radar phased array, beam pattern, interference direction, sidelobe cancellation, aperture size


Background. For radar systems, the beam pattern of a uniform linear array (ULA) is synthesized to ensure signal selectivity by direction. A specific ULA sidelobe is cancelled by rescaling the beam weights. In particular, this is done by increasing the number of sensors and shortening the scanning step. However, a noticeable limitation is a loss of the transmitted power. Therefore, the problem is to optimally balance the number of sensors versus effective ULA sidelobe cancellation.

Objective. In order to ensure multiple direction interference suppression, the goal is to find an optimal number of ULA radar sensors for the beam pattern synthesis. The criterion is to determine such a minimum of these sensors at which mainlobes towards useful signal directions are evened as much as possible.

Methods. To achieve the said goal, the ULA sidelobe cancellation is simulated. The simulation is configured and carried out by using MATLAB® R2020b Phased Array System ToolboxTM functions based on an algorithm of the sidelobe cancellation.

Results. By increasing the number of ULA sensors, the beam pattern lobes are not only thinned but also change in their power. In particular, the interference direction sidelobes become relatively stronger. The number of sensors is limited by the three influencing factors: the thinned-array curse transmitted power loss, the aperture size, and the sidelobes intensification.

Conclusions. An optimal number of ULA radar sensors for the beam pattern synthesis can be found when the scanning step is equal to the least distance between adjacent interference directions. At the start, the number of sensors is set at the number of useful signal directions. If the mainlobes towards useful signal directions are not evened enough, the set of interference directions is corrected.

Keywords: radar phased array; beam pattern; interference direction; sidelobe cancellation; aperture size.


R. Sturdivant, C. Quan, and E. Chang, Systems Engineering of Phased Arrays, Norwood, Massachusetts, USA: Artech House, 2018.

H. J. Visser, Array and Phased Array Antenna Basics, Hoboken, New Jersey, USA: John Wiley & Sons, 2006.

T. A. Milligan, Modern Antenna Design, 2nd ed. Hoboken, New Jersey, USA: John Wiley & Sons, 2005.

W. L. Stutzman and G. A. Thiele, Antenna Theory and Design, 3rd ed. Hoboken, New Jersey, USA: John Wiley & Sons, 2012.

H. Asplund et al., “Chapter 4 — Antenna Arrays and Classical Beamforming,” in Advanced Antenna Systems for 5G Network Deployments: Bridging the Gap Between Theory and Practice, P. von Butovitsch, Ed. Cambridge, Massachusetts, USA: Academic Press, 2020, pp. 89 — 132.

N. Fourikis, “Chapter 2 — From Array Theory to Shared Aperture Arrays,” in Advanced Array Systems, Applications and RF Technologies: A volume in Signal Processing and its Applications, N. Fourikis, Ed. Cambridge, Massachusetts, USA: Academic Press, 2020, pp. 111 — 217.

M. Skolnik, Introduction to Radar Systems, 3rd ed. New York City, New York, USA: McGraw-Hill, 2001.

M. N. Almarshad, M. Barkat, and S. A. Alshebeili,

“A Monte Carlo simulation for two novel automatic censoring techniques of radar interfering targets in

log-normal clutter,” Signal Processing, vol. 88, iss. 3, pp. 719 — 732, 2008.

W. E. Kock, Radar, Sonar, and Holography: An Introduction, Cambridge, Massachusetts, USA: Academic Press, 1973.

R. Gui, Z. Zheng, and W.-Q. Wang, “Cognitive FDA radar transmit power allocation for target tracking in spectrally dense scenario,” Signal Processing, vol. 183, 108006, 2021.

M.-M. Tamaddondar, H. Keshavarz, and J. Ahmadi-shokouh, “Beamsteering for non-uniform weighted array-fed reflector antenna,” Wireless Personal Communications, vol. 97, pp. 5511 — 5525, 2017.

S. J. Orfanidis, Electromagnetic Waves and Antennas, Piscataway, New Jersey, USA: Rutgers University, 2016.

M. Gustafsson, C. Sohl, and G. Kristensson, “Physical limitations on antennas of arbitrary shape,” Proceedings of The Royal Society A: Mathematical Physical and Engineering Sciences, vol. 463, pp. 2589 — 2607, 2007.

V. V. Romanuke, “Computational method of building orthogonal binary functions bases for multichannel communication systems with code channels division,” Mathematical Modeling and Computational Methods, Ternopil, Ukraine: Ternopil State Technical University, 2006.

W.-Q. Wang and H. Shao, “Radar-to-radar interference suppression for distributed radar sensor networks,” Remote Sensing, vol. 6, iss. 1, pp. 740 — 755, 2014.

