Cooperative Method for Distributed Target Tracking for OFDM Radar With Fusion of Radar and Communication Information

Radar systems based on orthogonal ifrequency-division multiplexing (OFDM) are promising candidates for future intelligent transport networks because they combine target-estimation functions with communication network functions in one single system. By exploring this dual functionality, this paper presents a new cooperative method for distributed target tracking for multiple-input multiple-output (MIMO) OFDM radar systems. The proposed method employs a cascading information-fusion approach. First, the ego-vehicle performs a multi-target estimation by fusing the radar signals reflected by the targets with the communication signals it receives. Then, the ego-vehicle performs a tracking process, fusing its estimates with the estimates made by other in-network vehicles. By exploring the cooperation between vehicles, the proposed method enables the distributed tracking of targets. The result is a highly accurate multi-target tracking across the entire cooperative vehicle network, leading to improvements in transport reliability and safety. The proposed method is validated through simulations and laboratory measurements at 24 GHz.