Joint Beampattern Design and Resource Allocation for Radar Tracking With LPI Constraints Based on Manifold Optimization
Yipeng Zhong, Jinfeng Hu, Hua Wang, Kai Zhong, Xin Yee Tai, Yongfeng Zuo, Huiyong Li · IEEE Transactions on Aerospace and Electronic Systems · 2025
Beampattern design and resource allocation can enhance the multi-target tracking (MTT) accuracy and antiinterception capability of the colocated-MIMO radar systems. The MMT problem is formulated as a Posterior Cramer-Rao ´ Lower Bound (PCRLB) minimization problem while satisfying the low probability of intercept (LPI) constraints. Due to the non-convex nature of bandwidth constraints, the problem is challenging to solve. Existing methods are mainly classified into heuristic methods and convex relaxation methods (CRM), which suffer from a huge computational cost or a relaxation loss. We notice that the complex sphere manifolds and the real oblique manifold naturally satisfy the transmit power and bandwidth constraints, respectively, while exact penalty terms are particularly effective in handling inequality constraints. Leveraging these characteristics, we propose a joint beampattern design and resource allocation (JBDRA) strategy based on the manifold optimization (MO) framework. First, the introduction of exact penalty terms and the construction of product manifolds transform the original problem into an unconstrained problem. Then, we develop a parallel conjugate gradient descent (PCGD) algorithm with an adaptive step size to solve it. The proposed method has the following advantages over existing methods: i) achieves a maximum improvement of 6% in tracking accuracy compared to CRM; ii) reduces the computation time by approximately 50% compared to CRM