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PROCEEDINGS OF SPIE
Volume 8008
Proceedings of SPIE, 0277-786X, v. 8008
SPIE is an international society advancing an interdisciplinary approach to the science and application of light.
Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2011
Ryszard S. Romaniuk Editor 23–29 May 2011 Wilga, Poland Organized by Institute of Electronic Systems, Faculty of Electronics and Information Technologies, Warsaw University of Technology (Poland) Sponsored by PSP—Photonics Society of Poland (Poland) • SPIE Europe • Committee of Electronics and Telecommunications, Polish Academy of Sciences (Poland) • EuCARD—European Coordination of Accelerator R&D (EU FP7) • IEEE Poland Section • PKOpto—Polish Committee of Optoelectronics of SEP
The papers included in this volume were part of the technical conference cited on the cover and title page. Papers were selected and subject to review by the editors and conference program committee. Some conference presentations may not be available for publication. The papers published in these proceedings reflect the work and thoughts of the authors and are published herein as submitted. The publisher is not responsible for the validity of the information or for any outcomes resulting from reliance thereon. Please use the following format to cite material from this book: Author(s), "Title of Paper," in Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2011, edited by Ryszard S. Romaniuk, Proceedings of SPIE Vol. 8008 (SPIE, Bellingham, WA, 2011) Article CID Number. ISSN 0277-786X ISBN 9780819485823 Published by SPIE P.O. Box 10, Bellingham, Washington 98227-0010 USA Telephone +1 360 676 3290 (Pacific Time)· Fax +1 360 647 1445 SPIE.org Copyright © 2011, Society of Photo-Optical Instrumentation Engineers Copying of material in this book for internal or personal use, or for the internal or personal use of specific clients, beyond the fair use provisions granted by the U.S. Copyright Law is authorized by SPIE subject to payment of copying fees. The Transactional Reporting Service base fee for this volume is $18.00 per article (or portion thereof), which should be paid directly to the Copyright Clearance Center (CCC), 222 Rosewood Drive, Danvers, MA 01923. Payment may also be made electronically through CCC Online at copyright.com. Other copying for republication, resale, advertising or promotion, or any form of systematic or multiple reproduction of any material in this book is prohibited except with permission in writing from the publisher. The CCC fee code is 0277-786X/11/$18.00. Printed in the United States of America. Publication of record for individual papers is online in the SPIE Digital Library.
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8008 1T Least square spline decomposition in time-frequency analysis of weather radar signals [8008-45]
K. I. Shelevytska, O. S. Semenova, I. V. Shelevytsky, F. J. Yanovsky, National Aviation Univ. (Ukraine)
8008 1U CFAR BI detector for mariner targets in time domain for bistatic forward scattering radar
[8008-51] Chr. Kabakchiev, The St. Clement of Ohrid Sofia Univ. (Bulgaria); I. Garvanov, State Univ. of
Library Studies and Information Technologies (Bulgaria); M. Cherniakov, M. Gashinova, Univ. of Birmingham (United Kingdom); A. Kabakchiev, V. Kiovtorov, M. Vladimirova, P. Daskalov, Institute of Information and Communication Technologies (Bulgaria)
8008 1V Preliminary results of ground reflectivity measurements using noise radar [8008-52] Ł. Maślikowski, P. Krysik, Warsaw Univ. of Technology (Poland); K. Dąbrowska-Zielińska,
W. Kowalik, M. Bartold, Institute of Geodesy and Cartography (Poland) 8008 1W Application of arbitrary waveform generator for noise radar [8008-18] K. A. Lukin, O. V. Zemlyaniy, P. L. Vyplavin, V. P. Palamarchuk, Usikov Institute for
Radiophysics and Electronics (Ukraine) SESSION 9 MATERIALS FOR PHOTONICS AND ELECTRONICS, OPTICAL FIBERS 8008 1X Specialty optical fibers: revisited (Invited Paper) [8008-105] R. S. Romaniuk, Warsaw Univ. of Technology (Poland) 8008 1Y Fiber optic structures for dynamic stress sensing [8008-106] R. Plaga, P. Lesiak, T. R. Woliński, Warsaw Univ. of Technology (Poland) 8008 1Z Approaches for diagnostic and predictive maintenance [8008-40] K. P. Boshnakov, V. I. Petkov, Univ. of Chemical Technology and Metallurgy (Bulgaria);
