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.

Automated summary

This paper introduces a new cooperative method for distributed target tracking using MIMO OFDM radar systems. By fusing radar signals with communication signals, as well as collaborating between multiple vehicles, highly accurate multi-target tracking is achieved.