to c/(2 f) c ) Wherein the carrier frequency of the transmitted signal is f c 1 GHz; the bandwidth and the symbol number of the transmission signal are respectively B-200 MHz and N-32, and the spatial angle is divided into K-180 discrete points (corresponding to 1 ° corresponding to 1 discrete grid), including the main lobe region Θ KL Side lobe region Θ SL And null region Θ NL 。
Experiment one: narrow main lobe single interference suppression experiment: the experiment considered that a single target was located
Figure RE-GDA0003776430150000191
The null region is
Figure RE-GDA0003776430150000192
The side lobe region is
Figure RE-GDA0003776430150000193
First, convergence performance is verified using the residual error. The variation curve of the residual error with the number of iterations as shown in FIG. 5The horizontal axis is iteration times iter (k), the vertical axis is residual error (db), and Q1 is a first residual variation curve with PAPR 1; q2 is a second residual variation curve with PAPR 1; q3 is a third residual variation curve with PAPR 1; q4 is a fourth residual variation curve with PAPR 1.5; q5 is a fifth residual variation curve with PAPR 1.5; q6-is the sixth residual variation curve with PAPR 1. The residual errors are respectively
Figure RE-GDA0003776430150000201
And
Figure RE-GDA0003776430150000202
as can be seen from fig. 5, the residual reaches a constant value after 450 iterations, with almost no fluctuation.
Fig. 6 shows the resultant transmission pattern of the obtained transmission signal, and fig. 6(a) is a simulation diagram of the waveform pattern when the PAPR is 1.0; fig. 6(b) is a simulation diagram of a waveform pattern when PAPR is 1.5; the horizontal axis represents angle (unit: degree) and the vertical axis represents frequency (unit: Ghz). As can be seen from fig. 6(a) and 6(b), all the obtained patterns are energy-focused in the direction of the main lobe θ being 100 °, and are in the null region Θ NL Lower nulls (D1, D2 rectangular areas) were formed. In addition, when the PAPR is 1.5, the synthesized pattern matching is smoother than when the PAPR is 1, which means that a larger PAPR realizes better local pattern synthesis, has better broadband emission pattern synthesis performance, and realizes a pattern with a main lobe matching expectation.
Experiment 2: wide main lobe multi-interference suppression experiment: the experiment considers that different directional diagrams are synthesized in different frequency bands, and the main lobe area of the directional diagrams is
Figure RE-GDA0003776430150000203
The null region is
Figure RE-GDA0003776430150000204
And
Figure RE-GDA0003776430150000205
the side lobe region is
Figure RE-GDA0003776430150000206
Fig. 7(a) is a 3D simulation diagram of a directional pattern obtained with a waveform PAPR of 1, and fig. 7(b) is a 2D simulation diagram, where frequency represents frequency (unit: Ghz), Angle represents Angle (unit: degree), and beampattern represents a directional pattern (unit: dB); fig. 8(a) is a 3D simulation diagram of a directional diagram obtained by setting the waveform PAPR to 1.5, and fig. 8(b) is a 2D simulation diagram; fig. 7 and 8 show the resulting transmit patterns of the obtained transmit waveforms. As can be seen from fig. 7 and 8, the pattern forms an energy focus in the main lobe region and deeper nulls in the null regions (rectangular regions D3, D4, D5, and D6).
The invention provides a matching design method of a broadband radar directional diagram with an L1 norm, which solves the problem of waveform nonlinear distortion caused by large-range fluctuation of a transmitting signal and the problem of waveform design that a broadband MIMO radar directional diagram main lobe norm approaches an expected directional diagram under the constraint of PAPR and sidelobe control. The method adopts the method of converting a waveform design problem into a real-valued optimization problem, solving based on a double-layer Alternating Direction Multiplier Method (ADMM), converting equality constraint into an augmented Lagrange function, and performing iterative solution by using the ADMM method. The invention realizes the main lobe matching with the expected directional diagram, the amplitude fluctuation control of the transmitted signal and the null suppression in the expected space-frequency area, and improves the radar clutter interference suppression capability.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.