L. A. Doukovska, D. I. Borissova, S. L. Kojnov, Institute of Information and Communication Technologies (Bulgaria)
8008 20 C-Ni films for cold cathode applied in fluorescent lamp [8008-64] I. Stępińska, E. Czerwosz, H. Wronka, M. Kozłowski, Tele and Radio Research Institute
(Poland) 8008 21 Resistance changes of carbon-palladium films obtained by PVD for sensor’s applications
[8008-89] K. Molenda, A. Kamińska, S. Krawcyzk, M. Kozłowski, E. Czerwosz, H. Wronka, Tele and Radio
Research Institute (Poland) Author Index
ix
CFAR BI Detector for Mariner Targets in Time Domain for
Bistatic Forward Scattering Radar
Chr. Kabakchiev*1, I. Garvanov**
2, M. Cherniakov***
3, M. Gashinova***
4, A. Kabakchiev****
5,
V. Kiovtorov****6, M. Vladimirova****7, P. Daskalov****8
*Faculty of Mathematics & Informatics, The St. Clement of Ohrid Sofia University, BG
** State University of Library Studies and Information Technologies, Sofia, BG
***School of Electrical, Electronic and Computer Engineering, University of Birmingham, UK ****
Institute of Information and Communication Technologies, BAS, Sofia, BG
1ckabakchiev@yahoo.com; 2igarvanov@yahoo.com; 3m.cherniakov@bham.ac.uk; 4m.s.gashinova@bham.ac.uk;
5 av_kab@abv.bg;
6 vladimir_ak@yahoo.com;
7mvladimirova@iit.bas.bg; 8panayot.daskalov@mps.bg
ABSTRACT
One original structure of the CFAR detector and parameter estimator of moving marine targets in conditions of natural
interference using Bistatic Forward Scattering Radar (FSR) are presented in this paper. The specific one dimensional
MTI CFAR processor with K/M-L batch processor and parameter estimator for a marine target with unknown size are investigated on the base of real data records that have been obtained by the team of the Birmingham University using
Forward Scattering Radar.
Keywords: Radar Detection and Estimations, CFAR processors, Forward Scattering Radar.
1. INTRODUCTION
The typical feature of Bistatic FSR systems is that the receiver and transmitter antennas are fixed and directed against
each other, and the targets move and cross the radio fence. The forward scattering effect that occurs in the Doppler
channel is that the signal-to-interference ratio (INR) drastically increases when a target is located close to the baseline
but outside of the dead zone. In FSR systems, the requirements to target automatic detection are very specific, because
the concept of a point target is inapplicable, and the duration of the package of pulses reflected from a moving target and
the pulse amplitude are unknown. They depend on various factors: target velocity, angle of crossing of a radio fence,
distance to the receiver, target dimensions.
Our investigations are based on the realistic records of marine target useful signals that have been obtained by the team
of the Birmingham University using Forward Scattering Radar in 2010 year Studies of the Birmingham University, show
and reaffirm previous such that the amplitude of maritime target signal is rather Rayleigh distributed and the amplitude
of the sea returns is Weibull distributed. The records are made in the form of signal lines presenting boats, yachts, and
sea surface with different roughness power.
We have a statistic task for detection FSR marine target with unknown speed, size and spectrum in conditions of sea
correlation clutter with unknown spectrum and power. In this situation, we propose to use the adaptive approach for
forming statistic rule for sub-optimally detection for the FSR marine target with unknown length in conditions of sea correlation clutter with unknown power [1-11]. The purpose of this approach is to construct decision rule structure with
estimates of unknown parameters for situation, when the part of parameters of statistics of two hypothesis are unknown,
for statistic H0 - unknown power, and for H1 – unknown length of target.
It is well known that, the CFAR detector with binary or non-coherent integration with fixed reference window is usually
used for detection of a point target with a known size in conditions clutter with unknown power [13-16]. But this
approach requires the independence of the samples of the marine interference.
