Theoretical Research On Multi-Radar Networking In Radar Cooperative Detection

With the development of modern high-tech and the improvement of the informatization level of weaponry and equipment, the performance and surviv-ability of single electronic warfare equipment has been challenged day by day.Radar as the core of modern weapon system, should be changed from tradi-tional single platform to multi-platform detection system. The communication network technology based on multi-radar cooperative detection scene becomes the front direction of modern information war. To meet the demand of high bandwidth and low latency information transmission between multiple ship-borne radar and the challenges of dynamic diversity of detection tasks on the sea battlefield, the traditional wireless networking method is no longer applica-ble. Therefore, it is urgent to study the fast networking scheme in multi-radar cooperative detection scenario.This paper focuses on the initialization phase of the communication net-work in multi-radar cooperative detection scenarios. Two parts are depicted in the following: a novel multi-carrier asynchronous neighbor discovery algo-rithm named 3-way MC-NDA has been proposed in this paper based on the feedback acknowledgement mechanism to minimize discovery time. The 3-way MC-NDA improves the interaction rules of handshake process by adding ack-packets substate to avoid the data delivery failure caused by unnecessary collisions and shorten the discovery latency. Simulation results denote that the proposed 3-way MC-NDA can decrease the expected neighbor discovery time by 95.6% than 1-way's and 98.3% than 2-way's on average. Furthermore, it can overcome the sensitivity to the large node density in traditional 2-way al-gorithm.A task-driven radar network weighted clustering algorithm (TWCA) has been proposed in this paper: Task node and task cluster concepts are proposed on the basis of the actual scene demand. The network node modeling is per-formed for both general task and emergency task according to the practical type of tasks, and the cluster head election algorithm is constructed. In TWCA al-gorithm, the influence of tasks on the node attributes is taken into account:the general task considers the communication distance between the node and the task cluster and the antenna rotation angle when the task is distributed; the emergency task takes into account the efficiency of the task dispatching by the node and the risk of task cluster. Simulation results denote the stability of clus-tering results and the average time of task. For the stability, the clustering effect of TWCA algorithm is 40.73% higher than that of traditional WCA algorithm,and TWCA algorithm is better than WCA for task completion 19.17%, which verifies the correctness and validity of the TWCA algorithm.