cyclic difference sets
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2019 ◽  
Vol 24 (1) ◽  
pp. 12-23
Author(s):  
G. Qiang ◽  
◽  
L. Yi-Yang ◽  
V. Lutsenko ◽  
Z. Yu ◽  
...  

2017 ◽  
Vol 13 (5) ◽  
pp. 358-362 ◽  
Author(s):  
Ling-xiang Li ◽  
Hai-bing Li ◽  
Ji-bi Li ◽  
Hua Jiang

2016 ◽  
Vol 5 (3) ◽  
pp. 73 ◽  
Author(s):  
E. Sandi ◽  
F. Y. Zulkifli ◽  
E. T. Rahardjo

Reducing system complexity and cost in synthesizing a sparse array antenna design is a challenging task for practical communication systems, such as radar systems and space communication. In this paper, a hybrid technique to synthesize a linear sparse array antenna design is described. This technique is developed using two methods. The first method is a combinatorial approach that applies cyclic difference sets (CDS) integers to significantly reduce the number of antenna elements. The approach and procedure used to apply the new CDS method to configure a linear sparse array, with significant reduction of the spatial antenna dimension, is described. The second method, applied to the array result of the first method, is amplitude tapering using a binomial array approach to reduce the sidelobes level (SLL). The simulation and measurement results of the sample sparse array design showed that the SLL was reduced in comparison to the sparse array design using only the combinatorial CDS method.


Author(s):  
Jian Dong ◽  
Ronghua Shi ◽  
Ying Guo

As a recently proposed concept, multiple-input multiple-output (MIMO) radars exhibit much higher spatial resolution than traditional transmitter based radars because of the synthesized virtual array. In this paper, the problem of minimum redundancy (MR)-MIMO array synthesis is addressed, which seeks to maximize the virtual array aperture of MIMO radars for a given number of transmitting and receiving elements. A hybrid method combining autocorrelation property of cyclic difference sets (CDSs) and global search characteristics of ant colony optimization (ACO) is proposed for a rapid and numerically-effective exploration of MR-MIMO array configurations. Numerical experiments validate the proposed method, showing improvements in convergence rate and computational cost with respect to bare ACO-based search as well as improvements in the generality and configuration variety with respect to the CDS-based method.


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