Robust Vehicle Positioning Based on Multi-Epoch and Multi-Antenna TOAs in Harsh Environments

For radio-based time-of-arrival (TOA) positioning systems applied in harsh environments, obstacles the surroundings and on vehicle itself will block signals from anchors, reduce number of available TOA measurements thus degrade localization performance. Conventional multi-antenna technique requires a good initialization to avoid local minima, suffers location ambiguity due insufficient and/or poor geometry anchors at single epoch. A new method based semidefinite programming (SDP), namely MEMA-SDP, is first designed address problem MEMA-TOA method. Then, an iterative refinement step developed obtain optimal result MEMA-SDP initialization. We derive Cramer-Rao lower bound (CRLB) analyze accuracy theoretically, show its superior performance over conventional single-epoch (SEMA) Simulation results environments demonstrate that i) provides initial estimation close real location, empirically guarantees global optimality final refined solution, ii) compared with SEMA method, has higher without ambiguity, consistent theoretical analysis.