c 20XX by the authors; licensee RonPub, Lübeck, Germany. This article is an open access article distributed under the terms and conditions of⃝
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Open Access

Open Journal of Internet of Things (OJIOT)
Volume X, Issue X, 20XX
http://www.ronpub.com/journals/ojiot
ISSN 2364-7108

Development of FM-CW Radar System for
Detecting Closed Multiple Targets
and Its Application in Actual Scenes
Kazuhiro Yamaguchi A , Mitumasa Saito B , Takuya Akiyama A , Tomohiro Kobayashi A ,Naoki Ginoza A , Hideaki Matsue A
A

Tokyo University of Science, Suwa, 5000-1 Toyohira, Chino, Nagano, Japan, 391-0292
yamaguchi@rs.tus.ac.jp, matsue@rs.suwa.tus.ac.jp
B
CQ-S net Inc., Torigoe 7-8, Kanagawa-ku, Yokohama-shi, Kanagawa, Japan, 221-0064, info@cq-snet.com

A BSTRACTIn this paper, detection method for 24 GHz band FM-CW radar system under closed multiple targets with small
displacements environment was proposed, and its performances were analyzed by using computer simulation. The
proposed detection method used a differential detection method for removing any signals from background objects,
and also used a tunable FIR filtering in signal processing for detecting multiple targets. The proposed detection
method enabled to detect both the distance and small displacement at the same time for each target correctly from thereceived signal including all of signals from the targets at the FM-CW radar. The basic performances for FM-CW
radar were analyzed in computer simulation, and field experiments for detecting target under actual environments.
The results showed that the proposed differential detection could only measure the desired targets, and the humanbreathing could also be detected in a hospital scene. Furthermore, under closed multiple targets environments, we
showed the problems for detecting both distance and small displacements of multiple targets at the same time byusing a single radar. Computer simulations were carried out for evaluating the proposed detection method with thetunable FIR filtering for FM-CW radar and analyzing the performance according to the parameters under closed
multiple targets environment. The results in computer simulation showed that the proposed detection method could
detect both the distance and small displacement correctly under closed multiple targets environment.

T YPE OF PAPER AND K EYWORDS
Regular research paper: FM-CW radar, distance measuring, small displacement measuring, multiple targets detection, tunable FIR filtering

1

I NTRODUCTION

such as sensor information. As one of sensing applications, radar has been employed to detect in widely areas
such as on the ground, on the sea, in the air, in space. The
radar systems can detect various information according
to application areas by transmitted and received throughradio wave.

Recently, rapidly evolving wireless communication technologies provides us to communicate various information from a lot of manufactures in widely technologies
field. IoT (Internet of Things) is popularly known as a
key topic for developing system and services, and it enables various physical devices to collect various things

Radar systems with 24 GHz band is based on ARIB
1

Open Journal of Internet of Things (OJIOT), Volume X, Issue X, 20XX!

Signal

D/A

VCO

BPF

Tx

Target 1&'

Target&(FFT
Display

A/D

Rx

BPF
#$%

"

Signal processing

Target&)&distance from the radar

Figure 1: Block diagram of a FM-CW radar systemstandard T73 [1] in Japan as sensors for detecting or
measuring mobile objects for specified low power radio
station. And the 24 GHz band radar system could beapplied in various field such as security, medical imaging and so on under indoor and outdoor environments.
Various radar systems were reported [2, 3, 4, 5]. Pulsed
radar systems can measure the period between the transmitted and received signals. The pulsed radar can detectthe distance in far field; however, the target in near field
can not be detected correctly. Doppler radar systems canmeasure the frequency difference between the reflected
and transmitted signals. The Doppler radar can detect
the moving velocity of the target; however, the distanceof the target can not be detected. FM-CW (FrequencyModulated Continuous-Wave) radar systems [6, 7] is themost widely used for detecting the distance of the target object in near field and the small displacement of thetarget.
As previous study, we reported the design, performance analysis, and applications with 24 GHz band
radar system for detecting both the distance from theradar and the small displacement for human breathing[8]. The radar system could detect both the distance tothe human from the radar and the small displacement of
the human breathing correctly; however, it was difficultfor detecting the distances and displacements for multiple humans at the same time. In order to detect the distances and displacements under closed multiple targets
environment, we proposed a detection method for signal
processing with a tunable FIR filter in the FM-CW radarsystem [9]. Furthermore, performance analysis for FMCW radar system was shown in computer simulations.
In this paper, the proposed detection method consideringboth the differential detection and the tunable FIR filtering for detecting both the distances and small displacements under single and closed multiple targets environment. Moreover, applications based on IoT for detecting
the human movements in actual scenes were described.
This paper consists of the following sections. In Section II, we describe the principle of a FM-CW radar sys-

tem and its basic performance under single target environment. In Section III, we describe the proposed detection method under single target environment. In Section
IV, we describe the proposed detection method undermultiple targets environment. In Section V, we discuss
the results of computer simulation and field experiments.
Finally, Section VI concludes this paper.

