Digital Signal Processing Reference
In-Depth Information
ˆ
a
ˆ
,
b
MSHT algorithm has brought in two thresholds [
] to binary hypothesis testing
H
as the
H
as the hypothesis for the absence of the target,
of the pixels.
Assume
hypothesis for the presence of the target.
When
k
∈
(
N
−
1
,
k
ˆ
Z
(
X
)
≥
a
Traj
~
H
i
1
i
=
1
(12)
k
ˆ
Z
(
X
)
≤
b
Traj
~
H
i
0
i
=
1
k
ˆ
,
ˆ
b
<
Z
(
X
)
<
a
take
another
sample
i
i
=
1
k
=
N
When
,
k
ˆ
Z
(
X
)
>
V
Traj
~
H
(13)
i
T
1
i
=
=
1
k
ˆ
Traj
~
H
Z
(
X
)
≤
V
0
i
T
i
1
c
c
are two constants on [0, 1], then
Let
,
ˆ
1
−
(
−
c
)(
1
−
β
)
(14)
a
ˆ
=
ln[
1
]
(
−
c
)
α
ˆ
0
ˆ
(
−
c
)(
1
−
β
)
ˆ
(15)
b
=
ln[
1
]
ˆ
1
−
(
−
c
)
α
0
σ
ˆ
ˆ
−
1
ˆ
−
1
V
T
=
η
[
μ
Φ
(
c
α
)
+
μ
Φ
(
c
(
−
β
))](
)
(16)
1
0
0
1
μ
−
μ
1
0
ˆ
ˆ
ˆ
and de-
α
a
ˆ
,
b
V
Thresholds [
] is involved with the value of SNR, false alarm rate
ˆ
.
β
tection probability
3.3
Tracking and Detecting IR Dim-Small Moving Target
It's known that DP algorithm and MSHT algorithm are two typical DBT algorithms
for detecting IR dim-small moving target. Both of them have their own strengths.
Compared to MSHT algorithm, DP algorithm has higher detection probability but
larger calculate amount. Thus we consider combining the advantages of these two
algorithms to detect IR dim-small moving target, aimed at obtaining high detection
probability, and low computation and storage requirements.
