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In this letter, we propose a novel Non-Line-of-Sight (NLOS) identification and error-mitigation method for dynamic object positioning and ultra-wideband (UWB) ranging. By utilizing inverse estimation on known Anchor Points (APs) and improved robust unscented Kalman filter (IRUKF), while fusing Gyroscope and Accelerometer data, the proposed technology identifies and compensates for NLOS occlusions between tag and APs, reducing positioning errors. The approach has been verified through simulation and experiment, with identification precision of 97.02%. After mitigating errors, substantial error reductions of 91.80% and 98.90% were observed in LOS and NLOS situations, respectively. Moreover, the developed IRUKF effectively minimizes mislocalization by 50.48% in harsh scenarios.