2

FM-CW R ADAR S YSTEM

2.1

Principle of FM-CW radar

Figure 1 shows the block diagram of a FM-CW
radar system [10]. FM-CW (Frequency-Modulated
Continuous-Wave) radar was one type of radar which
was transmitting a continuous carrier modulated by a periodic function such as a sawtooth wave to provide range
data shown in Figure 2.
In the FM-CW radar system, frequency modulated
signal at the VCO is transmitted from the transmitter Tx;
then, signals reflected from the targets are received at thereceiver Rx. Transmitted and received signals are multiplied by a mixer, and beat signals are generated as multiplying the two signals. The beat signal pass through alow pass filter; then, an output signal is obtained. In thisprocess, the frequency of the input signal is varied withtime at the VCO. The modulation waveform with a linear
sawtooth pattern [11] as shown in Figure 2. This figure
illustrates frequency-time relation in the FM-CW radar,and the red line denotes the transmitted signal and theblue line denotes the received signal. Here, f0 denotes
the center frequency, fw denotes the frequency bandwidth for sweep, and tw denotes the period for sweep.
We define that the transmitting signal VT (f, x) is represented as
2πf

VT (f, x) = Aej c x ,(1)where f denotes a frequency at a time, x denotes a distance between a target and the transmitter, A denotes anamplitude value, and c denotes the speed of light.
2

Kazuhiro Yamaguchi, Mitumasa Saito, Takuya Akiyama, Tomohiro Kobayashi, Naoki Ginoza, Hideaki Matsue: Development of FM-CW Radar
System for Detecting Closed Multiple Targets and Its Application in Actual Scenes

culated as follow.

Frequency

"# +

"!
%
!

Transmitted signal∫ f0 + f2w

Received signal

4πfVout e−j c df

P (x) =
f0 − f2w"=∫ f0 + f2w ∑K
f0 − f2w

"!
"# $
%

2

=A

!

k=1

#

Time

K
∑

"# : center frequency! : bandwidth of sweep frequency! : sweep time

= A2

K
∑

A2 αk γk ejφk ej

k=1

αk γk ejφk

∫ f0 + f2w

ej

e−j

4πf x
c

4πf (dk −x)
c

df

df

f0 − f2w[

αk γk ejφk ej

k=1{· fw sincFigure 2: Sawtooth frequency modulation

4πf dkc

4πf0 (dk −x)c2πfw (dk − x)
c

}]
.

(5)

In this equation, the function of sinc (x) denotes
The reflected signal VR (f, x) is represented assinc (x) =VR (f, x) =

K
∑

2πf

Aαk γk ejφk ej c (2dk −x) ,|P (x)| = A

2

where γk and φk are the reflective coefficients for amplitude and phase on kth target, respectively. αk denotes anamplitude coefficient for transmission loss from the kth
target, and dk is the distance between the transmitter andthe kth target.

K
∑

2πf

(6)

4πf0 (dk −x)
c

{

}

k=1

}]

2πfw (dk − x)c[
K∑
≤ A2 fw
α k γk· fw sinc{· sincAαk γk ejφk ej c (2dk ) .

αk γk ejφk ej

k=1Here, at the receiver whose position is x = 0, Equation (2) is rewritten as

VR (f, 0) =.

The amplitude value of the distance spectrum |P (x)| inequation (5) is given as

(2)

k=1

K
∑

sin x
x

2πfw (dk − x)
c

,

(7)

(3)

and we have equality if and only if the phase components
ϕk + 4πf0 (dc k −x) about all of k are equal.
Here, we assumed that the number of target is 1. The
The beat signal is generated as multiplying the trans- distance spectrum in equation (5) is rewritten as
mitted signal in Equation (1) and the received signal in[
Equation (3) at the position x = 0. After through LPF,
4πf0 (d1 −x)c
P (x) = A2 α1 γ1 ejφ1 ej
the output signal Vout (f, 0) is generated by}]{
2πfw (d1 − x),
· fw sinc(8)K∑
4πf dkc(4)
Vout (f, 0) =A2 αk γk ejφk ej c .
k=1

k=1

and the amplitude value of distance spectrum is given as{}
2πfw (d1 − x)
2
|P (x)| = A α1 γ1 fw sinc. (9)By using signal processing, a distance and a displacec
ment for the target are given from the generated output
signal in Equation (4). By using the Fourier transform, This equation indicates that the distance for the target isthe distance spectrum of the output signal P (x) is cal- generated by the amplitude value of distance spectrum.
3

Open Journal of Internet of Things (OJIOT), Volume X, Issue X, 20XX

Table 1: Parameters in computer simulations
Sampling time for sweep = 1 !

Sweep time tw
Sampling time for sweep
Number of FFT points
Window function

Values24.15 (GHz)50, 100, 200,400 (MHz)
1024 (µs)
0.1, 1, 10 (µs)
4096hamming

50 MHz!

Parameters
Center frequency f0
Bandwidth of sweep frequency fw

100 MHz

200 MHz
400 MHz

Measured distance [m]The phase value of distance spectrum ̸

P (x) is repre-

Figure 3: Resolution for distance spectrum according
to bandwidth of sweep frequency fw .

sented as̸

P (x) = φ1 +4πf0 (d1 − x)
= θ1 (x) .
c(10)"# = 200 MHz

Here, θ1 (x) satisfy −π ≤ θ1 (x) ≤ π, then the displacement for the target isc (−π − φ1 )c (π − φ1 )≤ d1 ≤
.
4πf0
4πf0

10 "#

(11)

!

