Localization systems utilizing Ultra-WideBand (UWB) have been widely used in dense urban and indoor environments. A moving UWB tag can be located by ranging to fixed UWB anchors whose positions are surveyed in advance. However, manually surveying the anchors is typically a dull and time-consuming process and prone to artificial errors. In this paper, we present an accurate and easy-to-use method for UWB anchor self-localization, using the UWB ranging measurements and readings from a low-cost Inertial Measurement Unit (IMU). The locations of the anchors are automatically estimated by freely moving the tag in the environment. The method is inspired by the Simultaneous Localization And Mapping (SLAM) technique used by the robotics community. A tightly-coupled Error-State Kalman Filter (ESKF) is utilized to fuse UWB and inertial measurements, producing UWB anchor position estimates and six Degrees of Freedom (6DoF) tag pose estimates. Simulated experiments demonstrate that our proposed method enables accurate self-localization for UWB anchors and smooth tracking of the tag.

Diversity reception of multipath Global Navigation Satellte System (GNSS) signals offers a new insight into carrier phase-based high-precision positioning. The focus of this paper is to demonstrate the fading independence between space and frequency diversity GNSS signals. In harsh urban environments, multipath components arrive to the mobile receiver antenna with different phases and Doppler shifts, therefore giving rise to the discontinuity of code and Doppler observations and large tracking errors. In this paper, an empirical model of fading GNSS signals is constructed, including power fluctuations and spread metrics. Based on this model, real BeiDou Navigation Satellite System (BDS) signals from two GNSS dual-frequency antennas are characterized, at both information and signal level. The block processing algorithm is utilized for signal investigation. Results show that: (1) a high proportion of asynchronous loss-of-lock (around 16%) is experienced by observations of diversity signals; and (2) power fluctuations of fading signals are uncorrelated in frequency separated branches unconditionally, yet for space diversity signals the independency exists in dynamic fading channels only. The results above corroborate the significant potential gain of diversity reception, and could be further implemented in researches of diversity combined GNSS parameter estimation in dense fading conditions.

This paper describes a robust integrated positioning method to provide ground vehicles in urbanenvironments with accurate and reliable localization results. The localization problem is formulated as a maximum a posteriori probability estimation and solved using graph optimization instead of Bayesian filter. Graph optimization exploits the inherent sparsity of the observation process to satisfy the real-time requirement and only updates the incremental portion of the variables with each new incoming measurement. Unlike the Extended Kalman Filter (EKF) in a typical tightly coupled Global Navigation Satellite System/Inertial Navigation System (GNSS/INS) integrated system, optimization iterates the solution for the entire trajectory. Thus, previous INS measurements may provide redundant motion constraints for satellite fault detection. With the help of data redundancy, we add a new variable that presents reliability of GNSS measurement to the original state vector for adjusting the weight of corresponding pseudorange residual and exclude faulty measurements. The proposed method is demonstrated on datasets with artificial noise, simulating a moving vehicle equipped with GNSS receiver and inertial measurement unit. Compared with the solutions obtained by the EKF with innovation filtering, the new reliability factor can indicate the satellite faults effectively and provide successful positioning despite contaminated observations.

The Spatial Only Processing Power Inversion (SOP-PI) algorithm is frequently used in Global Navigation Satellite System (GNSS) adaptive array receivers for interference mitigation because of its simplicity ofimplementation. This study investigates the effects of SOP-PI on receiver measurements for high-precisionapplications. Mathematical deductions show that if an array with a centro-symmetrical geometry is used, ideally, SOP-PI is naturally bias-free; however, this no longer stands when non-ideal factors, including array perturbations and finite-sample effect, are added. Simulations are performed herein to investigate how exactly the arrayperturbations affect the carrier phase biases, while diagonal loading and forward-backward averaging are proposed to counter the finite-sample effect. In conclusion, whether SOP-PI with a centro-symmetrical array geometry will satisfy the high precision demands mainly depends on the array perturbation degree of the element amplitude and the phase center.