A framework of cooperative resource scheduling and beamforming in networked node system for multi-target tracking under distributed collaborative interferences

Abstract

Traditionally, networked node systems (NNSs) have typically focused on multi-target tracking (MTT) under ideal environments, ignoring the presence of malicious interferences that cause NNS malfunctions. Electronic countermeasures have historically relied on stationary and independently distributed jammers. However, the emergence of dynamic distributed collaborative interferences (DCIs) makes traditional anti-interference methods inadequate. Hence, in response to the dynamic nature of DCIs, we propose a framework of cooperative resource scheduling and beamforming (FCRSB) specifically tailored for optimal MTT performance under DCIs. This FCRSB includes the signal model of NNS, signal-level fusion (SLF), data-level fusion (DLF), and the resource scheduling. Firstly, we introduce a distributed adaptive beamforming algorithm and monopulse angle measurement for SLF in each cluster of the NNS. Subsequently, after acquiring the measurements, DLF between clusters is incorporated. Then, we derive the posterior Cramér-Rao lower bound (PCRLB) for MTT in this scenario, which serves as the objective function to formulate the resource optimization problem-an NP-hard problem. To address this challenge, we propose a combined decoupled relaxation constraint and sequential convex programming approach to solve it and obtain the optimal beam selection and corresponding transmit power within the tracking mode. Finally, through numerical simulation experiments, we demonstrate the effectiveness of the proposed FCRSB for MTT under two cases of DCIs.