−

0.1 "#, 1 "#If the phase value satisfies ϕ1 = 0, equation (11) isrewritten as −3.11 [mm] ≤ d1 ≤ +3.11 [mm] with
f0 = 24.15 [GHz]. That is, the small displacement of
the target within ±3.11 [mm] is generated by the phase
Measured distance [m]value of distance spectrum.
On the other hands, the maximum distance for meaFigure 4: Error value for distance spectrum accordsuring dmax is
ing to sampling time for sweep.
fw∆f =[Hz] ,
tw /tsc
dmax =(12) are outputted with various parameters. Figure 3 shows
[m] ,
4∆f
the amplitude value for distance spectrum versus measured distance with various sweep bandwidth. The rewhere tw denotes the sweep time, ts denotes the interval
sult shows that the sweep bandwidth influenced the distime for sampling. For example, in the case with tw =tance resolutions and widely bandwidth could improve1024 µs and ts = 1 µs, the maximum distance is dmax =the resolution. In the case with ts = 1 µs, the distance
384 [m].
resolutions with fw = 50, 100, 200, 400 MHz were ±5,±1.5, ±1, ±0.5 m, respectively. Figure 4 shows the
2.2 Analysis of Basic Performances
amplitude value for distance spectrum versus measured
At first, we describes the basic performance about the distance with various sampling time. The result shows
FM-CW radar with 24 GHz band. Parameters for com- that the sampling interval influenced the error about theputer simulation are listed in table 1, and the parameters measured distance and shortly sampling interval could
were determined as ARIB standard T73[1]. Center fre- reduce the error value for distance. In the case with fw =quency was 24.15 GHz, bandwidth are 50, 100, 200, and 200 MHz, the error values about the measured distance
400 MHz. Note that the 400 MHz bandwidth was only with ts = 10 µs was about 0.5 m.
used for the computer simulation because of standards in
Figure 5 shows the result for measuring a slowly movthe Radio Law in Japan. Sweep time was 1024 µs, sam- ing target with fw = 200 MHz and ts = 1 µs. The tarpling times for sweep were 0.1, 1, 10 µs, number of FFT get moved from 10 m to 20 m at intervals of 0.5 m on
points was 4096, and the hamming windows was adapted each time step. Figure 5(a) shows the amplitude value
versus measured distance versus target distance with 3as the window function in signal processing.
We assumed that a static target is located at 10 m from dimensional viewing, and Figure 5(b) shows measured
the transmitter and receiver, and the distance spectrums distance versus target distance with 2-dimensional view4

Kazuhiro Yamaguchi, Mitumasa Saito, Takuya Akiyama, Tomohiro Kobayashi, Naoki Ginoza, Hideaki Matsue: Development of FM-CW Radar
System for Detecting Closed Multiple Targets and Its Application in Actual Scenes!

Measured distance [m]All of spectrums:

Measured distanceSpectrums of the other objects:!

Spectrum of the target object! = 200 MHz,
Sampling time for sweep = 1 !

Target distanceTarget distance [m](a): 3D view.

(a): without differential detection.

Measured distance

Measured distance [m]"# = 200 MHz
Sampling time for sweep = 1 !

Target distanceSpectrum of the target object! = 200 MHz,
Sampling time for sweep = 1 !

Target distanceTarget distance [m](b): 2D view.

Measured displacement [mm](b): with differential detection (Proposed).
Figure 5: Distance spectrum for measuring moving
Figure 7: Distance spectrum for measuring moving
target.
target distance with / without the differential detection under the environments which multiple objects
are located.
! = 200 MHz
Sampling time for sweep = 1 !
ment and it is not corresponding to the absolute distance
between the receiver and the target object. The small
displacement within ± 3.11 mm was correctly measured
with the parameters of the FM-CW radar system in thispaper although the displacement more than ±3.11 mm
had uncertainty.
Target displacement [mm]3

P ROPOSED T ECHNIQUES FOR SINGLE TAR GET DETECTION

Figure 6: Measured displacement.

3.1
ing. The color in (b) is corresponding to the strength of
the amplitude value in (a). From these figures, it was
confirmed that the distance could be measured correctly
according to the positions of the moving target.
Figure 6 shows the result for measuring a target withsmall displacement, and the measured displacement versus target displacement is outputted. The object was located at 10 m from the receiver, and the object moved
from -5 mm to 5 mm at intervals of 0.1 mm. The small
displacement could be measured by the phase value of
distance spectrum, and the measured displacement wascorresponding to the target displacement. Note thatthe measured displacement denotes the relative displace-

Detection for single target

As mentioned in the above section, the FM-CW radarsystem could measure the distance and the small displacement for single target at the same time. However,it was a special case that only the reflected signal on atarget could be received at the receiver. In general, thereceiver may receive the reflected signals from many objects. Therefore, when there was some objects for measuring the target distance, signal processing for detecting
the distance spectrum from the only target would be required.
The proposed method removes the signals from theother objects by using the differential detection of distance spectrum. Figure 7 shows the distance spectrum
5Open Journal of Internet of Things (OJIOT), Volume X, Issue X, 20XX

Table 2: Parameters in filed experiments

FM-CW radar

Parameters
Center frequency f0
Bandwidth of sweep frequency fw
Sweep time tw
Sampling time for sweep
ts
Outputting power on
Transmitting
Antenna gain
Range of distanceRange of relative displacement

Distance
Small displacement

Figure 8: An setting example of FM-CW Radar for
detecting human breathing

7 (mW)
11 (dBi)
0–100 (m)±3.11 (mm)Time [s]Measured distance [m](a): without differential detection.

Time [s](b): with differential detection (Proposed).
Figure 9: Distance spectrum for measuring moving
target distance with / without the differential detection.

