In this project, a three-dimensional universal cooperative localizer (3D UCL) is proposed for vehicular ad-hoc networks (VANETs) in 3D space under varied types of ranging measurements including time-of-arrival (TOA), received signal strength (RSS), angle-of-arrival (AOA), and Doppler frequency. Its core idea is to exploit generalized approximate message passing (GAMP) to resolve the 3D cooperative positioning problem after converting it as a generalized linear mixing problem. Unfortunately, the positioning performance of 3D UCL is severely degraded by the inaccurate ranging measurements from the non-line-of-sight (NLOS) links. Therefore, a 3D geographical information enhanced UCL (3D GIE-UCL) is developed by combining 3D UCL with a NLOS identification mechanism assisted by geographical information. Finally, 3D UCL is accelerated by graphics processing unit (GPU) parallelization, particle reduction and message censoring. 3D GIE-UCL is accelerated by particle reduction and anchor upgrading. Simulation results validate state-of-the-art positioning performances and cooperative gains of both 3D UCL and 3D GIE-UCL after comparing them with existing cooperative localizers. 3D GIE-UCL approaches to its performance upper bound provided by its correspondence with oracle link-type information. 3D UCL and GIE-UCL show 241× and 3.3× speedup after adopting the acceleration techniques, respectively


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