A combinatorial optimization framework for subset selection in distributed multiple-radar architectures

Keyphrases

• Combinatorial Optimization 100%
• Optimization Framework 100%
• Subset Selection 100%
• Mean Square Error 100%
• Cramér-Rao Bound 100%
• Knapsack Problem 100%
• Distributed multiple-radar Architecture 100%
• Performance Metrics 50%
• Parameter Estimation 50%
• Computational Complexity 50%
• Performance-based 50%
• Selection Strategy 50%
• Problem Formulation 50%
• Resource Allocation 50%
• Estimation Process 50%
• Performance Goals 50%
• Operating Cost 50%
• Exhaustive Search 50%
• Communication Link 50%
• Performance Level 50%
• Active Radar 50%
• System Elements 50%
• Performance Gap 50%
• Central Processing 50%
• Target Localization 50%
• Resource Allocation Scheme 50%
• Processing Load 50%
• Active Systems 50%
• Cost Parameters 50%
• Mean-square-error Performance 50%
• Multiple Radar System 50%
• Decision Factors 50%
• Performance Thresholds 50%
• Operational Radar 50%
• Heuristic Algorithm 50%
• Estimation Enhancement 50%

Computer Science

• Optimization Framework 100%
• Feature Subset Selection 100%
• Combinatorial Optimisation 100%
• Knapsack Problem 100%
• Cramer-Rao Bound 100%
• Performance Metric 50%
• Computational Complexity 50%
• Selection Process 50%
• Problem Formulation 50%
• Performance Goal 50%
• Performance Error 50%
• Parameter Estimation 50%
• Exhaustive Search 50%
• Communication Link 50%
• Heuristic Algorithm 50%
• Performance Gap 50%
• Estimation Process 50%
• Resource Allocation Scheme 50%
• Operational Cost 50%
• Resource Allocation 50%
• Decision Making 50%

Engineering

• Mean Square Error 100%
• Knapsack Problem 66%
• Metrics 33%
• Radar Systems 33%
• Problem Formulation 33%
• Parameter Estimation 33%
• Operational Cost 33%
• Selection Process 33%
• Exhaustive Search 33%
• Computational Complexity 33%
• System Element 33%
• Error Performance 33%
• Communication Link 33%
• Active System 33%
• Target Localization 33%
• Operational Radar 33%
• Cost Efficiency 33%