A Multistatic Microwave Radar Sensor for Short Range Anticollision Warning
2270 IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, VOL. 49, NO. 6, NOVEMBER 2000
A Multistatic Microwave Radar Sensor for
Short Range Anticollision
Abstract— An adequate radar technology for the detection and
localization of obstacles before, behind and on the sides of a moving
car is of primary importance to realize on-board devices able to
perform different tasks such as parking, stop and go, and pre alarm
of the frontal air-bags. In these situations, the radar must acquire the
position of the obstacles located at short distances from the car. This
acquisition must be carried out with high radial and angular
resolution; the former needs large radio frequency bandwidth, the
latter requires large antennas and this means that the investigation
area of the radar is certainly in the near field of the antenna. It is for
this reason that traditional anti-collision systems based on phase
array antennas prove to be unsuited to perform these tasks in the
short range . The solution that we are proposing is based on sev-
eral independent microwave radar sensors with wide angle of view
connected to a central processing unit able to define the position and
the relative velocity of the nearest obstacles. This prototype works in
the 13.4–14 GHz frequency range at low power (16 dBm eirp) in
accordance with the most recent ETSI and CEPT/ERC
Recommendations and it has been realized with microstrip tech-
nology so that thanks to its reduced size each device can be em-
bedded easily in a bumper.
Index Terms— Image reconstruction, microwave circuits,
at a time and, through a triangulation algorithm, the system
finds the ( ) position of the nearest obstacles in each area.
Fig. 2 shows the prototype of a radar sensor and where the
sensors are placed in the vehicle: four sensors are mounted in the
Front ( ) and four in the Back ( ). The larger the
number of sensors, the higher the degree of accuracy in the
localization of the obstacles and by separating the sensors with a
step of 0.3 meter the specifications defined in Fig. 1 are met.
The proposed system is based on microwave FMCW radar
sensors and a PC-DSP system. The working frequency range
is between 13.4 and 14 GHz, 40 mW of maximum radiated
peak power according to the CEPT Recommendation T/R 60-
01 and the ETSI 300 440 for low power radio-localization
equipment for detecting movement and radio-determination.
Low cost and reduced size of the whole system are of para-
mount importance, for this reason we have used hybrid mi-
crostrip technology and large scale components to realize the
FMCW transceiver (size of mm), and a central
digital signal processor (DSP) which performs, round robin
for each side of the vehicle, the necessary computation.
II. SYSTEM ARCHITECTURE
SAFETY in driving could be increased significantly with the assistanceof a device able to provide the distance and the relative velocity of the
nearest obstacles and it could be useful also in other situations such as
parking, stop-and-go and pre-
alarm of the frontal air-bags , .
To acquire the data necessary to perform these tasks in
every weather condition a reliable localization of the obstacles
before and behind the vehicle must be carried out. In Fig. 1
are shown the investigated space and the specifications of the
range of the antenna and the resolution required.
The peculiarity of this application in the short range is the wide
basis of the investigated areas: a characteristic that, to-gether with
the high angular resolution required, can’t be man-aged
successfully by the usual phase array techniques. In fact high
accuracy of the angular position is obtained using large antennas
so that the investigation area falls in their near field.
To measure the position ( ) of the nearest obstacles located in
each one of the four areas, we propose a distributed solution
based on several independent microwave radar sensors placed
round the vehicle. These sensors are turned on in sequence one
Manuscript received January 27, 1997; revised December 4, 1998 and
November 3, 1999.
The author is with CNR-CESPA, Dipartimento di Elettronica, Politecnico
di Torino, 10129 Torino, Italy (e-mail: email@example.com).
Publisher Item Identifier S 0018-9545(00)11224-1.
The architecture of the whole system is reported in Fig. 3; the
sensors and the computer are connected by RS-232 and supplied
by 12 V, in this way a thin and easy interconnection is realized.
Through serial interconnection the DSP performs the following
cycle in sequence on each radar sensor: starting of the measure-
ment cycle, reception of the sampled intermediate frequency
signal and processing of the spectrum analysis to evaluate the
distance of the nearest objects from the selected sensor. At the
end of a complete round robin cycle the DSP calculates the
position ( ) of the nearest obstacles on each side of the vehicle
and sends these data to the display or to the cruise control.
