IEEE Circuits and Systems Magazine - Q1 2021 - 58

weak reflected signal reaches the antenna after passing
through the wall again. Due to the inevitable clutter in
the radar environment, it is important that an algorithm
is able to separate target signal and clutter from the
received signal is introduced. In [63], the performance
of the singular value decomposition (SVD) approach
was compared with moving average as a clutter reduction technique in a SFCW radar. SVD, also known as the
subspace method, divides the data into two categories:

target and clutter subspaces. The SVD is applied on the
signal matrix to separate the target signature from the
clutter. This matrix can be represented as a linear combination of its eigen components. If only a single target
exists, then the second eigen component contains the
target information, whereas the first will contain the
clutter information.
While the chest displacement caused by breathing
can be extracted from the phase variation, it is still

Start
Weight
Initialization
Acquire
Received Signal
Using OMP estimation to find
Coarse Positioning
(Blick-Wise Estimation) some blocks of candidates.
Update Weights

Using estimation results to
update weights of blocks.

Blocks/Weights
Weight Sorting

Sorting the blocks according to their
weights in a descending order.

Block Merging

1) Merging blocks if they are too close.
2) Blocks with smaller weights are
merged into block with the near
larger weights.

Block Selection

Selecting block according
threshold and weights.

No

# of Iteration>
# of Training?

If in training phase, go to
the next iteration.

Yes

Selecting blocks for fine
positioning according to decision
strategy.

Decision
Fine
Positioning (OMP)

Performing OMP algorithm on
the selected blocks.

Figure 15. Two stage reconstruction algorithm [44]. Licensed under Creative Commons attribution license.

Complexity Analysis (b = 4, k = 3)

6
OMP

4

Coarse + Fine (OMP)

2
0
0

OMP Via MIB
5,000

Coarse + Fine (OMP Via MIB)

n 10,000
0

500
m
(a)

1,000

Complexity

Complexity

8

Complexity Analysis (b = 4, k = 3)

× 106
3

× 104

2
1
0
0

1,500

OMP Via MIB

Coarse + Fine(OMP Via MIB)
5,000
500
n
10,000 0
m

1,500
1,000

(b)

Figure 16. Computational complexity of the two-stage OMP algorithm [44]. Licensed under Creative Commons attribution license
https://creativecommons.org/licenses/by/4.0/
58

IEEE CIRCUITS AND SYSTEMS MAGAZINE

FIRST QUARTER 2021



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IEEE Circuits and Systems Magazine - Q1 2021

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