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A reverse ray tracing algorithm based on cluster analysis

Introduction of ray tracing can effectively solve problems of multi-path propagation, non-line-of-sight (NLOS) noise and hearability faced by localization algorithms in complex circumstances. However, the environment models are often too ideal and thus may affect the actual application of ray tracing; meanwhile, measurement errors of localization parameters can severely undermine the tracing results of signals' propagation paths. To address these problems, a reverse ray tracing algorithm is proposed based on cluster analysis. First, a two-dimensional propagation environment model is built, with the building surface assumed as the quasi-mirror to simulate the actual propagation environment of rays; second, the position orientating path and the area orientating path are defined based on features of the propagation path of multi-path localization signals. The algorithm proposed uses the branch tracing and search algorithm to calculate feasible paths according to the estimated TOA and AOA values of multi-path localization signals, and then employs cluster analysis to recognize position orientating paths and trace their propagations, based on which the sub-section weighting method is used to trace the maximum recognizable path among area orientating paths. Finally, simulation results demonstrate the rationality and effectiveness of the algorithm.