Joint Transmission Resource Allocation and Path Planning Scheme for Airborne Radar Cooperation in Nonideal Detection Environments

Due to non-ideal detection factors such as noise interference and Doppler blind effect (DBE), target tracks frequently exhibit fragmentation or complete disappearance. Traditional airborne radar cooperative resource allocation schemes are designed under ideal detection conditions, which may prevent effective assessment of the evolution of tracks, potentially leading to model mismatch. To address this issue, a joint transmission resource allocation and path planning (JTRAPP) method is proposed to achieve continuous and high-precision tracking of multiple targets in non-ideal detection environments. Firstly, a target detection model is established to characterize the effects of noise interference and DBE on radar detection, and a track evolution model is developed to describe the evolution process of the complete track lifecycle. Subsequently, the Bayesian Cramer-Rao lower bound ´ based on the track-to-track fusion (BCRLB-TF) framework is derived, and a probability model is established to characterize the existence of the fused tracks. Normalized BCRLB-TF is then adopted as the criterion, while the fused track existence probability is adopted as a constraint, and then a mathematical optimization model w.r.t. the JTRAPP scheme is constructed. Finally, leveraging the unique structure of the optimization problem, a two-step solution algorithm based on binary search and the alternating direction method of multipliers (ADMM) is devised. Simulation results demonstrate that the proposed method effectively enhances radar tracking performance for multiple targets while satisfying the predetermined fused track existence probability.