Research on Topology Structure Optimization and Resource Allocation Strategy for Distributed Radar Systems in TDOA-based Localization

Abstract

Time Difference of Arrival (TDOA) positioning technology, by processing the time delay information of signals arriving at distributed nodes, is a core method for achieving high-precision target localization. However, in practical system deployment, the rationality of node topology layout and the coordination efficiency of resource allocation among nodes directly determine the system's positioning performance and overall efficiency. Most existing research focuses on algorithm-level improvements, often overlooking the joint impact of the coupling relationship between the spatial positions of nodes and their antenna boresight orientation on system performance. This paper addresses key issues such as insufficient consideration of the impact of node deployment and boresight orientation on performance and inefficient resource allocation in distributed radar systems for TDOA positioning, conducting joint research on topology optimization and resource allocation strategies. At the level of TDOA positioning principles, a high-precision mathematical model is constructed based on the hyperbolic intersection positioning mechanism, systematically considering practical factors such as time synchronization errors and measurement noise. An innovative intelligent optimization algorithm incorporating regional constraints is proposed, embedding physical constraints of node positions and boresight orientation into particle swarm optimization and genetic algorithms to achieve efficient optimization of radar layout. In terms of resource allocation, classic methods such as the Hungarian algorithm and auction algorithm are combined with a dynamic weight adjustment mechanism and game theory framework. A dynamic resource allocation strategy based on machine learning prediction is also designed, effectively enhancing the system's adaptive capability and resource utilization efficiency in complex environments. Finally, through a joint simulation platform using MATLAB and STK, multiple sets of comparative experiments are designed to comprehensively evaluate the effectiveness and practicality of the proposed strategies across various dimensions, including positioning accuracy, resource utilization, and robustness. The research results provide a solid theoretical basis and technical support for the engineering implementation of distributed radar TDOA positioning systems.