We show how the state of use of ultra-wideband (UWB) system is improved by removing systematic errors (bias) on device-level to improve accuracy and apply simple procedure to automate calibration process on the system-level to reduce manual efforts. On device-level, we discern the different sources of bias and establish a method that determines their values, for specific hardware and for individual devices. Our comprehensive approach includes simple, easy-to-implement methodologies for compensating these biases, resulting in a significant improvement in ranging accuracy. The mean ranging error has been reduced from 0.15 to 0.007 m, and the three-sigma error margin has decreased from 0.277 to approximately 0.103 m. To demonstrate this, a dedicated test setup was built. On system-level, we developed a method that avoids measuring all anchor positions one by one by exploiting increased redundancy from anchor-to-anchor and anchor-to-tag ranges, and automatically calculating the anchors topology (relative positions between each other). Nonlinear least squares provides the maximum likelihood estimate of the anchor positions and their uncertainty. This approach not only refines the accuracy of tag localization but also offers a predictive measure of its uncertainty, giving users a clearer understanding of the system's capabilities in real-world scenarios. This system-level enhancement is further complemented by the integration of a ranging protocol called automatic UWB ranging any-to-any, which offers additional layers of flexibility, reliability, and ease of deployment to the UWB localization process.