Research on Surface Movement Radar Based on Adaptive Target
Detection Technology
Sen Ren
1
, De Zhang
2
, Jiming Zhang
3
and Yong Zhang
3
1
Technical Centre Air Traffic Management Bureau, CAAC, Beijing, China
2
Air Traffic Regulation office, CAAC, Beijing, China
3
The Second Research Institute of CAAC, Chengdu, China
{Sen Ren, De Zhang, Ji-ming Zhang, Yong Zhang}rensen@atmb.net.cn, zhangde@caac.gov.cn, zjmyzkk2000@163.com,
zhangyong3725@163.com
Keywords:
Adaptive clutter map, Surface movement radar, Target detection, STC.
Abstract: Aiming at the situation of heavy traffic in civil airport, complicated scene in airport and complex weather (foggy
weather), and this paper introduces an airport surface movement radar based on adaptive target detection
technology. The signal processing design mainly adopts adaptive STC (Sensitivity Time Control) and adaptive
clutter detection technology to improve the target detection probability (>97%), reducing the false alarm
probability (<3×10
-7
) and improving the system's anti-interference and environmental adaptability. That can
improve the airport operating efficiency while ensuring the flight safety of the aircraft, meeting the requirements
of civil aviation CNS equipment.
1INTRODUCTION
With the development of economic activities, the
rapid development of air transport industry and the
growing fleet size of airlines have resulted in the
rapid increase of aircraft take-off and landing
frequency in the airport. The frequency of aircraft
and motor vehicle movements has also become
increasingly frequent simultaneously. In the area of
airport surface, the probability of collisions between
take-off, landing and taxiing has greatly increased
as a result of the obstruction of the air traffic
controllers and other irresistible factors such as the
weather (rain, snow and fog). Therefore, it is
becoming increasingly prominent to effectively
solve the problem of traffic congestion and conflicts
in the airport, and the management of aircraft and
mobile vehicles at airports is becoming increasingly
important.
As an important equipment of civil air traffic
control field, Surface Movement Radar (SMR) not
only can detect and locate the target in real time, but
also can accurately obtain the information such as
the movement trajectory of the aircraft and vehicle
in the conflicts of aerodrome surface. However it
also appeared many problems in the course of
operation. In some airports, the effective reflection
area of buildings is large, and small targets
(vehicles, etc.) near tall buildings are easily lost.
Airports with damaged clearances have a serious
impact on the increase of false targets due to
complex electromagnetic environment, crosstalk
and multipath system performance. Some airports
have poor weather conditions, radar systems can
easily detect false targets and lose real targets,
greatly reducing SMR’s performance.
At present, they mainly use TERMA from
Denmark and INDRA from Spain in the domestic
airports. In recent years, as the state vigorously
promote the civil aviation CNS equipment
localization process requirements, the domestic
SICHUANG company of CETC-38th and other
companies have successfully developed a surface
movement radar system and has achieved "Civil
Aviation Air Traffic and Communications
Navigation Surveillance Equipment Provisional
License". These devices in the licensing process of
certification, the system requires to be strictly
validated and system tested to ensure that their
systems performance and reliability meet the
relevant technical requirements.
358
Ren, S., Zhang, D., Zhang, J. and Zhang, Y.
Research on Surface Movement Radar Based on Adaptive Target Detection Technology.
In 3rd International Conference on Electromechanical Control Technology and Transportation (ICECTT 2018), pages 358-363
ISBN: 978-989-758-312-4
Copyright © 2018 by SCITEPRESS Science and Technology Publications, Lda. All rights reserved
2 SURFACE MOVEMENT
RADAR SOLUTION
2.1 Solution
The current airports face many problems, and it lead
that the existing equipment cannot meet the needs
of the airport operation. It is a better solution to
select the appropriate airport surface movement
radar, which should have the following aspects:
Powerful target processing ability;
Higher of the detection probability, lower
of the false alarm probability;
Stronger of anti-interference and
environmental adaptability.
It is the basic requirement to have the above
capability that SMR can enter the Chinese civil
aviation market for sales and usage. The specific
targets should meet the requirements of civil
aviation industry standard MH / T4043-2015
"Technical Requirements for Civil Aviation X-band
Surveillance Movement Radar".
Based on adaptive target detection technology,
the surface movement radar mainly uses adaptive
STC gain control to improve the dynamic range of
the system greatly. The gain control voltage
changes proportionally with the intensity of the
input clutter so as to ensure that both the strong and
the weak targets can be detection. According to
meteorological conditions and geographical
conditions, the clutter real-time updates using
adaptive clutter detection technology. The adaptive
threshold detection can greatly improve the target
detection capability and anti-interference ability
under different scenarios and weather.
2.2 Surface Movement Radar Signal
Processing Design
The signal processing flow of surface movement
radar is shown in Fig.1. It mainly complete target
detection, reporting the original trace and the
background clutter to the back-end recorder.
