Abstract
To improve the precision and robustness of Unmanned Aerial Vehicle (UAV) integrated navigation systems, this paper presents an Interacting Multiple Model (IMM) navigation algorithm based on a Robust Cubature Kalman Filter (RCKF) with modified Zero Velocity Update (ZUPT) method assistance. This algorithm has a two-level fusion structure. At the bottom level, the Global Positioning System/Inertial Navigation System (GPS/INS) integrated navigation model and the Dynamic Zero Velocity Update/Inertial Navigation System (DZUPT/INS) integrated navigation model are established by modifying the Zero Velocity Update (ZUPT) method. Subsequently, the RCKF algorithm adopts a robust factor to weaken the influence of measurement outliers on the filter solution. At the top level, the estimation results of the GPS/INS integrated navigation model and the DZUPT/INS integrated navigation model are fused by the IMM algorithm. In addition to enhancing the robustness of filter estimation in the presence of measurement outliers, the proposed navigation algorithm also corrects navigation errors with ZUPT method assistance. Simulation and experimental analyses demonstrate the performance of the proposed navigation algorithm for UAVs.
Highlights
Inertial Navigation System (INS) is a navigation system that is able to calculate the position, velocity and attitude of a Unmanned Aerial Vehicle (UAV) with fairly good short-term navigation accuracy
To overcome the above problems, this paper proposes the Interacting Multiple Model (IMM) navigation algorithm, which is based on Robust Cubature Kalman Filter (RCKF), and applies the Zero Velocity Update (ZUPT) method to a UAV navigation system for the first time
IMM UAV NAVIGATION ALGORITHM BASED ON RCKF The DZUPT/INS model can correct navigation errors when the UAV is in level flight; when the UAV is not in level flight, the DZUPT/INS integrated navigation model no longer plays an important role, and the system mainly relies on the Global Positioning System/Inertial Navigation System (GPS/INS) model to obtain the correct navigation parameters
Summary
Inertial Navigation System (INS) is a navigation system that is able to calculate the position, velocity and attitude of a UAV with fairly good short-term navigation accuracy. Because the flight environment of UAVs is different from that of underwater vehicles, it is necessary to modify the ZUPT method according to the characteristics of UAVs and to apply the ZUPT method to integrated navigation systems in UAVs. To overcome the above problems, this paper proposes the IMM navigation algorithm, which is based on RCKF, and applies the ZUPT method to a UAV navigation system for the first time. The IMM algorithm calculates the weight of the DZUPT/INS model and the GPS/INS model in the navigation system. IMM algorithm is introduced to fuse the GPS/INS navigation model and the DZUPT/INS navigation model, which improves the precision and robustness of the navigation system at the same time.
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