US 12,519,509 B2 · Communication and radar target detection method based on intelligent omni-surface

Abstract

It discloses a communication and radar target detection method based on an intelligent omni-surface, comprising step 1: constructing an optimization problem by maximizing a minimum beampattern gain as an objective function, the communication system being an integrated sensing and communication system based on an intelligent omni-surface; step 2: setting a constraint condition for the optimization problem constructed in the step 1, the constraint condition comprising a minimum rate constraint of a user, a maximum transmit power constraint of a base station, and amplitude and phase shaft constraints of the intelligent omni-surface; and step 3: solving the optimization problem after setting with the constraint condition to obtain an optimization solution for maximizing the minimum beampattern gain. According to the method, a capability of detecting the radar target is further improved under the condition that a quality of service of a communication user is guaranteed.

A communication and radar target detection method based on an intelligent omni-surface applied to an integrated sensing and communication system, comprising the following steps of:

step 1:
constructing an optimization problem by maximizing a minimum beampattern gain as an objective function, the integrated sensing and communication system being an integrated sensing and communication system based on an intelligent omni-surface;
step 2:
setting a constraint condition for the optimization problem constructed in the step 1, the constraint condition comprising a minimum rate constraint of a user, a maximum transmit power constraint of a base station, and amplitude and phase shift constraints of the intelligent omni-surface;
and
step 3:
solving the optimization problem after setting with the constraint condition to obtain a solution for maximizing the minimum beampattern gain, thus realizing communication and radar target detection;
the integrated sensing and communication system based on the intelligent omni-surface in the step 1 is applied to a downlink communication, and a base station communicates with a user under the assistance of the intelligent omni-surface and completes radar target detection;
each element of the intelligent omni-surface in the step 1 has a function of both reflected and transmitted signals, a signal reflected by the element is referred to as a reflected signal, and a signal passing through the element is referred to as a transmitted signal;
and a communication area covered by the intelligent omni-surface is divided into two parts, which are a reflection area and a transmission area;
the optimization problem in the step 1 is as follows:
max
w
,
R
0
,
v
r
,
v
t
min
q
∈
{
1
,
2
,
…
,
Q
}
𝒫
θ
q
(
w
,
R
0
,
v
t
)
wherein, w∈CN×1 represents an active transmitted beamforming vector, R0∈CN×N is a covariance matrix of radar signals,
v
r
=
[
λ
1
r
⁢
e
j
⁢
θ
1
r
,
λ
2
r
⁢
e
j
⁢
θ
2
r
,
…
,
λ
M
r
⁢
e
j
⁢
θ
M
r
]
H
⁢
and
v
t
=
[
λ
1
t
⁢
e
j
⁢
θ
1
t
,
λ
2
t
⁢
e
j
⁢
θ
2
t
,
…
,
λ
M
t
⁢
e
j
⁢
θ
M
t
]
H
are reflected and transmitted beamforming vectors respectively, λrm and θrm are a reflected amplitude and a reflected phase shift of an mth element of the intelligent omni-surface respectively, λtm and θrm are a transmitted amplitude and a transmitted phase shift of the mth element of the intelligent omni-surface respectively, Pθq (w, R0, Vt)=αH(θq)ΘtF (wwH+R0)FHΘHt α(θq) is a beampattern gain, α(θq)=[1, ej2πΔsin θq, . . ., ej2π(N−1) Δsin θq]T is a steering vector of a qth angle to be detected on the intelligent omni-surface, θq is the qth angle to be detected relative to the intelligent omni-surface, Θt=diag(vHt) is a transmitted beamforming diagnal matrix, F∈CM×N represents a channel between the intelligent omni-surface and the base station, M is a total number of elements of the intelligent omni-surface, N is a number of antennas equipped for the base station, Q is a total number of angles to be detected, Δ is a ratio of carrier wavelength to antenna spacing, m∈{1,2, . . . , M}, q∈{1,2, . . . , Q}, CN×1 represents a complex column vector of N dimension, and CM×N represents a complex number matrix of M×N dimension;
diag{□} represents to converting the vector to a diagonal matrix, (□)T and (□)H respectively represent transposition and conjugate transposition of a vector, ef□ represents an exponential form of complex number, and sin(□) represents a sinusoidal function;
the constraint condition in the step 2 comprises:
constraint
⁢
condition
⁢
1
:
R
≥
R
min
constraint
⁢
condition
⁢
2
:

w

2
+
Tr
⁡
(
R
0
)
≤
P
max
constraint
⁢
condition
⁢
3
:
λ
m
r
+
λ
m
t
=
1
,
λ
m
r
∈
[
0
,
1
]
,
λ
m
t
∈
[
0
,
1
]
,
m
∈
{
1
,
2
,
…
,
M
}
constraint
⁢
condition
⁢
4
:
θ
m
r
∈
[
0
,
2
⁢
π
)
,
θ
m
t
∈
[
0
,
2
⁢
π
)
,
m
∈
{
1
,
2
,
…
,
M
}
constraint
⁢
condition
⁢
5
:
R
0
≥
0
wherein,
R
=
log
2
(
1
+
❘
"\[LeftBracketingBar]"
g
H
⁢
Θ
r
⁢
Fw
❘
"\[RightBracketingBar]"
2
σ
2
)
is an achievable data rate of the user, g∈CM×1 represents a channel between the user and the intelligent omni-surface, Θr=diag(vHr) is a reflected beamforming diagnal matrix, Rmin is a minimum rate of the user, σ2 is a variance of an additive white Gaussian noise, π is a ratio of circumference to diameter, ∥□∥2 is a square of normal of a vector l2, Tr(□) is a trace of matrix, |□|2 is a square of a complex modulus, Pmax represents a maximum transmit power of the base station, and R0≥0 represents that R0, is a semi-positive definite matrix;
and
the constraint condition 1 is the minimum rate constraint of the user, the constraint condition 2 is the maximum transmit power constraint of the base station, the constraint condition 3 and the constraint condition 4 are amplitude and phase shift constraints of the intelligent omni-surface respectively.

283 more elements

Communication and radar target detection method based on intelligent omni-surface

Life of this patent

Communication and radar target detection method based on intelligent omni-surface

Life of this patent

Abstract

Claims6