A modified real GA for the sparse linear array synthesis with multiple constraints

By Kesong Chen, Zhaoshui He, Ch. Han. 2006

183 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/469093e581e343c7e8bd23d25a006c07fd2b7dcf

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Aerospace Engineering

1. Sotirios K Goudos
2. Q. Feng
3. Z. Yu
4. John N. Sahalos
5. Wee Ser
6. Ling Cen
7. Wei Cen
8. Chuan Lin

In Electrical and Electronic Engineering

1. Sotirios K Goudos
2. Q. Feng
3. Z. Yu
4. John N. Sahalos
5. Wee Ser
6. Ling Cen
7. Wei Cen
8. Chuan Lin

Citations in the corpus

• Linear Aperiodic Array Synthesis Using an Improved Genetic Algorithm (2012, methodology): “Although the SA based method [20] has high performance in array pattern synthesis, it is possible that sparse arrays with continuously spaced sensors could have a high degree of freedoms in lowering the sidelobe level [14], [15], [17].”
• Synthesis of Unequally Spaced Antenna Arrays by Using Differential Evolution (2010, methodology): “2048864 algorithms (GAs) [5]–[9], particle swarm optimization (PSO) [1], simulated annealing (SA) [10] and so on, have become more and more popular in this community as they are applicable to both regular and irregular arrays, with or without constraints.”
• Sparse Linear Array Synthesis With Multiple Constraints Using Differential Evolution With Strategy Adaptation (2011, methodology): “The second example is that of a 37-element array with [17].”