Multi-Target Localization in Asynchronous MIMO Radars Using Sparse Sensing

Multi-target localization, warranted in emerging
applications like autonomous driving, requires targets to be
perfectly detected in the distributed nodes with accurate range
measurements. This implies that high range resolution is crucial
in distributed localization in the considered scenario. This work
proposes a new framework for multi-target localization, addressing
the demand for the high range resolution in automotive applications
without increasing the required bandwidth. In particular,
it employs sparse stepped frequency waveform and infers the
target ranges by exploiting sparsity in target scene. The range
measurements are then sent to a fusion center where direction of
arrival estimation is undertaken. Numerical results illustrate the
impact of range resolution on multi-target localization and the
performance improvement arising from the proposed algorithm
in such scenarios.