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INVESTIGATION INTO THE LIMITATIONS AND EFFECT OF PARAMETERS OF

GSC ON RADAR ARRAY PERFORMANCE

Wu Weiming¹, Edrea Tan Yi Lin¹, Yeoh Wee Soon²

¹Raffles Girls’ School, 20 Anderson Road, Singapore 259978

² DSO National Laboratories, 20 Science Park Drive, Singapore 118230

ABSTRACT

The performance of radar systems can be greatly hindered with the presence of radar

interference. A well­established electronic counter­countermeasure (ECCM) technique is

the sidelobe canceller approach. Modelled in MATLAB, the adaptive array processing

algorithm used in this study is the Generalized Sidelobe Canceller (GSC), which optimally

estimates the parameters for combining data from an array of sensors to improve the target

signal­to­jamming ratio (SJR). This study experiments on the limitations and ability of the

radar system when faced with different external factors, namely jammer power and angle of

jammer attack. As an extension, an internal factor is also studied, namely the spacing

between the array sensors, so as to observe how the performance of a radar system can be

improved and optimized where possible. Results are quantified in terms of the SJR of

output signal before and after the introduction of GSC and through the null­to­null

beamwidth of the array. The results of this study show that the application of GSC is an

effective ECCM technique that can be used even with substantial change in external factors. It

is also discovered that λ/2 is the ideal parameter for spacing between array elements for this

particular array.

INTRODUCTION

Radar has been employed prominently and extensively in the field of defence. Through

the transmission and receiving of radio signals in the form of electromagnetic waves, the

presence and type of objects can be detected with the use of radar [Villiard, O.G., Jr., 1976].

However, the performance of radar systems can be limited by noise and other sources of

interference. Radar jamming and deception, also known as electronic countermeasure

(ECM),

hinder its performance by saturating the receiver with noise or false information [Corcoran,

A, 2009].

To minimise the amount of interference that a jammer can introduce to a radar receiver,

electronic counter­countermeasure is utilized. The application of an ECCM, such as a

general sidelobe canceller, is a technique used to reduce the effect of jammers received

through the sidelobe of a radar system. It is essentially an adaptive array capable of

automatically sensing and reducing, or even eliminating unwanted signals entering the radar’s

field of view, in particular its sidelobes, while still enhancing reception of the desired target

returns. By using the signals received through additional auxiliary antennas, the radar system is

able to cancel incoming interfering signals, hence displaying only the desired target signal

[Budge, 2007].

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Diagram 1. An illustration of Generalized Sidelobe Canceller.

Diagram 1 illustrates the GSC system used for this study. The setup of such a radar

system consists of external aerials (auxiliary antennas), placed near the main antenna (main

channel) [Bucciarelli, 1984]. The main antenna is pointed towards the desired signal

angular location while the interfering signals can often be detected somewhere in the

sidelobes. This configuration means that the main antenna would receive returns from both

the desired and interfering signals [Taylor and Francis Group, 2009]. However, as jamming

power is generally

much stronger than the target signal, the auxiliary antenna returns are primarily from

the interfering signal.

The signals received through the auxiliary array antennas are multiplied by proper weights

and then summed obtaining an estimate of the jammer signal received through the radar

sidelobes. The jammer estimate is then subtracted from the radar output. With the feedback

circuit, the weights can be obtained through the evaluation of the correlation coefficients

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between each auxiliary signal and the residue of cancellation [Skolnik M., 1981].

With the use of GSC as an ECCM technique, it is certain that there are limitations and

also parameters that can be altered so as to facilitate a better array performance. Hence, this

study aims to obtain a better understanding of the limitations and effectiveness of such a

technique with varying parameters of the jammer. A second portion of the research also aims to

investigate how the accuracy and efficiency of adaptive array processing can be improved

by adjusting relevant parameters of the radar’s internal system to a more optimal state to

improve the radar system’s performance.

MATERIALS AND METHODS

The codes used for this study is run on a Matrix Laboratory (MATLAB) simulator, Octave

3.8.0 to derive the results and graphs and the text editor “sublime text” is utilized. A simulation

of the elements of a radar system, including main and auxiliary arrays, as well as target and

jammer signals, is carried out.

