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In the GNSS-denied localization scenario, only received signals and corresponding distance measurements are available. Based on that, in this letter, we construct a multistage clustering-based model for UAV swarm. We characterize the proposed model as a coalition formation game (CFG) and provide corresponding preference criteria for algorithm design. A tree-like multistage clustering mechanism is adopted based on a coalitional graph game (CGG). Each cluster (local map) performs localization calculation and then merges through neighboring drones (NDs) stage by stage. The simulation results show that the proposed scheme can achieve better localization accuracy than the comparison algorithms and is more robust for irregular network topologies. [ABSTRACT FROM AUTHOR]

This paper provides an adaptive hybrid robust filter (AHRF) for multi-sensor relative navigation systems that can be used to support cooperative intelligent transport systems. It is known that Huber’s M-estimation based robust filter and the fault detection and exclusion (FDE) based RAIM filter each has its own drawbacks, depending on the nature of the observation error biases. Based on the interactive multiple model (IMM) framework, our proposed AHRF in this paper can take advantage of both filters in a complementary sense. A new adaptive IMM (AIMM) algorithm with Markov transition probability prediction is proposed to allow AHRF to switch efficiently between the two filters. We consider the relative navigation system with Global Navigation Satellite System (GNSS) and ultra-wideband (UWB) as observations to verify AHRF in three cases of possible failure modes and multipath-induced errors. Our results show that AHRF outperforms both the FDE and robust filter in all cases. AHRF framework can be further adapted to include many other fault-tolerant filters to improve the robustness of multi-sensor relative navigation system even further. [ABSTRACT FROM AUTHOR]

A cooperative integrity monitoring (CIM) algorithm is proposed in this work. Under the CIM architecture, the algorithm can fully exploit the global navigation satellite system (GNSS) data and inter-vehicle measurements data to improve the detection and isolation of faulty measurements due to multipath or non line of sight (NLOS). Taking the advantages of cooperative scheme, a residual decomposition method is used to model the measurement errors into common and specific parts, a greedy search strategy is used to exclude the faulty measurements based on its sub-statistics. Simulation results show that CIM has better detection of GNSS fault than traditional receiver autonomous integrity monitoring (RAIM). Also, CIM is capable of detecting the faulty outliers in inter-vehicle measurements. The results indicate that CIM can be applied to many existing multi-sensor cooperative positioning algorithms. [ABSTRACT FROM AUTHOR]

Resolution of integer cycle ambiguities is a critical requirement for centimeter-level carrier-phase positioning. This paper investigates the issue of GPS rapid resolution of integer cycle ambiguities, where a Low Earth orbit (LEO) ranging satellite is utilized to obtain large satellite geometry variations generated by its fast-moving property. We define a new system by adding the LEO ranging satellite transmitting signals on the L1 and/or L2 band to the GPS to improve the ability to estimate the integer cycle ambiguities rapidly, and analyse the performance using canonical metrics, such as gain in baseline precision, ambiguity precision and correlation, and ambiguity dilution of precision. Furthermore, in terms of success probability, we evaluate the performance of the proposed scheme compared with that of GPS. In addition, the impacts of the altitude of LEO satellite orbit, the number of visible satellites, the LEO satellite?s L2 navigation frequency, and different locations of the receivers on the ambiguity resolution are further analysed. The performance of the proposed scheme is demonstrated through in-depth numerical simulations. [ABSTRACT FROM AUTHOR]