Claims (8)

1. The method for acquiring the directional diagram of the broadband MIMO radar is characterized by comprising the following steps:
acquiring a sampling signal and a first function expression of a first direction graph; the first function expression is used for representing the relation among the steering vector of the sampling signal, the frequency domain signal and the first direction diagram;
converting the first function expression based on the L1 norm, and determining a second function expression of the first direction diagram;
converting the second function expression into a third function expression containing a sampling signal sequence corresponding to the sampling signal, and determining a fourth function expression meeting the PAPR constraint condition and the sidelobe control constraint condition according to the PAPR constraint condition, the sidelobe control constraint condition and the third function expression;
converting the fourth function expression into a convex function, and taking the convex function as a fifth function expression;
solving the fifth function expression in an iterative solution mode to obtain a target sampling signal sequence which enables the first direction graph to meet a preset convergence condition;
determining the guide vector and the frequency domain signal according to the target sampling signal sequence;
and determining a second directional diagram according to the steering vector, the frequency domain signal and the second function expression.
2. The wideband MIMO radar pattern acquisition method of claim 1, wherein the first functional expression is determined by:
acquiring a sampling signal of a baseband signal and a guide vector of an antenna array;
performing discrete Fourier transform on the sampling signal of the baseband signal to obtain a frequency domain signal;
and determining a first function expression of the first direction diagram according to the steering vector of the antenna array and the frequency domain signal.
3. The method for obtaining a wideband MIMO radar pattern according to claim 1, wherein the converting the second function expression into a third function expression including a sampling signal sequence corresponding to the sampling signal, and determining a fourth function expression satisfying a PAPR constraint and a sidelobe control constraint according to a PAPR constraint, a sidelobe control constraint, and the second function expression includes:
acquiring the PAPR constraint condition and the sidelobe control constraint condition;
converting the second function expression into a third function expression containing a sampling signal sequence corresponding to the sampling signal;
converting the PAPR constraint condition under the condition that the total emission energy is 1 to obtain the converted PAPR constraint condition;
and determining a fourth function expression meeting the PAPR constraint condition and the sidelobe control constraint condition according to the converted PAPR constraint condition, the sidelobe control constraint condition and the third function expression.
4. The method of claim 1, further comprising:
converting the fifth function expression by using a preset intermediate variable to obtain a sixth function expression; the sixth functional expression is used for representing the relation between the intermediate variable and the first direction diagram, and the intermediate variable is used for representing the relation between the sampling signal sequence and the guide vector;
the solving the fifth function expression in an iterative solution manner to obtain a target sampling signal sequence which enables the first direction graph to meet a preset convergence condition includes:
and solving the sixth function expression in an iterative solution mode to obtain a target sampling signal sequence which enables the first direction graph to meet a preset convergence condition.
5. The method for obtaining a wideband MIMO radar directional diagram according to claim 4, wherein the obtaining a target sampling signal sequence that makes the first directional diagram satisfy a preset convergence condition by solving the sixth functional expression in an iterative solution manner includes:
constructing an augmented Lagrangian function of the sixth function expression;
solving an intermediate variable in the augmented Lagrangian function by utilizing a parallel iteration mode based on an ADMM method;
and determining the target sampling signal sequence according to the intermediate variable obtained by solving.
6. A radar beam pattern acquisition apparatus, comprising:
the first expression determining unit is used for acquiring the sampling signal and a first function expression of a first direction graph; the first function expression is used for representing the relation among the steering vector of the sampling signal, the frequency domain signal and the first direction diagram;
the first conversion unit is used for converting the first function expression based on the L1 norm and determining a second function expression of the first direction graph;
a second expression determining unit, configured to convert the second function expression into a third function expression including a sampling signal sequence corresponding to the sampling signal, and determine a fourth function expression satisfying a PAPR constraint condition and a sidelobe control constraint condition according to the PAPR constraint condition, the sidelobe control constraint condition, and the third function expression;
the second conversion unit is used for converting the fourth function expression into a convex function, and taking the convex function as a fifth function expression;
the iteration unit is used for solving the fifth function expression in an iteration solving mode to obtain a target sampling signal sequence which enables the first direction diagram to meet a preset convergence condition;
a first determining unit, configured to determine the steering vector and the frequency domain signal according to the target sampling signal sequence;
and the second determining unit is used for determining a second directional diagram according to the steering vector, the frequency domain signal and the second function expression.
7. An electronic device, comprising:
a processor and a memory;
the memory is used for storing computer operation instructions;
the processor is used for executing the method of any one of claims 1 to 5 by calling the computer operation instruction.
8. A storage medium having stored thereon computer instructions, characterized in that the computer storage medium has stored thereon at least one instruction, at least one program, set of codes, or set of instructions, which is loaded and executed by the processor to implement the method of any of claims 1 to 5.
CN202210305599.4A 2022-03-25 2022-03-25 Broadband MIMO radar directional diagram acquisition method and device, electronic equipment and storage medium Active CN115015918B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202210305599.4A CN115015918B (en) 2022-03-25 2022-03-25 Broadband MIMO radar directional diagram acquisition method and device, electronic equipment and storage medium

