US 12,276,724 B1 · Method for suppressing azimuth ambiguity of multi-channel SAR systems based on channel cancellation

Abstract

The present disclosure discloses a method for suppressing the azimuth ambiguity of multi-channel SAR systems based on channel cancellation, which falls within the field of radar signal processing. The method includes: imaging echoed of the multi-channel SAR system based on a linear mapping reconstruction algorithm to obtain a reconstructed high-resolution wide-swath image; estimating positions of the azimuth ambiguity regions of the reconstructed high-resolution wide-swath image; extracting ambiguity images in the azimuth ambiguity regions based on channel cancellation and the refocusing algorithm; and suppressing a repetitive ambiguity image in imaging the echo of the multi-channel SAR system. The method weakens the influence of the original image on azimuth ambiguity extraction, improves the performance of ambiguity suppression, and solves the problem of additional repetitive ambiguity in multi-channel SAR systems by reconstructing the ambiguity signal, and improves the image quality of the multi-channel SAR system, which has great value for subsequent applications such as SAR image interpretation.

A method for suppressing azimuth ambiguity of multi-channel SAR systems based on channel cancellation, characterized by comprising the following steps:

step 1, imaging echoes of the multi-channel SAR system based on a linear mapping reconstruction algorithm to obtain a reconstructed high-resolution wide-swath image;
step 2, estimating positions of the azimuth ambiguity regions of the reconstructed high-resolution wide-swath image and defining an azimuth ambiguity detection function r(τ,η) as:
r(τ,η)=log{{|L1(τ,η)|2}/{|L2(τ,η)}
wherein log {·} represents a natural logarithm operation, represents a spatial averaging operation, |·| represents an absolute value calculation operation of a complex number, and L1(τ,η) and L2(τ,η) respectively represent two multi-look images obtained by performing azimuth double-look on a reconstructed high-resolution wide-swath image, τ represents a range fast time and η represents an azimuth slow time;
step 3, extracting ambiguity images in the azimuth ambiguity regions based on channel cancellation and a refocusing algorithm, wherein
a linear combination coefficient ω(fη)=[ω1(fη), ω2(fn), . . . , ωN(fη)] for the-channel cancellation satisfies the following expression:
{
∑
n
=
1
N
ω
n
(
f
η
)
⁢
H
n
(
f
η
+
b
⁢
f
a
)
=
0
,
b
=
0
,
1
,
…
,
N
-
2
∑
n
=
1
N
ω
n
(
f
η
)
⁢
H
n
(
f
η
+
k
⁢
f
a
)
=
1
,
k
=
-
1
wherein ωn(fη) represents the linear combination coefficient corresponding to the nth channel, n represents a serial number of a receiving channel, b represents a serial number of a Doppler interval, an azimuth frequency is
f
η
∈
[
f
c
-
N
⁢
f
a
2
,
f
c
-
(
N
-
1
)
⁢
f
a
2
]
,
fa represents an azimuth sampling rate of a single channel, fc represents a center frequency, Hn(fη) represents a transfer function of the nth receiving channel, and k represents an order of an azimuth ambiguity;
a form IMCC(τ,fn) of a image IMCC(τ,η) in the time domain after channel cancellation in a range-Doppler domain is:
I
M
⁢
C
⁢
C
(
τ
,
f
η
)
=
∑
n
=
1
N
ω
n
(
f
η
)
p
n
(
f
η
)
⁢
I
n
(
τ
,
f
η
)
wherein pn(fη) represents a reconstruction coefficient of the nth channel in a reconstruction process, and In(τ,fη) represents a form of an image In(τ,η) in the time domain corresponding to the nth channel in the range-Doppler domain;
ambiguity refocusing and inverse defocusing are realized by phase multiplication in two-dimensional frequency domain, and a calculation method of refocusing is:
R
⁡
(
τ
,
η
)
=
IFFT
⁢
2
⁢
{
r
(
1
)
(
f
τ
,
f
η
)
⊗
K
*
(
f
τ
,
f
η
+
k
·
f
a
)
}
r
(
1
)
(
f
τ
,
f
η
)
=
FFT
⁢
2
⁢
{
I
M
⁢
C
⁢
C
(
τ
,
η
)
}
⊗
K
⁡
(
f
τ
,
f
η
)
K
⁡
(
f
τ
,
f
η
)
=
exp
⁢
{
-
4
⁢
j
⁢
π
⁢
R
0
c
⁢
(
f
0
+
f
τ
)
2
-
c
2
⁢
f
η
2
4
⁢
V
r
2
}
wherein c represents the velocity of light, Vτ represents an equivalent imaging speed corresponding to the central range gate of the ambiguity region, f0 represents a carrier frequency, R0 represents a nearest slant range, fτ represents a distance frequency, r(1)(fτ,fη) represents an intermediate result, R(τ,η) represents a result of refocusing, * represents a complex conjugate operation, ⊗ represents a Hadamard product, K(fτ,fη) represents a two-dimensional frequency domain expression of an echo of an ideal point target, FFT2{·} represents a two-dimensional Fourier transform, and IFFT2{·} represents a two-dimensional inverse Fourier transform;
and
an image RAmb(τ,η) corresponding to ambiguity pixels is obtained from a refocused image through classification of a mixed Gaussian ambiguity, and inverse refocusing is performed to obtain a ambiguity image IAmb(τ,η) corresponding to the ambiguity pixels:
IAmb(τ,η)=IFFT2{r(2)(fτ,fη)ωK′(fτ,fη)}
r(2)(fτ,fη)=FT2{RAmb(τ,η)}ωK(fτ,fη+kfa)
wherein r(2) represents an intermediate result;
and
step 4, suppressing a repetitive blurred image in an echo of the echoes of the multi-channel SAR system.

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Method for suppressing azimuth ambiguity of multi-channel SAR systems based on channel cancellation

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Method for suppressing azimuth ambiguity of multi-channel SAR systems based on channel cancellation

Life of this patent

Abstract

Claims4