3.2 Field Experiments and Application
3.2.1

1024 (µs)
1 (µs)

Measured distance [m]when the target object moves from 10 m to 20 m and theother objects are located at 15 m and 20 m. The transmitted signal is reflected on the target and the other objects,
the receiver receives several reflected signals. Therefore,
the distance spectrum of the other objects are also generated by the FM-CW radar system in Figure 7(a), andthe distance spectrum of the target can not be detected
clearly. In particular, when the reflection coefficient of
the target is lower than that of the other objects, the distance spectrum of the other object has higher amplitude
value than that of the target.
In the proposed differential detection, at first, the distance spectrum of the other objects P0 is generated beforehand in Figure 7(a). Then, the distance spectrum of
the target and the other object P is subtracted by P0 .
By using the differential detection, distance spectrum removed the distance spectrum of the other targets is generated as P − P0 . Therefore, the distance spectrum of
the desired target is only detected. Figure 7(b) shows the
distance spectrum by using the proposed differential detection method, and the distance spectrum of the target
is correctly measured. As compared with the measured
distance spectrums in Figure 7(a) and (b), it is clearly
confirmed that the proposed method can detect target distance by using the difference detection. The proposed
differential detection can effectively detect the moving
or static target distance from multiple reflections of the
background static objects.

Values24.15 (GHz)
200 (MHz)

Setup condition for field experiments

In order to evaluate the effectiveness of the proposed
method for detecting the target distance and displacement, we developed a FM-CW radar system and carriedout the experiments with the radar system in actual environment. Table 2 lists the parameters, and the developed
FM-CW radar system got a certificate of conformity withtechnical regulations in Article 38-6 Paragraph 1 of theRadio Law in Japan, and developed FM-CW radar system was accommodate to ARIB standard T73 in Japan
[1].

3.2.2

Results in field experiments

Figure 9 shows the distance spectrum of a moving target.
A person walked away from the FM-CW radar and thencame close between 2 m to 10 m. In Figure 9(a), several
distance spectrums of the person and the background objects were outputted. The distance spectrum of the moving person was not clearly detected in Figure 9(a) because of the reflected signals from background objects.
In order to detect the distance spectrum of the moving
6

Measured small
displacement [mm]Kazuhiro Yamaguchi, Mitumasa Saito, Takuya Akiyama, Tomohiro Kobayashi, Naoki Ginoza, Hideaki Matsue: Development of FM-CW Radar
System for Detecting Closed Multiple Targets and Its Application in Actual Scenes

3.2.3

Example of Application

In this section, we show an example of application with
24 GHz FM-CW radar system. Figure 8 shows a setup of
5 seconds
the FM-CW radar system for detecting human breathing
Time [s]in actual scenes. The FM-CW radar satisfied the safety
guideline, and the details of the safety guideline is deFigure 10: Displacement for measuring the move- scribed in Appendix.
ment of human breathing.
Figure 11(a) shows the example of the results for detecting human breathing of single target in a room ofa hospital. The distance spectrum in this example wasmeasured as following flow.
1. Measuring distance spectrum without any person.

1. Without any person
2. Reflection on the human body

2. A person comes to the bed. The radar received signals from human’s body.

Measured small
displacement [mm]Measured distance [m]3. Breathing detection

3. The person lies asleep on the bed. The radar detects
the person’s breathing movement.

By generating the distance spectrum of the backgroundobjects without the person, the distance spectrum of
the person was only detected. When the person comesTimewithin the range of radar, the radar system could detectreflected signals from the person, and the distance spec(a)trums of the human’s body were detected. After the person lied down on the bed, the radar system could detect
the small displacement for the person’s breathing moveAlert information
ment. By using the differential detection method, the disTypes of status
tance and small displacement of the moving object wereclearly detected.
As connecting the developed FM-CW radars in several rooms in the hospital, detecting several targets could
Status for individual targets
be realized. An example of monitoring several targets is(b)shown in Figure 11(b). The developed FM-CW radars
were connected the network system, and the information
Figure 11: Example of application.
of detecting the distance and small displacement weresent to server in nurse station. In the nurse station, status of several targets could be monitored, and the alert
information such as falling off the bed and stopping theperson with the differential detection method, the dis- human breathing could be monitored.
tance spectrum without the person was measured beforehand. By generating the distance spectrum of the back4 P ROPOSED T ECHNIQUES FOR MULTIPLE
ground objects beforehand, the distance spectrum of the
TARGETS DETECTION
moving person was correctly detected in Figure 9(b) withthe proposed differential detection. Therefore, the FM- 4.1 Problems for multiple targets detection
CW radar system could measure movement of the target
As mentioned in the above section, the FM-CW radar
person effectively.
system could detect both the distance and displacement
Figure 10 shows the result of measuring the small correctly under single target environments; however, thedisplacement for human breathing. The human’s chest FM-CW radar could not detect both the distance and dismovement was measured within the range of relative placement correctly under closed multiple targets envismall displacement. In Figure 10, it was detected that ronments. In order to realize detection for closed multhe period of breathing was about 4 s and the breathing tiple targets, we propose the detection method by using
movement was about within ±2 mm.
the signal processing with a tunable FIR filter.
Time

7

Open Journal of Internet of Things (OJIOT), Volume X, Issue X, 20XX

Signal processing

Ceiling
FM-CW radar

For target 1

Distance: 1.0m

1. Peak position
detection

Signal after
A/D process

Distance: 2.0m

Display
amplitude value

2. Tunable bandpath FIR filter

FFT

Displayphase value

Small displacement

Small displacement

2.0mm

2.5mm

For target 2

7.5s

Target 2

1. Peak position detection
Amplitude [A.U.]

Target 1

Figure 12: Setup conditions with 2 targets
Only target 1

2. Tunable band-path FIR filter

1
0.8
0.6
0.4
0.2
0
0

2

4

Amplitude [A.U.]

