LOS Signal Identification Based on Common Chord Intersection Point Position Deviation from MS in Target Localization

Target localization has been a popular research topic in recent years since it is the basis of all kinds location-based applications. For GNSS-denied urban or indoor environments, method based on time-of-arrival (TOA) one most methods due to its high accuracy and simplicity. However, Non-line-of-sight (NLOS) error major cause that degrades TOA-based method. Identifying whether received signal at base station (BS) line-of-sight (LOS) transmission NLOS key methods. In LOS identification methods, compared with statistic machine learning geometric constraint advantages simplicity without requiring priori knowledge signals large amounts training datasets. this paper, we propose two-step common chord intersection point position deviation from mobile stations (MS). first step, BSs are divided into multiple BS combinations every three BSs, TOA distance each combination estimated MS, whose satisfy Gaussian distribution roughly identified as enter second other discarded combination. mutual threshold discrimination result matrix, points combination, corresponding identified. The ultimately. Compared two proposed algorithm better accuracy, setting value theoretical basis, which facilitates application algorithm.