?is paper deals with the problem of localization of mobile robot in indoor environment with mixed line-of-sight/nonline-ofsight\r\n(LOS/NLOS) conditions. To reduce the NLOS errors, a prior knowledge-based correction strategy (PKCS) is proposed to\r\nlocate the robot. ?is strategy consists of two steps: NLOS identi??cation and mitigation. We propose an NLOS identi??cation\r\nmethod by applying the statistical theory. ?en we correct the NLOS errors by subtracting the expected NLOS errors. Finally,\r\nthe residual weighting algorithm is employed to estimate the location of the robot. Simulation results show that the proposed\r\nstrategy signi??cantly improves the accuracy of localization in mixed LOS/NLOS indoor environment.
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