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202210305599.4A CN115015918B (en) 2022-03-25 2022-03-25 Broadband MIMO radar directional diagram acquisition method and device, electronic equipment and storage medium

Publications (2)

Publication Number Publication Date
CN115015918A true CN115015918A (en) 2022-09-06
CN115015918B CN115015918B (en) 2023-06-06

Family

ID=83066906

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202210305599.4A Active CN115015918B (en) 2022-03-25 2022-03-25 Broadband MIMO radar directional diagram acquisition method and device, electronic equipment and storage medium

Country Status (1)

Country Link
CN (1) CN115015918B (en)

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107329120A (en) * 2017-06-29 2017-11-07 中国人民解放军信息工程大学 The MIMO radar waveform design method differentiated towards approaching target
US20180331740A1 (en) * 2017-05-11 2018-11-15 Intel Corporation Multi-finger beamforming and array pattern synthesis
CN110456314A (en) * 2019-08-05 2019-11-15 西安电子科技大学 Centralized MIMO radar waveform optimization method based on main lobe broadening
WO2020212569A1 (en) * 2019-04-17 2020-10-22 Université Du Luxembourg Method and device for beamforming in a mimo radar system

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20180331740A1 (en) * 2017-05-11 2018-11-15 Intel Corporation Multi-finger beamforming and array pattern synthesis
CN107329120A (en) * 2017-06-29 2017-11-07 中国人民解放军信息工程大学 The MIMO radar waveform design method differentiated towards approaching target
WO2020212569A1 (en) * 2019-04-17 2020-10-22 Université Du Luxembourg Method and device for beamforming in a mimo radar system
CN110456314A (en) * 2019-08-05 2019-11-15 西安电子科技大学 Centralized MIMO radar waveform optimization method based on main lobe broadening

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
巩朋成 等: "基于发射方向图合成的低PAPR宽带MIMO雷达波形设计", 《中国科学: 信息科学》 *
程子扬: "MIMO雷达优化波形设计与信号处理研究", 《中国博士学位论文全文数据库信息科技辑》 *

Also Published As

Publication number Publication date
CN115015918B (en) 2023-06-06

Similar Documents

Publication Publication Date Title
Lan et al. Transceive beamforming with accurate nulling in FDA-MIMO radar for imaging
CN108303683B (en) Single-base MIMO radar real-value ESPRIT non-circular signal angle estimation method
CN105137409B (en) The sane space-time adaptive processing method of echo signal mutually constrained based on width
CN107092007A (en) A kind of Wave arrival direction estimating method of virtual second order array extension
CN112636773B (en) Broadband time domain beam forming method based on digital frequency domain compensation
CN111352080B (en) Design method of low-interception frequency-controlled array MIMO radar system under constraint of PAPR and similarity
CN113189592B (en) Vehicle-mounted millimeter wave MIMO radar angle measurement method considering amplitude mutual coupling error
CN111352079B (en) Design method of low interception system based on frequency control array MIMO radar
Tang et al. Wideband multiple‐input multiple‐output radar waveform design with low peak‐to‐average ratio constraint
Wang et al. Nested array sensor with grating lobe suppression and arbitrary transmit–receive beampattern synthesis
Lu et al. Wideband beampattern synthesis using single digital beamformer with integer time delay filters
CN108667489B (en) Multi-beam waveform transmitting method and system
Hua et al. Colocated MIMO radar transmit beamforming using orthogonal waveforms
CN111162878B (en) Multi-domain joint anti-interference method based on subarray dimension reduction band constraint
CN115015918A (en) Broadband MIMO radar directional diagram obtaining method and device, electronic equipment and storage medium
CN109490846B (en) Multi-input multi-output radar waveform design method based on space-time joint optimization
CN108828536B (en) Broadband emission digital beam forming interference design method based on second-order cone programming
Rakhimov et al. Channel estimation for hybrid multi-carrier mmWave MIMO systems using 3-D unitary Tensor-ESPRIT in DFT beamspace
CN107153175B (en) Phase weighting sidelobe suppression method based on alternative projection
CN106842147B (en) A kind of digital beam froming method solving graing lobe interference problem
CN115144829A (en) Radar beam pattern acquisition method and device, electronic device and storage medium
Chen et al. Eigenvalue decomposition approach for beampattern synthesis
CN112162240A (en) Sparse frequency waveform generation method and device based on co-prime array and storage medium
CN110954887B (en) Phased array MIMO beam forming method based on spherical invariant constraint and antisymmetry
Ma et al. Hyper beamforming with single-sideband time-modulated phased arrays for automotive radar

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant