Joint Power and Time Allocation Algorithm in Multi-radar System for Cooperative Target Detection

In recent years, the remarkable performance of airborne radar networks has increasingly come to the fore and garnered widespread attention. To delve deeper into the untapped potential of airborne radar networks, there is a critical need to explore more effective methods of resource allocation within their application domains. Current research has predominantly concentrated on singularly enhancing the accuracy of multi-target tracking or the performance of regional searches, overlooking the comprehensive consideration of resource allocation issues in the context of target detection. In order to improve the multi-target search and tracking performance of multi-radar system, a joint power and time allocation algorithm in multi-radar system for cooperative target detection is proposed in this study. The evaluation metrics for radar search and tracking performance are derived separately, based on signal detection theory and the Cramér-Rao lower bound. A joint optimization allocation model is developed for multi-aircraft radar systems geared towards cooperative detection. This model seeks to maximize radar operational performance as the optimization objective, which will be achieved under the constraint of predefined system power and time resources. Parameters including radar selection, radiated power, and time in radar search and tracking missions are jointly optimized. By incorporating the interior point method and particle swarm algorithm, a three-step decomposition approach is employed to solving the optimization problem. The results revealed that the proposed algorithm compared to average power allocation, average power-time allocation and random power-time allocation algorithms, improves radar system search performance and tracking accuracy effectively while adhering to the predefined system resource constraint.