Geometric Optimization of Distributed MIMO Radar System for Accurate Localization in Multiple Key Subareas

Abstract

In this paper, we study a geometric optimization problem of distributed multi-input multi-output (MIMO) radar system. We aim to enhance both the system surveillance and localization performance by adjusting the node positions. Different from existing researches, from a practical perspective, we consider the importance differences of the performance in different subareas and the coupled relationship between different radar performance. To optimize the node placement scheme, we first establish evaluation metrics respectively for surveillance and localization performance. Then, we formulate a multi-objective geometric optimization problem with complex coupled constraints. Considering that the final optimization problem is difficult to tackle due to its high dimensionality, non-convexity, and especially the complex coupled constraint, we propose a novel self-constrained multi-objective particle swarm optimization (SC-MOPSO) algorithm for fast computation. The SC-MOPSO algorithm can be efficiently applied to the established optimization problem with the complex coupled constraint satisfied. Moreover, the obtained Pareto-optimal solution set is more complete in comparison with the state-of-the-art algorithms. Finally, various numerical results show that the proposed method can effectively enhance both the system surveillance and localization performance while the complex coupled constraints are satisfied.