Detecting Reliable Receiver Subsets for TDOA Localization Under Non-Line-of-Sight Using Subset Expansion

Abstract

Accurate time difference of arrival (TDOA) localization depends on reliable measurements. In cluttered indoor and urban environments, non-line-of-sight (NLOS) propagation is common. It introduces positive excess delays and biases TDOA observations. This letter studies receiver subset selection for TDOA localization under NLOS conditions. Conventional minimum cost fitting may select a subset with a low residual but a large localization error. To improve robustness, we propose a subset expansion detection framework. Each original four receiver subset is augmented with additional receivers to form multiple expanded configurations. This allows the same original subset to be examined repeatedly. We further develop a validation scheme that combines a balancing parameter test with a position consistency test. The former exploits the one-sided nature of NLOS delays. The latter checks whether position estimates remain consistent across different expanded subsets. Simulation results show that the proposed method achieves lower root mean square error than several baselines under a range of NLOS conditions.