In order to solve the problem of decreased navigation performance of the Global Navigation Satellite System (GNSS)/inertial navigation system (INS) integrated navigation systems in GNSS-denied environments, and to improve the navigation accuracy and robustness of the navigation system, a novel adaptive federated filter with a feedback scheme for a GNSS/INS/visual odometry (VO) integrated navigation system is proposed in this paper. A visual-inertial odometry system model with a multi-state constraint Kalman filter structure based on a polar geometry and trifocal tensor geometry between different images is established, which can provide better navigation accuracy in GNSS-denied environments. Moreover, a new method to obtain the information allocation factor according to the different navigation performances of local filters is deduced in this paper, which has low computational complexity and a simple structure. Meanwhile, an abnormal measurement detection algorithm based on fuzzy logic is proposed to detect the abnormal measurements of local filters. The results of the vehicle experiment with the publicly available real-world KITTI dataset show that the proposed algorithm can obtain reliable navigation results in GNSS-denied environments and improve the navigation accuracy and robustness of the GNSS/INS/VO integrated navigation system.

No abstract

No abstract

The problem of distributed power allocation in wireless sensor network (WSN) localization systems is investigated in this paper, using the game theoretic approach. Existing research focuses on the minimization of the localization errors of individual agent nodes over all anchor nodes subject to power budgets. When the service area and the distribution of target nodes are considered, finding the optimal trade-off between localization accuracy and power consumption is a new critical task. To cope with this issue, we propose a power allocation game where each anchor node minimizes the square position error bound (SPEB) of the service area penalized by its individual power. Meanwhile, it is proven that the power allocation game is an exact potential game which has one pure Nash equilibrium (NE) at least. In addition, we also prove the existence of an ϵ-equilibrium point, which is a refinement of NE and the better response dynamic approach can reach the end solution. Analytical and simulation results demonstrate that: (i) when prior distribution information is available, the proposed strategies have better localization accuracy than the uniform strategies; (ii) when prior distribution information is unknown, the performance of the proposed strategies outperforms power management strategies based on the second-order cone program (SOCP) for particular agent nodes after obtaining the estimated distribution of agent nodes. In addition, proposed strategies also provide an instructional trade-off between power consumption and localization accuracy.