Three variables were tested separately so as to see how each of them affected the behaviour

and effectiveness of the radar system. The variables of each tests are stated as follows:

● Test 1: Changing the jamming power via jamming­to­signal ratio (JSR)

● Test 2: Changing the angle of attack of the jammer (j_aoa)

● Test 3: Changing the spacing between array sensor elements (d)

Two performance metrics are used to qualify the simulation results, and they are elaborated

as follows. The ability to suppress interference signals determines a radar system’s

signal­to­jammer ratio, which compares the level of desired signal against the level of

interference signal at the array output. SJR of the output signal leaving the radar system is

one such measurement employed to determine the effectiveness of radar interference

reduction and suppression techniques. Such unwanted interference can enter a radar system

through its antenna and hamper the signal processing of the radar’s signal processor

[Douglas A., 2003]. The formula is presented as follows in decibels [Fourikis, 1996]:

( 1 )

Null­to­null beamwidth is also used to measure the angular width of the main beam. A

small null­to­null beamwidth is desirable as it is an indication that more power is radiated at

the angle of arrival of the target instead of being distributed at the sidelobes. The following

equation is utilized in this study [Toomay J., 2004]:

θnn = 115λ

D

degrees ( 2 )

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Where

θnn = antenna null­to­null beamwidth for

a uniform current distribution,

radian or degrees,

λ = wavelength in meters,

D = length of the array in meters.

In the simulations, the default setting of values are adjusted such that j_aoa= 0°, JSR = 50

dB and d=lambda/2 (i.e., λ/2), and rectangular windowing is employed. Number of

targets=1 is

standard for all tests. The number of elements in the main channel is set at Nm=16, while

the number of elements in the auxiliary array is set at Na=4. Lastly, the angle of arrival of the

target at t_aoa=20°. The following tables provide a clearer picture of the variations in

parameters used in the respective tests.

Table 1.1: Variables in Test 1

Test 1.1 Test 1.2 Test 1.3 Test 1.4 Test 1.5

j_aoa (°) 0

JSR (dB) 0 10 20 30 50

Spacing

between array

sensors (d)

lambda/2

Table 2.1: Variables in Test 2

Test 2.1.1 Test 2.1.2 Test 2.1.3 Test 2.1.4 Test 2.1.5

j_aoa (°) ­80 ­40 0 40 80

JSR (dB) 50

Spacing

between array

sensors (d)

lambda/2

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Table 3.1: Variables in Test 3

Test 3.1.1 Test 3.1.2 Test 3.1.3 Test 3.1.4 Test 3.1.5

j_aoa (°) 0

JSR (dB) 50

Spacing

between array

sensors (d)

lambda/8 lambda/4 lambda/2 lambda 2*lambda

RESULTS

Each test produces results that are presented into three figures covering different aspects so

that more alternatives are available when analyzing the results. The figures of all the tests

can be found attached in the Appendix. A brief description of each figure can be found as

follows:

Figure 1: Main array response in decibels against the angle of arrival of the target in degrees.

Figure 2: Response of the array over time with the presence of a jammer and radar noise under

different settings, “noisy”, as well as in the absence of it, labelled “noiseless”.

Figure 3: Comparison of noiseless array output against the final array output.

The results of Test 1 and 2 would be quantified by SJR output before and after the application

of the GSC so as to give a clear indication of the limitations and effectiveness of the GSC

under different parameters. Test 3 would employ the use of final SJR as well as null­to­null

beamwidth to study the change in array response caused by a change in spacing between

array sensor elements.

Test 1: Changing the jamming power via the jammer­to­signal ratio, JSR (dB)

The JSR of the jammer is increased from 0 dB to 50 dB and the SJR output before and after

the application of the GSC are calculated respectively. The results are recorded as follows in

Table 1.2.

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Table 1.2: Calculations from Test 1 done on Matlab Simulator 3.8.0

JSR (dB) 0 10 20 30 50

SJR output

without GSC

(dB)

11.974 8.709 0.657 ­9.113 ­29.097

SJR output

after GSC

(dB)

11.475 11.544 11.578 11.589 11.594

Test 2: Changing the angle of attack of the jammer, j_aoa (°).

The angle of attack of the jammer is changed by intervals of 40° from ­80° to 80° and the same

calculations are made for the SJR outputs. The results are recorded as follows in Table 2.2.

Table 2.2: Calculations from Test 2 done on Matlab Simulator 3.8.0

J_aoa (°) ­80 ­40 0 40 80

SJR output

without GSC

(dB)

­26.761 ­17.032 ­29.097 ­32.683 ­19.848

SJR output

after GSC

(dB)

11.562 11.558 11.594 11.217 11.620

Test 3: Changing the spacing between the array sensors (d)

The final SJR output and null­to­null beamwidth is calculated each time the distance of

array sensor elements is doubled in intervals from d=lambda/8 to d=2*lambda. The results

are recorded as follows in Table 3.2.