We must estimate only the length of target. The optimal or sub-optimal signal estimation of the parameters of FS Moving Marine Targets length is based on our hypothesis that the number of detected pulses, in the pulse package received from
the target, defines the target projection of length. It is enough for forming the CFAR adaptive threshold, i.e. the length of
the tested and the reference windows.
The next our hypothesis in this situation is that using of the single channel Moving Target Indicator (MTI) with pulse
canceller to reject the marine radar clutter or reduce correlation signal process in uncorrelation process. Than the
structure of this original CFAR detector, must decorrelate signal to nose mixture and estimate the length of the target
(pulse package) and the clutter power for forming the adaptive threshold.
For that reason, in this paper we propose original structure of single channel MTI with one – dimensional CA CFAR processor with length target estimator (LTE) so call (MTI CA CFAR LTE). It uses: MTI rejector of sea clutter, using one
or two pulse canceller, a standard CA CFAR detectors with fixed length of the tested and the reference windows;
estimator of length of target, use two nonparametric tests K/M for of a beginning of plot of target and nonparametric L -
detectors of several zero for detection a finish a plot of target.
The purpose of this paper is to determine the part of parameters, number of pulse canceller, and numbers in the binary
rules for nonparametric detectors for a beginning of plot of target or a finish a plot of target of this MTI and one
dimensional CFAR BI LTE detector. These estimates are calculated on the base of realistic records that have been
obtained by the team of the Birmingham University using Forward Scattering Radar [1-7].
The paper includes the following sections: Abstract, Introduction, CFAR signal detection and estimation, Results,
Conclusion, References.
2. CFAR SIGNAL DETECTION AND ESTIMATION
In our investigation, for sub-optimally detection of the FSR marine target with unknown speed and length in conditions
of sea correlate clutter with unknown power, we use the adaptive approach for forming CA CFAR statistic rule [13, 15]. This structure is shown in the figure 1, and consists of: one channel Moving Target Indicator, Square Low Detector, Cell
Average Constant False Alarm Detector, a Binary K/M and L nonparametric detectors for a beginning or a finish a plot
of target, and estimator of the parameters of target, like length and energy.
The structure of MTI CA CFAR K/M-L processor with parameter target estimator includes: rejector of sea clutter, which
uses one or two pulse canceller; standard CA CFAR detectors, and estimator of length of target. This estimator uses
binary K/M and L nonparametric detectors for a beginning or a finish a plot of target. The adaptive CFAR processor
detects single pulses in clutter with unknown power and counts them using the decision rule “K out of M”, for estimating
of the beginning and L for estimating finish of plots of target. It indicates a beginning of plot or finish of target, when the criterion K/M and L are bigger of the thresholds.
Figure 1 Block diagram of research algorithm
2.1. Moving Target Indicator
Moving Target Indicator - is one of the oldest methods to reject the radar clutter. We propose to use the simple MTI system or no recursive basic types filter configuration. It is constructed with cascade of single 1 or 2 pulse cancellers
without feedback, i.e. transversal filter or FIR MTI with the “moving window”. We know that it is not the optimum MTI
filter, and it have the degradation improvement factor of single or dual cancellers to use. In this FSR situation, our
purpose is to decorrelated the reflected signal from sea clutter, or to minimize the correlation time.
SLD CA CFAR K/M-L
target Input
signal
MTI
no target
Parameter
estimation
2.2. CA CFAR detector
The standard one dimensional CA CFAR processor has been realized using constant false alarm rate detection on the
signal envelope. It has a fixed length of the tested and the reference windows. The sample from the test resolution cell x0 is compared with adaptive detection threshold HD=VT. The detection is declared if the sample x0 exceeds the detection
threshold, see a fig. 2. It well know that, the CFAR detector with binary or non-coherent integration with fixed reference
window is usually used for detection of a point target with a known size in conditions clutter with unknown power [13-
16].