10.0s

1
0.8
0.6
0.4
0.2
0

Beat frequency [kHz]

2.5mm

0
2

4

Beat frequency [kHz]Figure 14: Block diagram of the proposed multiple
targets detection in signal processing
10.0s

Table 3: Parameters in computer simulations

Only target 2
2.0mm

Parameters
Center frequency f0
Bandwidth of sweep frequency fw
Sweep time twPowertarget 1 + target 2

Time
Distance

Small displacement

7.5s

Bandwidth for FIR filter
B
Number of FFT points
Window function

Values24.15 (GHz)
100, 200, 400, 800(MHz)256, 512, 1024, 2048(µs)
200, 400, 800, 1600,
3200 (Hz)4096
hammingTime

spectrum is obtained. After processing the FFT operaFigure 13: Simulated results of detection for closed tion, the peaks of amplitude value of the distance specmultiple targets
trum are calculated for each user. In the peak position
detection processing, the two frequency value according
to the targets is obtained; then, FIR filters are designed
4.2 FIR filtering
according to the peak positions of desired targets. The
The procedures of the proposed detection method for tunable FIR filter has the center frequency corresponding
multiple closed targets is as follow. We assumed that to the calculated frequency in the peak position detecthe FM-CW radar is located a short distance from a bed tion, and the linear property for the phase value. By usas shown in Figure ??. In this situation, the radio waves ing the designed FIR filter, band-path filtering operation
were radiated from the FM-CW radar, and 2 targets lied is carried out for the distance spectrum. After throughdown on the bed. The distances from the radar to each band-path filter, the amplitude and phase value for eachtarget were different, so that the peaks of distance spec- target are detected correctly.
trum were detected at different frequency. In this case,the detected result shown in Figure 13 is sum of these 2
targets, and it is difficult for detecting both the distanceand phase values for each user correctly.
In order to solve this problem, signal processing withthe tunable FIR filter was used in the proposed detection method. Figure 14 shows the block diagram of the
proposed detection method. At first, the A/D converted
signal is carried out the FFT operation, and the distance

4.3
4.3.1

Computer Simulations
Setup condition

In order to evaluate the performance for FM-CW radarsystem with the proposed method under multiple targets
environment, we carried out computer simulations. Parameters for computer simulations are listed in Table 3,
and the parameters are also based on ARIB standard T73
8

Kazuhiro Yamaguchi, Mitumasa Saito, Takuya Akiyama, Tomohiro Kobayashi, Naoki Ginoza, Hideaki Matsue: Development of FM-CW Radar
System for Detecting Closed Multiple Targets and Its Application in Actual Scenes

Table 4: Setup conditions for targets
Target 1
1.0 (m)
2.5 (mm)10.0 (s)0.80.7[1]. Center frequency was 24.15 GHz, and frequency
bandwidths were 100, 200, 400, and 800 MHz. Notethat the 400 and 800 MHz bandwidth were only used forthe computer simulation because of standards in the Radio Law in Japan. Sweep times were 256, 512, 1024,
and 2048 µs, sampling time of sweep was 0.1 µs, number of FFT points was 4096, and the hamming windows
was adapted as the window function in signal processing. The bandwidths for FIR filter were 200, 400, 800,
1600, and 3200 Hz.
In the following sections, we describe the evaluation
values for analyzing the results of multiple targets detection, and the performance analysis according to bandwidth for sweep frequency, sweep time, bandwidth for
FIR filter, and position of target 2 are described.

0.5

0.4
0.3
0.2
Minimal value
$!"#
!"# =

0.1
0
0

1

2
"#$ 3 %
Beat frequency [kHz]

!

4

5

(a): Amplitude3
Setuped value

Detected value
Setuped value!

2

Evaluation values for amplitude andphase values

Figure 15 shows the evaluation values for detecting theamplitude and phase values of the distance spectrum ofmultiple targets. As evaluation values, we defined thedegree of amplitude separation for amplitude value and
NMSE for phase value.
The degree of amplitude separation is represented by|Pmin |
|P (fmin )|Sk = 10 log= 10 log|Pk ||P (fk )|Maximal value
"!
! =

0.6

Small displacement [mm]4.3.2

Maximal value
"!
! =

0.9

Target 2
2.0 (m)2.0 (mm)
7.5 (s)Amplitude [A.U.]

Parameters
Distance
Amplitude of Displacement
Period of displacement11
Detected value

0

"
!