Table 3.2: Calculations from Test 3 done on Matlab Simulator 3.8.0

d (m) lambda/8 lambda/4 lambda/2 lambda 2*lambda

SJR output

after GSC

(dB)

9.5601 10.884 11.594 11.370 11.127

Null­to­Null

beamwidth

(°)

59.08 33.79 16.72 8.30 4.21

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DISCUSSION AND CONCLUSION

For Tests 1 and 2, by studying the change in the quality of the signals before and after

the application of the GSC, links can be drawn between the performance of the array

and the sidelobe canceller, as shown through qualitative and quantitative analysis.

In Test 1 with reference to Figure 2, there is a trend in the absence of the GSC whereby

the “noisy” signal received by the array becomes significantly stronger as the JSR ratio

increases to the point whereby the SJR output becomes negative when JSR is set to a value

larger than 20 dB. The jamming signal has overpowered the target signal and rendered the

signal received unusable. However, after the implementation of GSC, it can be seen from

Figure 3 that the final output of the radar systems met with different jamming powers

seemed similar and comparable to one another. Through the calculation of the final SJR

output, it is discovered that the test with the highest initial JSR of 50 dB unexpectedly had

the highest SJR output by a small margin. Even when met with high jamming power, the

performance of the radar system is not compromised, giving a positive indication that the

GSC is indeed capable of effectively cancelling strong jammer signals and retaining the

quality of the desired target signal.

In Test 2, it is observed that in Figure 2, the “noisy” signal received by the radar

becomes gradually stronger when the angle of attack of the jammer approaches the angle of

arrival of the target at 20°. This is met with the sole exception of the test whereby the “noisy”

signal increased significantly with the change in location from ­40° to ­80°. Upon closer study

of Figure 1, it is possible that the anomaly is due to the difference in the array response of

the sidelobes. Examining the final SJR output with reference to table 2.2, the quantitative

results also confirm the observations made that radar performance is slightly poorer when

the jammer is located closer to the target. Although there is a slight but definite correlation

between the angle of attack of the jammer and the ability of the GSC to reduce the interference

signal, the GSC is extremely successful in reducing the jammer signal regardless of the wide

range of the angles of attack. This is evident from the similar final SJR output of all the

tests, whereby there is only a slight difference of 0.403 dB between the highest and lowest SJR

output.

With reference to Table 3.2 for Test 3, it is observed that an increase of spacing between

array elements (d) from lambda/8 to lambda/2 yields a remarkable increase in the SJR of the

output signal from 9.5601 dB to 11.594 dB when GSC is implemented. A further increase

in d to 2*lambda causes the final SJR output to decrease slightly from 11.594 dB to 11.127 dB.

Aside from SJR output, other factors are put into consideration when analyzing and

evaluating radar performance with the change of array spacing. Referring to Figure 1, it is

observable that as d increases from lambda/8 to 2*lambda, the null­to­null beamwidth

decreases significantly from

59.08° to 4.21°, which is an advantageous effect. However, it is also seen that more than

one mainlobe appears at various steering angles when the value of d exceeds lambda/2. Due

to the presence of undesirable multiple main lobes, the angle of arrival of the target signal

would be unknown. Putting these factors into account, it is hence evident that lambda/2 is the

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best spacing distance for main array sensor elements due to its high SJR output, small

null­to­null beamwidth and presence of only one main lobe.

Through the results from the first two tests, it is evident that the the GSC is able to

effectively maintain a similar final SJR output, even with a wide range of varying jammer

parameters. Test 3 demonstrated how the change in the spacing of array sensors affects overall

radar performance and hence can be employed to effectively reduce the effects of a jammer and

complement the use of a particular array. Through this study, a better understanding of the

abilities of the GSC has been gained and it is concluded that the GSC is an excellent SLC

technique that can be employed so as to facilitate satisfactory array performance with the

presence of jammers.

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ACKNOWLEDGEMENTS

Our embarkment and completion of this DSO project could not be possible without the

guidance and help received from many individuals and organisations. We would like to

express our gratitude to everyone who has helped us through the way through this exciting

project.

First of all, we would like to sincerely give our thanks to our mentor, Dr Yeoh Wee Soon,

who has supported us through the year. Under his supervision, we were able to have a much

better and in depth understanding of our research topic, which would not be possible if not for

his kind guidance.