Figure 2 Block diagram of a Cell Average Constant False Alarm Detector
2.3. K/M-L algorithm
This is a batch detector, or a non parametric detection of the package of binary signals with unknown length. The criteria for fix of the beginning package is simultaneity the criteria of the detection, in this batch detector. For fix of the centre of
plot of target it uses other non parametric test for the finish of plot of target. When the target size is unknown, ordinary
for the automatic detection of the binary pulses is used the approach for batch detection for the estimate of the beginning
and finish of plot of target, and after that is estimated the size of plot. It use two nonparametric tests K/M for of a
beginning of plot of target and nonparametric L - detectors of several zero for detection a finish a plot of target. Our aim
is to use this approach for estimation of the unknown length of the pulse package of longer targets.
3. RESULTS
In this paper two moving targets are of interest, namely, small boat and yacht. Target detection is obtained through the
principle of Forlard Scattering Radar.
3.1. Clutter decorrelation
Sea induces clutter into the receiver, which are correlated. To remove the correlation of the disturbances we apply Moving Target Indicator algorithm. We studied one and two pulse canceller MTI algorithms. This work shows only
results for small target. On the figures 3 - 11 are shows the results of: the envelope of a signal; spectrum of a signal and
interference and correlation coefficient of a clutter.
Figures show that the signal envelope has a high correlation. Spectrums of the target and clutter are characterized by low
frequency peaks. After applying the MTI clutter power decreases and the signal to noise ratio increases. Implementation
of MTI two-time further reduced the correlation, but the improvement is not as great. From the results we make decision
to use one-period MTI in subsequent studies.
Square Law
Detector
x1 … xN/2 x0 xN/2+1 … xN
T
0
1
NxV
N
i
i∑=
=
1
0 10 20 30 40 50 600
0.5
1
1.5Envelope of a signal
Time / s
Re
ce
ive
r O
utp
ut
/ V
0 50 100 150 200 250
-100
-90
-80
-70
-60
-50
-40
-30
-20
-10
0
Frequency (Hz)
Pow
er(d
B)
Power spectral density of the signal
Clutter
Target + Clutter
-1000 -800 -600 -400 -200 0 200 400 600 800 1000
-0.5
0
0.5
1
co
rre
latio
n c
oeff
icie
nt
Fig. 3 Envelope of a signal Fig. 4 Signal spectrum Fig. 5 Correlation coefficient of a clutter
0 0.5 1 1.5 2 2.5
x 104
0
0.01
0.02
0.03
0.04
0.05
0.06Envelope
Time / s
yi=
xi-x
i-1 /
V
0 50 100 150 200 250
-110
-100
-90
-80
-70
-60
-50
-40
-30
Frequency (Hz)
Po
wer(
dB
)Power spectral density of the signal
Clutter
Target + Clutter
-1000 -800 -600 -400 -200 0 200 400 600 800 1000
-0.2
0
0.2
0.4
0.6
0.8
1
1.2
co
rre
latio
n c
oeff
icie
nt
Fig. 6 Envelope of a signal, after MTI
processing -1 pulse canceller Fig. 7 Signal spectrum after MTI
processing - 1 pulse canceller Fig. 8 Correlation coefficient of a clutter
after MTI processing
0 0.5 1 1.5 2 2.5
x 104
0
0.005
0.01
0.015
0.02
0.025
0.03
0.035
0.04Envelope
Time / s
yi=
xi-2
xi-
1+
xi-
2 /
V
0 50 100 150 200 250
-120
-110
-100
-90
-80
-70
-60
-50
-40
Frequency (Hz)
Po
we
r(d
B)
Power spectral density of the signal
Clutter
Target + Clutter
-1000 -800 -600 -400 -200 0 200 400 600 800 1000
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
co
rre
latio
n c
oeff
icie
nt
Fig. 9 Envelope of a signal, after MTI processing - 2 pulses canceller
Fig. 10 Signal spectrum after MTI processing - 2 pulses canceller
Fig. 11 Correlation coefficient of a clutter after MTI processing
3.2. CFAR processing
After one-period MTI we applied CA CFAR signal processing. CA CFAR detector is used to detect single pulse. The
specificity of the received signal leads us to choose the parameters of the detector as follow: the number of reference
cells is 600, the distance between the test cell and the reference window is 1250 cells (on both sides of the test cell).
After the CA CFAR processing K/M-L algorithm is applied to detect a package pulses with unknown length. The results
after MTI, CA CFAR and K/M-L processing for small target are shown in the figure 12. The results are obtained for K =
40, M = 50, L = 20.