K. N. Le, “A review of selection combining receivers over correlated Rician fading,” Digital Signal Processing, vol. 88, pp. 1 — 22, 2019.

A. A. Mulla and P. N. Vasambekar, “Overview on

the development and applications of antenna control systems,” Annual Reviews in Control, vol. 41,

pp. 47 — 57, 2016.

A. Oxley, “Chapter 4 — Signals From Satellites to Receiver — GPS,” in Uncertainties in GPS Positioning, A. Oxley, Ed. Cambridge, Massachusetts, USA: Academic Press, pp. 61 — 70, 2017.

A. Oxley, “Chapter 11 — Improving Accuracy With GPS Augmentation,” in Uncertainties in GPS Positioning, A. Oxley, Ed. Cambridge, Massachusetts, USA: Academic Press, pp. 129 — 134, 2017.

A. Sleiman and A. Manikas, “The impact of sensor positioning on the array manifold,” IEEE Transactions on Antennas and Propagation, vol. 51, no. 9, pp. 2227 — 2237, 2003.

G. Efstathopoulos, G. Elissaios and A. Manikas, “The effect of uncertainties on the performance of array systems,” in 2007 IEEE 18th International Symposium on Personal, Indoor and Mobile Radio Communications, Athens, Greece, 2007, pp. 1 — 5.

E. Dahlman, S. Parkvall, and J. Sköld, “Power

Control, Scheduling, and Interference Handling,”

in 4G: LTE/LTE-Advanced for Mobile Broadband, E. Dahlman, S. Parkvall, J. Sköld, Eds. Cambridge, Massachusetts, USA: Academic Press, 2011,

pp. 265 — 299.

L. Borowska, G. Zhang and D. S. Zrnic, “Spectral processing for step scanning phased-array radars,” IEEE Transactions on Geoscience and Remote Sensing, vol. 54, no. 8, pp. 4534 — 4543, 2016.

P. Fritsche and B. Wagner, “Evaluation of a novel radar based scanning method,” Journal of Sensors, vol. 2016, Article ID 6952075, 2016.

V. V. Romanuke, “Equidistant phase commutation by an algorithm based on a system of noncyclic binary elements using four of eight active phases,” Herald of Technological University of Podillya. Technical sciences, no. 5, pp. 169 — 174, 2004.

S. Alland, W. Stark, M. Ali, and M. Hegde, “Interference in automotive radar systems: characteristics, mitigation techniques, and current and future research,” IEEE Signal Processing Magazine, vol. 36, no. 5, pp. 45 — 59, 2019.

G. Hakobyan, K. Armanious, and B. Yang, “Interference-aware cognitive radar: a remedy to the automotive interference problem,” IEEE Transactions on Aerospace and Electronic Systems, vol. 56, no. 3, pp. 2326 — 2339, 2020.

V. V. Romanuke, “Interval uncertainty reduction via division-by-2 dichotomization based on expert estimations for short-termed observations,” Journal of Uncertain Systems, vol. 12, no. 1, pp. 3 — 21, 2018.

V. V. Romanuke, “A minimax approach to mapping partial interval uncertainties into point estimates,” Journal of Mathematics and Applications, vol. 42, pp. 147 — 185, 2019.

W. Huang and R. Lin, “Efficient design of doppler sensitive long discrete-phase periodic sequence sets for automotive radars,” in 2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM), Hangzhou, China, 2020, pp. 1 — 5.

C. Aydogdu et al., “Radar interference mitigation for automated driving: exploring proactive strategies,” IEEE Signal Processing Magazine, vol. 37, no. 4, pp. 72 — 84, 2020.

S. Torres and D. Warde, “Ground clutter mitigation for weather radars using the autocorrelation spectral density,” Journal of Atmospheric and Oceanic Technology, vol. 31, no. 10, pp. 2049 — 2066, 2014.

R. J. Doviak and D. S. Zrnić, “Chapter 3 — Radar and Its Environment,” in Doppler Radar and Weather Observations, 2nd ed. R. J. Doviak and D. S. Zrnić, Eds. Cambridge, Massachusetts, USA: Academic Press, 1993, pp. 30 — 63.

F. Vincent, O. Besson, S. Abakar-Issakha, Laurent Ferro-Famil, and F. Bodereau, “On the tradeoff between resolution and ambiguities for non-uniform linear arrays,” in 2016 IEEE Global Conference on Signal and Information Processing (GlobalSIP), Washington, USA, 2016, pp. 1052 — 1055.

M. H. Er, “Array pattern synthesis with a controlled mean-square sidelobe level,” IEEE Transactions on Signal Processing, vol. 40, no. 4, pp. 977 — 981, 1992.