AD collection
Pulse compression
Adaptive STC
gain control
Echo signal LFM
DDC down conversion
Adaptive clutter
detection
Detection
results:
target
Data:
backgroun
d clutter
Signal processing design
Fig.1 Surface movement radar signal processing
As shown in FIG.1, the echo signal is collected
by the AD. Adaptive STC gain control is performed
according to the collected data to ensure that the
signal has no saturation distortion. Subsequently,
the signal is down-converted, pulse-compressed by
DDC (Direct Digital Control). Finally, it outputs
background clutter and target information after the
adaptive clutter detection.
Signal processing design mainly uses adaptive
STC gain control and adaptive clutter detection
techniques. The following will be described in
detail.
3 THE MAIN TECHNICAL
REALIZATION OF SURFACE
MOVEMENT RADAR
3.1 Adaptive STC gain control
technology
3.1.1 Algorithm Design and Implementation
At present, STC to control the sensitivity of receiver
Research on Surface Movement Radar Based on Adaptive Target Detection Technology
359
mainly depends on the rule of the strength of
short-range clutter with distance (time) change, and
setting the value of the STC attenuation responded.
However, these have some disadvantages, such as
the inability to manually calibrate the STC curve for
a particular area and the inability to detect small
targets in the context of a strong clutter. This paper
designs and implements a relationship curve
between STC gain and time. The curve is adaptively
generated according to the specific environment
scenario. The specific implementation flow is
shown in Fig.2. This method not only keeps the
input signal level at a reasonable magnitude, but to
complete the target detection without loss of echo
signal power.
Signal processing
STC compensation
Data processiing
STC attenuation
control
STC graph
RF echo signal
Fig.2 The workflow of adaptive STC
a) According to the actual scene, STC
two-dimensional (angle-distance dimension) graph
is established, and the size of STC sub-module is
determined according to the actual needs, including
the angle interval and distance interval;
b) The radar system enters the "adaptive
STC curve establishment" mode, and the signal
processing board establishes an adaptive STC curve
according to the data intensities in different
distances collected from different angles so as to
automatically change the STC attenuation, so that
the input signal strength is maintained within the
receiver's dynamic range.
c) After the STC curve is established, the
system works normally. After STC attenuation and
controlled, the intensity of echo signal in the
channel keeps within the dynamic range of the
receiver. It can generate the STC waveform to use a
digitization method. Each amount of attenuation is
calibrated manually after the adaptive STC is
generated to determine the error between the actual
gain and the commanded gain.
d) In order not to lose the signal power, STC
compensation is performed on the received echo
signal in the signal processing board to restore the
real signal;
e) Carry on the subsequent processing to the
compensated signal, it finishes the target’s STC
control and realized.
3.1.2 Simulation test results
Fig.3-1 shows the background of the original clutter
with no STC control at the airport. It shows that the
terminal and office building are obviously saturated
and there is a piece of strong background clutter
(104 square meters magnitude of RCS (Radar Cross
Section)), which inundated many small targets,
leaving observers unable to observe the area.
Fig.3-2 shows the clutter background after adaptive
STC processed. It can be seen that both the terminal
and the office building undergo STC attenuation,
and the entire clutter background remains within a
stable range, avoiding saturation and blocking of
signals. Like these, it not only solves the problem of
strong clutter submerging small targets and
improves the detection probability, but also reduces
the false alarm and missed alarm caused by system
saturation.
Fig.3-1 Original clutter background Fi.3-2 Clutter background after adaptive STC processed
ICECTT 2018 - 3rd International Conference on Electromechanical Control Technology and Transportation
360
3.2 Detection technology of adaptive
clutter map
3.2.1 Algorithm design and implementation
of clutter map detection
Clutter detection recording clutter in real time is a
time-domain adaptive threshold detection method. It
can analyze the existence, strength and changes of
clutter in order to change the characteristics of the
processing system. In doing so, it can adapt to the
changing clutter environment. After pre-processing,
the signal processor sends the pulse pressure result
to Doppler filter of zero speed for filtering. One
data are recursively calculated to update the clutter
data in real time and adjust the clutter detection
threshold. Another data compared with the adaptive
clutter threshold, when the data is greater than the
threshold, then it is the target. The process shown in
Fig.4:
Pulse pressure
results
Clutter map
update
Adaptive
threshold
detection
Doppler filter of
zero speed
Real-time
data
Target
output
Fig.4 Flow chart of adaptive clutter detection
3.2.2 High-precision clutter map storage
The system realizes the surveillance of the entire
airport surface. The structure of clutter map storage
is divided by azimuth and distance units. The
azimuth units are determined according to the
system's angular accuracy and angular resolution.