-1

-2

-3
0

10

20

30

Time [s][dB] ,(b): Phase(13)

Figure 15: Definitions of evaluation values for comwhere k denotes the number of target, Sk denotes theputer simulation
degree of amplitude separation, Pmin denotes minimalvalue of amplitude whose frequency is fmin , and Pk denotes the peak value for k-th target with frequency of fk .
and phase value in (b). As shown in (a), the degrees
The NMSE for phase value is represented byof amplitude separation were about -2.5 dB and -19 dB
with fw = 100 MHz and fw = 800 MHz, respecN∑ |d′ − di |2i(14) tively. Because the resolution of the distance spectrum
NMSE =,′ |2|di
was increased as an increasing the bandwidth of sweep
i=1
frequency, the separation of targets for amplitude value
where N denotes the number of sampling points, di andbecome easily.
d′i denote the sampled signals of detected and setuped
As shown in (b), NMSE was about 2 % with the bandvalues for a target, respectively.
width of sweep frequency fw = 100 MHz, and NMSE
was also improved as an increasing the bandwidth of
4.3.3 Performance for Bandwidth of sweep fresweep frequency. Although there was a few disadvanquency
tage for NMSE of target 2, the multiple targets detections
Figure 16 shows the evaluation values versus the band- could correctly achieved because the degree of amplitude
width of sweep frequency fw for amplitude value in (a) separation with -1 dB and NMSE with 6 % were enough
9

Open Journal of Internet of Things (OJIOT), Volume X, Issue X, 20XX

00
! = 1024 "#-2$ = 200 Hz

Degree of amplitude separation [dB]

Degree of amplitude separation [dB]

-2
-4
-6
-8
-10
-12

Target 1-14

Target 2

-16
-18
-20

-4
-6
-8
-10

Target 1-12

Target 2-14"# = 200 MHz= 200 Hz

-16
-18
-20
-22

-22

-24

-24
0

100 200 300 400 500 600 700! : Bandwidth of sweep frewuency [MHz]

0

800

256

768 1024 1280 1536 1792 2048

512

! : Sweep time [us](a): Amplitude(a): Amplitude

7.0%

7.0%
! = 1024 "#$ = 200 Hz

6.0%

6.0%

5.0%

! = 200 MHz

5.0%

4.0%

NMSE

NMSE

= 200 Hz

3.0%

4.0%
Target 1

3.0%

Target 2
Target 1

2.0%

2.0%

Target 2

1.0%

1.0%

0.0%

0.0%
0

100 200 300 400 500 600 700! : Bandwidth of sweep frequency [MHz]

800

0

256

512

768 1024 1280 1536 1792 2048
! : Sweep time [us](b): Phase(b): Phase

Figure 16: Evaluation values versus bandwidth ofsweep frequency

Figure 17: Evaluation values versus sweep timetarget 2 was about 4 % with tw = 2048 µs. Because
the resolution for distance spectrum was decreased as anincreasing the sweep time, the sweep time should be lessthan 1024 µs.

values for detecting multiple targets in practical use.

4.3.4

Performance for Sweep time

Figure 17 shows the evaluation values versus the sweep
time tw for amplitude value in (a) and phase value in(b). As shown in (a), the degree of amplitude separation for target 1 kept about -4 dB in accordance not tothe sweep time. The degree of separation for target 2
had -1 dB during the sweep time tw = 256 ∼ 1024 µs.
In the case with tw = 2014µs, the degree of amplitude
separation was almost 0 dB. That is, it was difficult to
detect the peak value of amplitude for target 2. Moreover, compared to the result in (b), the worst NMSE for

4.3.5

Performance for Bandwidth of FIR filter

Figure 18 shows the evaluation values versus the bandwidth of FIR filter B for amplitude value in (a) and phasevalue in (b). As shown in (a), the degree of amplitude
separation for target 1 kept -2 dB in accordance not tothe bandwidth of FIR filter B. When B was more than1600 Hz, the degree was more than -1 dB, therefore, it
was difficult to detect the peak value.
As shown in (b), NMSE for target 1 was less than 3

10

0

0

-2

-2
Degree of amplitude seperation [dB]

Degree of amplitude seperation [dB]

Kazuhiro Yamaguchi, Mitumasa Saito, Takuya Akiyama, Tomohiro Kobayashi, Naoki Ginoza, Hideaki Matsue: Development of FM-CW Radar
System for Detecting Closed Multiple Targets and Its Application in Actual Scenes

-4
-6
-8

Target 1-10

Target 2

-12
-14
-16

-18
-20

! = 200 MHz-22! = 256 "#$ = 200 Hz

-4
-6
-8
-10

( ! =200 MHz)
⣔ิ6
Target 2( ! =200 MHz)
⣔ิ3
Target 1( ! =400 MHz)
⣔ิ4
Target 2( ! =400 MHz)
⣔ิ1
Target 1( ! =800 MHz)
⣔ิ2
Target 2( ! =800 MHz)

-12

-14
-16

-18
-20
-22

! = 256 "#

䝍
䝀
䝍
䝀
䝍
䝀
䝍
䝀
䝍
䝀
䝍
䝀

⣔ิ5
Target 1

-24

-24
0

1

400 800 1200 1600 2000 2400 2800 3200$: Bnadwidth of FIR filter [Hz]1.2(a): Amplitude

1.4
1.6
1.8
Position of target 2 [m]2(a): Amplitude
7.0%

7.0%
6.0%

$! = 200 MHz! = 256 "#

6.0%

5.0%

Target 1

5.0%! = 256 "#$ = 200 Hz

NMSE

NMSE

Target 2
⣔ิ

4.0%

⣔ิ

3.0%

⣔ิ
⣔ิ

2.0%

䝍䞊
Target 1
䝀䝑䝖䠍( ! =200 MHz)䝍䞊
Target 2
䝀䝑䝖2( ! =200 MHz)䝍䞊
Target 1
䝀䝑䝖䠍( ! =400 MHz)䝍䞊
Target 2
䝀䝑䝖2( ! =400 MHz)䝍䞊
Target 1
䝀䝑䝖䠍( ! =800 MHz)䝍䞊
Target 2
䝀䝑䝖2( ! =800 MHz)

4.0%

3.0%
2.0%

⣔ิ

1.0%

1.0%

⣔ิ

0.0%

0.0%
0

400 800 1200 1600 2000 2400 2800 3200$: Bandwidth of FIR filter [Hz]1(b): Phase

1.2

1.4
1.6
1.8
Position of target 2 [m]2(b): Phase

Figure 18: Evaluation values versus bandwidth of Figure 19: Evaluation values versus positions of tarFIR filter
get 2%, but NMSE for target 2 was more than 5 % with B =1600 and 3200 Hz. Because the widely bandwidth of
FIR filter was enough not to cut the signal of the othertarget completely, the bandwidth of FIR filter should beless than 1600 Hz.

