Research Article
Sparse Antenna Array Design for MIMO Radar Using Multiobjective Differential Evolution
Algorithm 2
Sparse antenna array design using MODE.
Input: , , , , , . | Step 1. Initialization: Generate random solutions using (16), and generate opposite solutions using opposition-based | learning. | Step 2. Coding: is generated using (18) for each solutions in these solutions; | Step 3. Calculate fitness value: is defined by (15), , evaluate the fitness value at these solutions, select the | fittest solution via fast non-dominated sorting, | , and store the solutions in the current population . | For to do | For to do | Step 4. Mutation: Randomly select three distinct individuals, , , and , | who are all different from the target individual. denotes the best | individuals among the three which is mean that the one has best | fitness function value. Generate a perturbed individual as follows: | | Step 5. Crossover: ; | Step 6. Pareto dominance | if ( dominates ) | replace by in the current population , and then add to the | advanced population . | else | add to the advanced population . | End | End | Step 7. Select the fittest solutions via fast non-dominated sorting and save | them in the ; denotes the best individual with respect to .; | End | Output: . |
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