Decentralized batch estimation for asynchronous data fusion in MIMO radar systems

This paper considers the multi-target tracking (MTT) problem in multi-input multi-output (MIMO) radar systems with the “defocused transmit-focused receive” (DTFR) operating mode, in which each transmitter forms a defocused beam to illuminate the whole surveillance region and each receiver adopts a focused beam to acquire a high angular resolution. When MIMO radars work in the DTFR operating mode, asynchronous data fusion (ADF) becomes very challenging since the measurements from the same target are acquired by different receivers at different times. To address this problem, we develop a novel batch estimation approach. By incorporating a time-aligned strategy, the local measurement as well as the most recently received asynchronous measurements from other receivers during a predefined update period are fused to jointly estimate the target state. In addition, motivated by the benefits of decentralized fusion architecture, a decentralized batch estimation (DBE) approach and its particle filtering based implementation (DBE-PF) are both presented. Finally, a target tracking scenario is also provided to demonstrate the effectiveness of the proposed DBE-PF approach.