4.3.6

Performance for distance between targets

Finally, we show the result for detecting multiple targets
when the target 2 comes close to the target 1 from 2 m to
1.5 m. Figure 19 shows the evaluation values versus the
position of target 2 from the radar for amplitude value in(a) and phase value in (b). The position of the target 1
was 1 m from the radar.

Compared to the results, the degree of amplitude separation and NMSE become depleted as the target 2 approaches to the target 1. As shown in (a), when the bandwidth of sweep frequency was more than 400 MHz, thedegree of amplitude separation had good property which
enough to detect the peaks. However, in the case with
fw = 200 MHz, the degree for target 2 was about -0.3
dB, and it was difficult to detect the peaks.
As shown in (b), when fw was less than 400 MHz,NMSE could be kept about less than 5 %. However, inthe case with fw = 800 MHz, NMSE become depleted.
It was difficult to detect peaks of amplitude for targets
as decreasing distance between targets. Therefore, thecenter frequency of FIR filter was not enough to cut the11

Open Journal of Internet of Things (OJIOT), Volume X, Issue X, 20XX

other target’s signal, and the imperfect FIR filter influenced NMSE values. Although there were a few difficulty for determining the parameters of the proposed detecting method for FM-CW radar, the proposed detecting
method could be effective for detecting the distance andthe small displacement at the same time under multiple
targets environments.

5

ACKNOWLEDGEMENTS
A part of this work was supported by “Ashita wo Ninau
Kanagawa Venture Project” of Kanagawa in Japan. The
authors appreciate Prof. Toshio Nojima at Hokkaido
University in Japan getting the valuable advices for analyzing the safety properties of the developed FM-CW
radar system according to the safety guideline.

R EFERENCES

D ISCUSSIONAs related works, MIT group reported the radar systemfor detecting human breathing in [12]. The system could
also detect the movement, and the human breathing in
the room could be detected clearly. However, in Japan,
the bandwidth for sweep frequency was strongly smaller
than the MIT’s radar system because of the ARIB standard T73. As shown in figure 3, the resolution was depending on the bandwidth; therefore, the smaller bandwidth influence the detected distance and small displacement. Moreover, under closed multiple targets environment, some distance between radars and each target must
be required for separating the distance spectrum of eachtarget. Therefore, in this paper, we used a tunable FIR
filtering method in signal processing for detecting closed
multiple targets at the same time.

6

C ONCLUSION

In this paper, a FM-CW radar system with 24 GHz bandwith tunable FIR filter for detecting closed multiple moving targets with small displacements was described. The
proposed detecting method generates tunable FIR filter
whose center frequency is corresponding to the peak positions of distance spectrum of each target. The tunable
FIR filtered signal can be detected the distance and displacement for each target correctly. In computer simulations, performances of FM-CW radar system underclosed multiple moving targets environment was analyzed in accordance with the bandwidth of sweep frequency, sweep time, bandwidth of FIR filter, and the distance between targets. As the result, the 24 GHz FMCW radar with the proposed detection method could effectively detect both the distance and the small displacement for each target under the multiple moving targets
environments. And it was confirmed that the proposed
detection method can detect both the distance and small
displacement correctly when the distance between targets was 0.5 m.
As future works, we try to hardware implementationof the proposed FIR filtering and the field experiments.
12[1] ARIB STD-T73 Rev. 1.1, Sensors for Detectingor Measuring Mobile Objects for Specified Low
Power Radio Station, Association of Radio Industries and Businesses Std.
[2] S. MIYAKE and Y. MAKINO, “Application of
millimeter-wave heating to materials processing,”
IEICE transactions on electronics, vol. 86, no. 12,
pp. 2365–2370, dec 2003.
[3] M. Skolnik, Introduction to Radar Systems.
Graw Hill, 2003.