III. MICROWAVE RADAR SENSOR
Each radar sensor is realized on four different layers (see Fig. 4):
the FMCW transceiver (on layer 1), the Intermediate Frequency
subsystem (IF on layer 2), the automatic gain con-trolled amplifier
(AGC on layer 3) and a microcontroller (layer 4). On layer 2 the dc
bias network of the HEMPT’s are also implemented. The front end is
realized with hybrid technology (Diclad 527, mils; )
using 8 low-cost HEMPT (Nec NE32484A); the VCO is able to
sweep on the range GHz with 0 dBm output power. The
swept signal supplies, by means of a power divider, the HEMPT T3
(mixer) and the couple T6–T7 (transmitter power amplifier). A two-
on layer 3) and acquired by the microcontroller (Motorola HC11
on layer 4) and finally transferred to the remote DSP system. The
local microcontroller controls the gain of the AGC IF am-plifier
(using the multiplier Analog Device AD834 on layer 3), generates
the predistorted modulation waveform (using the Na-tional
DAC0832, 8 bit 1 Msps, on layer 4) to have a linear chirp
transmitted signal, manages the communication with the remote
system and switches on and off the transceiver.
The front-end overall performances allow a 35-dB S/N of the
IF signal in the worst case, that is with an obstacle of 1 m radar
cross section located at 5 m in front of the antenna. In this way
the degree of accuracy in the measurement of the radial distance
is of about one centimeter thanks to the large bandwidth used
(bandwidth 600 MHz, resolution 0.25 m) and to the processing.
IV. DIGITAL PROCESSING
The processing system enables and queries, in round robin, all
the radar sensors and acquires the sampled intermediate fre-
quency signals (each IF sampled signal is packed in an 80-byte
array). Fig. 7 shows the block diagram and the picture of the fast
Fourier transform (FFT) board; the system is realized by means
of two cooperating processors, the first one (Intel 80 486) man-
ages the communication with the radar sensors and passes the IF
streams to the second (TRW TMC2310), which is specialized in
very fast windowing and FFT processing (windowing zero
padding on 1024 byte in 612 s).
The result of the spectral analysis is the reflectivity diagram
RD( ) of the scenario seen by the radar sensor , :
and radial distance and radial velocity between
antenna and the scattering objects;
carrier wavelength (2.2 centimeter);
system resolution (25 centimeter);
2272 IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, VOL. 49, NO. 6, NOVEMBER 2000
Fig. 3. System architecture.
Fig. 4. Block diagram of the microwave (13 4 4 14 GHz) FMCW Radar Sensor.
transmitted signal power (10 dBm);
total gain of the system;
IF intermediate signal in time;
modulation period (80 s);
radial reflectivity of the observed scenery;
point spread function of the whole system (4)
The i80486 processes the reflectivity diagram RD( ) in order
to verify the presence of any obstacles and to extract their ra-dial
distance together with their echo intensity; in this way each
sensor compiles its own list of the obstacles which are detected in
the locations of the peaks in the reflectivity diagram RD .
At the end of the round robin cycle a list of the obstacles for
each radar sensor is available and the localization process can
start to evaluate, for each side of the vehicle, the presence of at
least one obstacle and, in this case, to perform a triangulation
process to calculate the (
) of its position and show it on
display; a complete cycle is performed any 20 ms.
process finds the () positions of the
obstacles present on each side of the vehicle by triangulation
on their radial distances between the first and the last sensor of
side considered (using the first list of
one , whereis the number of sensors on the vehicle
side). To do this in a proper way one needs to know the
correct association between the two sets of radial distances: if on
one side of the vehicle there are present obstacles, the system
has to find the right association among possible ones. This
task is carried out using the obstacle lists of the other sensors
(intermediate sensors ) to build an association matrix
(AM) of merit figures of the possible associations (AM of
elements). For any association ( ) (obstacle of the
obstacle of the ) the position of the hypothetical
obstacle ( ) is evaluated by intersecting the two circles
having as radius the two radial distances considered [
] and centers located on the first and last
After that, the expected radial distances from each
intermediate sensor ( ) are evaluated and used to calculate the
merit figure of the actual association as the sum of the squared
relative errors between the expected radial distances and the
actual closest ones [ with such as
GIUBBOLINI: MULTISTATIC MICROWAVE RADAR SENSOR 2273
Fig. 6. Protoype radiation diagrams (vertical and horizontal planes at 13.4,
13.7, and 14.0 GHz).