Based on the system's ranging precision and angular
resolution, the distance units are determined. The
specific schematic diagram shown in Fig.5:
Fig.5 The division of clutter map storage space
3.2.3 Clutter map update
The clutter map update uses recursive computation
and its data is stored by the system. When a new
frame of data arrives, the system reads the clutter
map data and recursively computes with the new
data to update the clutter map data in real time. The
recursive operation shown in Fig.6:
1
Z
K
n
XternE
n
Yputut O
1n
Y
-+
+
Fig.6 Block diagram of the clutter update
Its expression is
nnn
XKYKY
1
)1(
(1)
K in the formula (1) is a forgetting factor of less
than 1. Z
-1
represents the delay of the antenna
scanning period (clutter map memory). After the
antenna is scanned in multiple circles, the amplitude
clutter map stores the average clutter value of the
distance element in the corresponding azimuth.
3.2.4 Simulation results
Fig.7 shows the single-frame data clutter detection
diagram. Blue represents the raw data the system
received, while the purple colour represents the
noise floor. Green is the adaptive clutter detection
threshold. When the original data is greater than the
adaptive clutter detection threshold, it is the target.
Research on Surface Movement Radar Based on Adaptive Target Detection Technology
361
Fig.7 The clutter detection of single-frame data
Fig.8-1 and Fig.8-2 show the multi-frame raw
data and adaptive clutter detection results
respectively. From the original data, it can be seen
that the terrain is complex and the clutter is more.
After the adaptive clutter threshold detection, the
detected target is very few with only two targets.
Thus it greatly reduces the false alarm probability of
the system and improves the detection performance
of the system.
Fig.8-1 Raw data Fig.8-2 Test results of adaptive clutter map
4 SYSTEM PERFORMANCE AND
EXAMPLES
4.1 Detection probability and false
alarm probability
Detection probability
At a domestic airport, a reflector of 1 square meter
is placed in a plurality of areas of the radar
detection. After N scanning times, the number of
scanning times undetected by this reflector is
recorded. The detection probability P
d
equals the
number of scanning times undetected divided by N,
then multiply by 100%. After the design of the
surface movement radar scanning, the P
d
measured
more than 97%.
False alarm probability
After clearing the airport, the multiple areas of
the airport (confirm that there is no target in the
area) is observed. Step 1: Divide an area at the test
site to determine there are no targets in the area.
Statistics the number times N of false targets the
system detected in T seconds, then the false alarm
probability P
fa
equals divided by N, afterward
divide by area size, final multiply by 100%. After
the design of the surface movement radar scanning,
ICECTT 2018 - 3rd International Conference on Electromechanical Control Technology and Transportation
362
the P
fa
measured less than 3×10
-7
.
4.2 Field test results
Over a long period of time in a rainy day, Fig.9-1
shows the test results of conventional pulse radar
processing in a domestic airport. The red base map
shows the scene of the airport and the blue shows
the target result of the system test. The observation
shows that: 1) the contours of strong clutter
(terminal, lamp post and barbed wire) are all
detected as low-speed targets, resulting in more
false alarms; 2) the RCS of targets is small, so they
are undetected leading to leakage alarm on far away
from the runway.
Fig.9-1 Test results of conventional pulse radar system. Fig.9-2 Test results of this system after treatment
Fig.9-2 shows the detection results of the radar
system after adaptive STC gain control and adaptive
clutter detection. The red bottom is the scene of the
airport and the blue is the target of the system test.
The results show that: 1) The contour of strong
clutter (terminal, lamp post, barbed wire) is
eliminated, reducing the false alarm probability; 2)
On far away from the runway, the RCS of the
targets (aircraft and vehicle) is small but both are
detected, improving the detection probability of the
target.
5 CONCLUSIONS
Adopting adaptive STC and adaptive clutter
detection technology, it can well solve some
problems that the conventional SMR equipment has
more false alarms, lower detection probability and
lost target under the background of strong clutter in
complicated and variable weather environment.
That greatly improves the detection probability of
the target (>97%), reducing the false alarm
probability (<3×10
-7
). Through improving the
overall system performance and anti-interference, it
ultimately improves operating efficiency of the
airport. Therefore, during the process of
certification and testing of CNS equipment, the
technical solutions of manufacturers should be
focused on the design review of SMR, and the
relevant testing requirements should be formulated
to ensure that the system can meet the requirements
of civil CNS equipment
.
REFERENCES
ICAO. Chicago Convention on International Civil
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MH / T4043-2015, Technical Requirements for Civil
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Jin Wen. The Application and Development of Surface
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48-50
Shao Wei, Yang Zhi-qian. Design on Control Circuit of
Surface Movement Radar[J]. Electronic Design
Engineering, 2014(21):1-3
Sheng Jie, Yan Yong. Analysis of Clutter Suppression
Capability in Surface Movement Radar[J]. Radar
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