LAUSR

The cooperative positioning method based on wireless sensors has become a popular positioning solution for the intelligent vehicle in recent years, especially in global navigation satellite system (GNSS)-denied environments. However, the error due to the non-line-of-sight (NLOS) propagation is the main problem, which affects cooperative positioning accuracy noticeably, thereby affecting the intelligent vehicle’s functions. In order to circumvent aforementioned problem, this article proposes a multisensor cooperative fusion positioning methodology to achieve reliable position in NLOS environments. Initially, the NLOS identification module based on the consistency of multisensor measurement value is used to detect NLOS signals. Then, the NLOS mitigation module based on multilayer perceptron (MLP) is implemented to inhibit the NLOS error by decoupling the relationship between the motion of intelligent vehicle and the change of ultrawide band (UWB) observations. Lastly, the adaptive fuzzy factor graph fusion module is designed for multisensor fusion to overcome the influence of variable signal quality. The real vehicle experiments have been conducted. Compared with the traditional least squares method, the root mean square error (RMSE) is reduced from 5.932 to 1.056 m, and the maximal error (MAX) is reduced from 38.886 to 5.583 m. The results have proven the effectiveness of our proposed methodology.