Integrated Navigation Fusion Strategy of INS/UWB for Indoor Carrier Attitude Angle and Position Synchronous Tracking

In some GPS failure conditions, positioning for mobile target is difficult. This paper proposed a new method based on INS/UWB for attitude angle and position synchronous tracking of indoor carrier. Firstly, error model of INS/UWB integrated system is built, including error equation of INS and UWB. And combined filtering model of INS/UWB is researched. Simulation results show that the two subsystems are complementary. Secondly, integrated navigation data fusion strategy of INS/UWB based on Kalman filtering theory is proposed. Simulation results show that FAKF method is better than the conventional Kalman filtering. Finally, an indoor experiment platform is established to verify the integrated navigation theory of INS/UWB, which is geared to the needs of coal mine working environment. Static and dynamic positioning results show that the INS/UWB integrated navigation system is stable and real-time, positioning precision meets the requirements of working condition and is better than any independent subsystem

Hybrid Adaptive Computational Intelligence-based Multisensor Data Fusion applied to real-time UAV autonomous navigation

Nowadays, there is a remarkable world trend in employing UAVs and drones for diverse applications. The main reasons are that they may cost fractions of manned aircraft and avoid the exposure of human lives to risks. Nevertheless, they depend on positioning systems that may be vulnerable. Therefore, it is necessary to ensure that these systems are as accurate as possible, aiming to improve the navigation. In pursuit of this end, conventional Data Fusion techniques can be employed. However, its computational cost may be prohibitive due to the low payload of some UAVs. This paper proposes a Multisensor Data Fusion application based on Hybrid Adaptive Computational Intelligence - the cascaded use of Fuzzy C-Means Clustering (FCM) and Adaptive-Network-Based Fuzzy Inference System (ANFIS) algorithms - that have been shown able to improve the accuracy of current positioning estimation systems for real-time UAV autonomous navigation. In addition, the proposed methodology outperformed two other Computational Intelligence techniques