Mc-[4] S. Fujimori, T. Uebo, and T. Iritani, “Short-range
high-resolution radar utilizing standing wave formeasuring of distance and velocity of a moving target,” ELECTRONICS AND COMMUNICATIONSIN JAPAN PART I-COMMUNICATIONS, vol. 89,
no. 5, pp. 52–60, 2006.
[5] T. Uebo, Y. Okubo, and T. Iritani, “Standing wave
radar capable of measuring distances down to zero
meters,” IEICE TRANSACTIONS ON COMMUNICATIONS, vol. 88, no. 6, pp. 2609–2615, jun 2005.
[6] T. SAITO, T. NINOMIYA, O. ISAJI, T. WATANABE, H. SUZUKI, and N. OKUBO, “Automotive fm-cw radar with heterodyne receiver,” IEICE
transactions on communications, vol. 79, no. 12,
pp. 1806–1812, dec 1996.
[7] W. Butler, P. Poitevin, and J. Bjomholt, “Benefits ofwide area intrusion detection systems using fmcw
radar,” in Security Technology, 2007 41st AnnualIEEE International Carnahan Conference on, Oct2007, pp. 176–182.
[8] K. Yamaguchi, M. Saito, K. Miyasaka, and H. Matsue, “Design and performance of a 24 ghz band
fm-cw radar system and its application,” in Wireless and Mobile, 2014 IEEE Asia Pacific Conference on, Aug 2014, pp. 226–231.
[9] K. Yamaguchi, M. Saito, T. Akiyama,
T. Kobayashi, and H. Matsue, “A 24 ghz band
fm-cw radar system for detecting closed multiple
targets with small displacement,” in Ubiquitousand Future Networks (ICUFN), 2015 SeventhKazuhiro Yamaguchi, Mitumasa Saito, Takuya Akiyama, Tomohiro Kobayashi, Naoki Ginoza, Hideaki Matsue: Development of FM-CW Radar
System for Detecting Closed Multiple Targets and Its Application in Actual Scenes

International Conference on, July 2015, pp.
268–273.

According to the guideline [15], these parametersmust be satisfied as[10] M. Skolnik, Radar Handbook, Third Edition.
McGraw-Hill Education, 2008.

E ≤ 61.4 [V/m] ,P ≤ 1 [mW/cm2 ] .
[11] W. Sediono and A. Lestari, “2d image reconstruction of radar indera,” in Mechatronics (ICOM),
2011 4th International Conference On, May 2011, Therefore, the developed 24 GHz FM-CW radar system
pp. 1–4.
in this paper sufficiently satisfies the conditions in the[12] F. Adib, H. Mao, Z. Kabelac, D. Katabi, and R. C. guideline.
Miller, “Smart homes that monitor breathing andheart rate,” in Proceedings of the 33rd Annual
ACM Conference on Human Factors in Computing
Systems, ser. CHI ’15. New York, NY, USA:ACM, 2015, pp. 837–846. [Online]. Available:
http://doi.acm.org/10.1145/2702123.2702200

AUTHOR B IOGRAPHIES
Kazuhiro Yamaguchi wasreceived the M.S. and Ph.D
degrees in information sciencefrom Hokkaido University,
Hokkaido, Japan, in 2009 and2012. He is currently an Assistant Professor at the Tokyo
University of Science, Suwa,
in Japan. His research interests
include Internet of Things,
wireless communication, signal
and image processing, and[13] C95.1-2005, IEEE Standard for Safety Levels with
Respect to Human Exposure to Radio Frequency
Electromagnetic Fields, 3 kHz to 300 GHz, IEEE
Std.
[14] ICNIRP, “ICNIRP STATEMENT on the guidelines
for limiting exposure to time‐ varying electric,
magnetic, and electromagnetic fields (up to 300ghz),” Health Physics, vol. 97, no. 3, pp. 257–258,
2009.
holography.

[15] Ministry of Internal Affairs and Communications
http://www.tele.soumu.go.jp/resource/j/material/
dwn/guide38.pdf.

A PPENDIX
In general, electromagnetic wave must be satisfied theguidelines on human exposure to electromagnetic fields,
where it have been instituted in various organizations.
IEEE C95.1 in USA [13] and ICNIRP in Europe [14] are
the guidelines, and MIC also have instituted the guideline in Japan [15].
Developed 24 GHz FM-CW radar in this paper havethe properties as follow. The power of the transmitter is
7 [mW], the transmitting antenna gain is 11 [dBi], theeffective radiated power is 88 [mW], the radiation angleof the transmitting wave is about 50 [degree], and the
distance between the transmitter and the human is 2.5[m]. According to the radar equation, the electric fieldstrength E and the power density P on the human bodyis calculated as√
30 × 0.088= 0.65 [V/m] ,
E=
2.5
0.652
E2
=
= 1.12 × 10−4 [mW/cm2 ] .
P =
z0
120π
13

Mitsumasa Saito was received
the B.S. degree from University of Electro-communications,Tokyo, Japan, in 1978. From1978 to 2006, he has been engaged in research and development of security and multimedia
devices, electronic display for
consumer electronics at SONY
Corporation in Japan. In 2009,
he established company of CQS net Inc. Kanagawa, Japan. His
research interests include Internet of Things, radar technology, and signal and image processing.
Takuya Akiyama was received
the B.E. degree from Tokyo University of Science, Suwa, Japan,
in 2014. He is currently working
toward the M.S degree.

Open Journal of Internet of Things (OJIOT), Volume X, Issue X, 20XX

Tomohiro Kobayashi was received the B.E. degree from
Tokyo University of Science,
Suwa, Japan, in 2015. He is currently working toward the M.S
degree.

Naoki Ginoza is currently
working toward the B.E. degree
at Tokyo University of Science,
Suwa, in Japan.

Hideaki Matsue was received
the B.S. and Ph.D degreefrom University of Electrocommunications and Tokyo
Institute of Technology, Tokyo,
Japan, in 1978 and 1993,
respectively.
From 1978 to
2004, he has been engaged inresearch and development ofdigital microwave radio-relay
system, network architecture
for personal communication at
NTT Electrical Communication Laboratories in Japan.
He is currently a Professor at the Tokyo University of
Science, Suwa, in Japan. His research interests include
Internet of Things, network architecture, and wirelesscommunication.

14