We would also like to extend our gratitude towards DSO National Laboratories for the

provision of resources which helped our project greatly, and also to the staff who have kindly

ensured that we were able to make good progress on this research study.

Last but not least, we would also like to thank our teacher­in­charge, Mr Shaun De Souza,

for giving us the opportunity to participate in this project and allow us to expand our learning

out of the school curriculum.

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REFERENCES

[1] Skolnik M. 1981. Introduction to Radar Systems, Second Edition. Cerra, F. j. (ed.)

McGraw­Hill Book Company, U.S.

[2] Fourikis, N. 1996. Phased Array­Based Systems and Applications. In K. Chang (Ed.), Wiley

series in microwave and optical engineering. John Wiley & Sons, Inc.

[3] Budge, M. 2007. ST: Radar Waveform and Signal Processing. Sidelobe cancellation.

[4] Federation of American Scientists Military Analysis Network 1998. AN/PPS­5B Ground

Surveillance Radar Set.

[5] Villiard, O.G., Jr. 1976. The Ionospheric Sounder and Its Place in the History of Radio

Science.

[6] Bucciarelli, T. 1984. The Gram­Schmidt Sidelobe Canceller.

[7] Merv, B. 2011. Radar waveforms and signal processing. Retrieved from

http://www.ece.uah.edu/courses/material/EE710­Merv/.

[8] Taylor and Francis Group. 2009. Adaptive Array Processing.

[9] Douglas, A. G. 2003. Radar Signal Processing and its Applications.

[10] Toomay, J. 2004. Radar Principles for the Non­specialist. Cavanaugh Editorial Services

(Ed.), SciTech Publishing Inc., U.S.

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APPENDIX

Test 1 (variable: change in jamming power via JSR)

Test 1: figure 1

Figure 1: The main array response remains the same with change in jamming power via JSR.

Test 1: figure 2

Figure 2 (Test 1.1: JSR = 0)

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Figure 2 (Test 1.2: JSR = 10)

Figure 2 (Test 1.3: JSR=20)

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Figure 2 (Test 1.4: JSR=30)

Figure 2 (Test 1.5: JSR 50)

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Test 1: figure 3

Figure 3 (Test 1.1: JSR = 0)

Figure 3 (Test 1.2: JSR = 10)

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Figure 3 (Test 1.3: JSR=20)

Figure 3 (Test 1.4: JSR=30)

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Figure 3 (Test 1.5: JSR 50)

Test 2 (variable: change in jammer angle of attack)

Test 2: figure 1

Figure 1: The main array response remains the same with change in jammer angle of attack.

Test 2: figure 2

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Figure 2 (Test 2.1: j_aoa = ­80 degrees)

Figure 2 (Test 2.2: j_aoa = ­40 degrees)

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Figure 2 (Test 2.3: j_aoa = 0 degrees)

Figure 2 (Test 2.4: j_aoa = 40 degrees)

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Figure 2 (Test 2.5: j_aoa = 80 degrees)

Test 2: figure 3

Figure 3 (Test 2.1: j_aoa = ­80 degrees)

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Figure 3 (Test 2.2: j_aoa = ­40 degrees)

Figure 3 (Test 2.3: j_aoa = 0 degrees)

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Figure 3 (Test 2.4: j_aoa = 40 degrees)

Figure 3 (Test 2.5: j_aoa = 80 degrees)

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Test 3 (variable: spacing between array sensors (d))

Test 3: figure 1

Figure 1 (Test 3.1: d = lambda/8)

Figure 1 (Test 3.2: d = lambda/4)

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Figure 1 (Test 3.3: d = lambda/2)

Figure 1 (Test 3.4: d = lambda)

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Figure 1 (Test 3.5: d = 2*lambda)

Test 3: figure 2

Figure 2 (Test 3.1: d = lambda/8)

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Figure 2 (Test 3.2: d = lambda/4)

Figure 2 (Test 3.3: d = lambda/2)

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Figure 2 (Test 3.4: d = lambda)

Figure 2 (Test 3.5: d = 2*lambda)

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Test 3: figure 3

Figure 3 (Test 3.1: d = lambda/8)

Figure 3 (Test 3.2: d = lambda/4)

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Figure 3 (Test 3.3: d = lambda/2)

Figure 3 (Test 3.4: d = lambda)

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Figure 3 (Test 3.5: d = 2*lambda)