Fig. 5. Photos of the prototype radar sensor: microwave and dc layers.
By analyzing the association matrix the obstacle ( ) po-
sitions are obtained. This process searches for the minimum
values in every th row of AM: the two radial distances asso-
ciated with this AM element permit to obtain, by triangulation,
the ( ) position of the th obstacle.
obstacle configurations with discrete and distributed objects
(in relation to the spatial resolution of the radar of 25 cm).
These configurations have been chosen to test the robustness
of the tri-angulation process in solving operative ambiguities
and to esti-mate the precision while localizing the obstacles.
In Fig. 8 a test set-up with the associated screen output is shown.
It is possible to see the correspondence between the spa-tial position
of the obstacles ( ) and the displayed output.
The characterization of the accuracy of the whole system
has been obtained with one microwave rear reflector located
in dif-ferent positions in the frontal operative range (see Fig.
1) on a grid of 0.5 m step on both and axis. Fig. 9 shows
the lo-calization error as the mean value on 100 acquisitions
of the error between the measured position ( ) and the
actual one ( ):
V. SYSTEM CHARACTERIZATION
The whole system has been characterized in laboratory by
using four radar sensors and analyzing their IF signals in several is always less than 1 cm.
2274 IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, VOL. 49, NO. 6, NOVEMBER 2000
Fig. 8. Test setup example and associated display output.
Fig. 9. System accuracy with one obstacle in the investigated area.
Fig. 7. Block diagram of the DSP system and photo of the FFT board.
A set of characterizations with a second disturbing target has
shown that until the distance between two obstacles is greater
than the resolution of the radar (25 cm) the accuracy in local-
izing the obstacles is kept under 1 centimeter on both of them.
Similar considerations are possible for more discrete targets.
The system has been tested also for the robustness of the lo-
calization process. All the tests with discrete obstacles
separated by a distance greater than the radar resolution have
been passed without ambiguity by the triangulation process.
Special cases have been found when the first and the last
sensor did not “see” the same number of obstacles; this is
possible for one of the fol-lowing reasons:
— the areas investigated by the two sensors did not
— the obstacles are so close to each other that one or both
the sensors are unable to resolve them,
— one distributed obstacle (larger than the spatial resolu-
tion) is present in the scenario.
In all these cases, the association matrix is rectangular rather
than square, and fewer obstacles than the real number of scat-
tering centers have been detected.
The first situation occurs in the lateral sides of the
investigated area and can be controlled by accurate
positioning of the sensor orientations.
In the second situation the system gives the location of two
or more merged scattering centers with a lower accuracy.
Finally, in case of a distributed obstacle, the system can
give only its radial minimum distance from the vehicle.
A distributed microwave radar sensor for the short-range an-
ticollision warning has been presented. The proposed system is
realized by several FMCW microwave transceivers located all
around the vehicle and a central DSP system. The system shows
on a display, every 20 ms, the ( ) position of all the obstacles
present around the vehicle in the short range (until 3 meter).
The operative frequency range and the radiated power
follow the most recent International Recommendations and it
is pos-sible to classify the system as a low power device for
radio-de-termination. The system has been realized using
consumer hy-brid technology.
The characterization of the system has shown a degree of
accuracy higher than 1 cm on the whole operative range. The
process implemented by the system works properly without
any ambiguities on the nearest obstacle, on the whole oper-
ative range when only discrete obstacles are present. In case
the nearest obstacle is a distributed obstacle (for example a
guardrail on the right-hand side of the car), the system can
give only its minimum distance.
This feature will permit the implementation of many func-
tions such as the parking aids, the stop-and-go and the pre-
alarm of the air bags.
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Luigi Giubbolini was born in Imperia, Italy, in 1963.
He received the Dr. Eng. degree in electronics from the
Polytechnic of Turin, Turin, Italy, in 1989.
Since 1989, he has done research in the Depart-ment
of Electronics of the Polytechnic of Turin on radar
imaging for automotive applications in the EEC
PROMETHEUS project. His research interests con-
cern the microwave imaging techniques, microstrip
circuits and digital signal processing. He has worked as
a Research Consultant for Magneti Marelli Com-pany,
where he was involved in the developing of a
Lidar anticollision system for vehicles. Presently, he
is with the official staff of the “Antennas and
Propagation Study Center” of the Italian Research
National Council, Turin, Italy, as Researcher, where he takes part in several
EC and Italian research projects.