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.

REFERENCES

[1] Antoniou, M, Sizov, V, Cheng, H, Jancovic, P, Abdullah, R, Rashid, N, Cherniakov, M, “The Concept of a Forward Scattering Micro-Sensors Radar Network for Situational Awareness”, Radar 2008, Adelaide, 2008.

[2] M. Cherniakov, Cheng Hu, M. Gashinova, (2007) “Sea clutter characterization in UWB FSR”, in Proc. of

International Conference Antennas, Radar and Wave Propagation (IASTED), Montreal, Canada, 2007, May, pp.

143 – 147.

[3] Sizov, V, Cherniakov, M, Antoniou, M, “Forward scatter RCS Estimation for Ground Targets”, Proceedings of

the 4th European Radar Conference, Munich, Oct 2007.

[4] Cherniakov, M, Gashinova, M, Cheng, H, Antoniou, M, Sizov, V, Daniel, L.Y, “Ultra wideband forward

scattering radar: Concept and prospective”, Radar 2007, Edinburgh, 2007. [5] Sizov, V, Cherniakov, M, Antoniou, M, “Forward Scattering Radar Power Budget Analysis for Ground Targets”,

IET Proc. In Radar, Sonar and Navigation.

[6] Daniel, L.Y, Gashinova, M, Cherniakov, M, “Maritime UWB Forward Scattering Radar Network: Initial Study”,

RADAR 2008, Adelaide.

[7] Daniel, L.Y, Gashinova, M, Cherniakov, M, “Maritime Target Cross Section Estimation for an Ultra-Wideband

Forward Scatter Radar Network”, Department of Electrical, Electronic and Computer Engineering, University of Birmingham, UK, EuRAD conference, Amsterdam, 2008.

[8] Cheng, H, Antoniou, M, Cherniakov, M, Sizov, V, “Quasi-Optimal Signal Processing in Ground Forward

Scattering Radar”, Radar Con, Rome, 2008.

[9] Rashid, N, Antoniou, M, Jancovic, P, Sizov, V, Abdullah, R, Cherniakov, M, “Automatic Target Classification

in a Low Frequency FSR Network”, 11th European Microwave week, Amsterdam, 2008.

[10] Cherniakov, M, Cheng, H, Gashinova, M, “UWB FSR for air targets detection: preliminary analysis”,

Proceedings of the 4th European radar conference, location Munich, 2007.

[11] Hansen,P. Scheff, “Measurement of Ocean Forward Scatter with an Ultrawideband Radar”, 1999. [12] Gaspare Galati edit., Advanced radar techniques and systems, IEE Radar, Sonar, Navigation and Avionics

Series 4, Peter Peregrinus Ltd., 1993.

[13] Garvanov, I., V. Behar, Chr. Kabakchiev, “CFAR Processors in Pulse Jamming”, 5th International Conference,

"Numerical Methods and Applications – NM@A-02”, Springer-Verlag Berlin Heidelberg, Lecture Notes in

Computer Science, LNCS 2542, (ISBN 978-3-540-00608-4), pp. 291-298, 2003.

[14] Garvanov, I., “CFAR BI Detector in Binomial Distribution Pulse Jamming”, Comptes Rendus de l’Academie

Bulgare des Sciences, (ISSN: 0861-1459), vol. 56, №10, pp. 37-44, 2003.

[15] Garvanov, I., Chr. Kabakchiev, “One and Two Dimensions CFAR Processors in the Presence of Strong Pulse Jamming”, Cybernetics and Information Technologies, (ISSN 1311-9702), Volume 2, № 1, pp. 58-72, 2002.

[16] Garvanov, I., Chr. Kabakchiev, “Sensitivity of CFAR Processors Toward the Change of Input Distribution of

Pulse Jamming”, Proc. of IEEE - International Conference on Radar “Radar 2003”, ISBN 0-78037871-7,

Adelaide, Australia, pp. 121-126, 2003. CPCI № 8576