Range/optical flow-aided integrated navigation system in a strapdown sensor configuration

Abstract

This paper presents a measurement fusion mechanism of a strapdown range/vision sensor and IMU for an integrated navigation system in order to provide accurate relative navigation performance on a general ground surface in a GNSS-denied environment. The ground surface model during maneuvering is proposed as a piecewise continuous one, with flat and sloped surface profiles. In its implementation, the presented system consists of an IMU and the aided sensor modules, consisting of a vision sensor and a LiDAR. For obtaining improved performance of integrated navigation system, it is suggested a new measurement model and sensor fusion scheme incorporating two-dimensional flow vectors and range from aided sensors with inertial measurements. In filter realization, an indirect INS error model is employed, with measurement vectors containing two-dimensional velocity errors, and one differenced altitude in the navigation frame. In computing the altitude difference, the ground slope angle is estimated through two bisectional LiDAR signals, with a practical assumption representing a typical ground profile. In this process, the range variation due the attitude change of the system is compensated in a novel way, through geometric characteristics between range measurements and ground shape. Finally, the overall integrated system is implemented, based on the extended Kalman filter framework, and the performance is demonstrated through a simulation study with an aircraft flight trajectory scenario and experiments with an integrated hardware platform.