0 5 10 15 20 25 30 35 40 45 500
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0.16
0.18
Time / s
CFAR detection
Signal Envelope /10
Detection Threshold
MTI Signal
CA CFAR output/10
K/M-L CFAR output/10
21 22 23 24 25 26 27
0
0.05
0.1
0.15
Time / s
CFAR detection
Signal Envelope /10
Detection Threshold
MTI Signal
CA CFAR output/10
K/M-L CFAR output/10
Fig. 12 Results from CFAR signal processing of а small target
Table 1 shows estimates of the size of the detected package and average signal energy which surpasses the threshold of
the CA CFAR detector for a small target.
Table 1. Parameter estimation for small target
K 45 40 50 80 90 90 195 295
M 50 50 100 100 100 100 200 300
L 20 80 80 50 50 30 10 10
Target cells 787 872 912 881 869 789 660 360
Target energy / V 0.0171 0.0151 0.0139 0.0149 0.0152 0.0171 0.0190 0.0225
Table 1 shows that increasing K and/ or decreasing of L lead to detect a package with a shorter length. If K is reduced and/ or L increases the detected package is with great length. As the package is small, so the average energy of signals
surpasses the threshold of detection is greater.
On figure 13 are shown the results after MTI, CA CFAR and K/M-L processing for large target. The results are obtained
for K = 80, M = 100, L = 50.
0 5 10 15 20 25 30 35 40 45 500
2
4
6
8
10
12
Time / s
CFAR detection
Signal Envelope
Detection Threshold
MTI Signal
CA CFAR output * 4
K/M-L CFAR output * 5
15 16 17 18 19 20 21 22 23 24
0
2
4
6
8
10
Time / s
CFAR detection
Signal Envelope
Detection Threshold
MTI Signal
CA CFAR output * 4
K/M-L CFAR output * 5
Fig. 13 Results from CFAR signal processing of а large target
Table 2 shows estimates of the size of the detected package and average signal energy which surpasses the threshold of
the CA CFAR detector for a large target.
Table 2. Parameter estimation for large target
K 40 50 80 90 150 190 250 290 400
M 50 100 100 100 200 200 300 300 500
L 80 80 80 80 80 80 80 80 80
Target cells 1881 1932 1902 1881 1927 1868 1915 657 834
Target energy / V 0.2455 0.2298 0.2422 0.2455 2318 0.2474 0.2374 0.3681 0.2954
By obtained results it can be concluded that the good work of K/M-L algorithm for large and small targets is convenient
to use values of K = 40, M = 50, L = 80. In this case, we get relatively good values for the signal energy and the size of
the target package.
4. CONCLUSION
We are constructed and investigated sub-optimally CA CFAR statistic rule for detection of the FSR marine target with
unknown speed and length in conditions of correlated sea clutter with unknown power.
This adaptive detection structure contain: one channel Moving Target Indicator, Square Low Detector, Cell Average
Constant False Alarm Detector, a Binary K/M and L nonparametric detectors for of a beginning or a finish a plot of
target, and estimator of the parameters of target, like length and energy;
The part of parameters of the CFAR FSR detector and parameters of the short and long marine targets are determined, on
the base of real data records that have been obtained by the team of the Birmingham University;
The tuned parameters of the detection structure are as follow: the length of the tested and the reference windows are: one
cells - for tested, and quarter from the length of the biggest target (400 cells) – for reference, the distance between windows - the length of the longest target (2000 cells); a binary K/M and L for estimate of a beginning or a finish a plot
of target - K/M= 40/50 and L= 80;
The determined parameters of the short and long targets are: for short target: the length 870 – 880 cells, and energy
about 0.018 V; for long target: the length 1880-1900 cells, and energy about 0.24 V.
5. ACKNOLEDGMENT
This work is partially supported by the Bulgarian Science Fund SISER, FP7–REGPOD–2007–1, DTK02/28/2009, MU-
FS-05/2007, DDVU02/50/2010, BG051PO001-3.3.04/40, DO-О2-344/2008, and NIP-2011-07/2011.
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