An Adaptive Sensor Fusion Method with Applications in Integrated Navigation
نویسنده
چکیده
The Kalman filter (KF) is a form of optimal estimator characterized by recursive evaluation, which has been widely applied to the navigation sensor fusion. The adaptive algorithm is one of the approaches to prevent divergence problem of the Kalman filter when precise knowledge on the system models is not available. Two popular types of adaptive Kalman filter are the innovation-based adaptive estimation (IAE) approach and the adaptive fading Kalman filter (AFKF) approach. In this paper, an approach involving the concept of the two methods is proposed. The method is a synergy of the IAE and AFKF approaches. The ratio of the actual innovation covariance based on the sampled sequence to the theoretical innovation covariance is employed for dynamically tuning two filter parameters: fading factors and measurement noise scaling factors. The method has the merits of good computational efficiency and numerical stability. The matrices in the KF loop are able to remain positive definitive. Navigation sensor fusion using the proposed scheme applied to the loosely-coupled GPS/INS integration will be demonstrated.
منابع مشابه
A Hierarchical SLAM/GPS/INS Sensor Fusion with WLFP for Flying Robo-SAR's Navigation
In this paper, we present the results of a hierarchical SLAM/GPS/INS/WLFP sensor fusion to be used in navigation system devices. Due to low quality of the inertial sensors, even a short-term GPS failure can lower the integrated navigation performance significantly. In addition, in GPS denied environments, most navigation systems need a separate assisting resource, in order to increase the avail...
متن کاملAdaptive Fusion of Inertial Navigation System and Tracking Radar Data
Against the range-dependent accuracy of the tracking radar measurements including range, elevation and bearing angles, a new hybrid adaptive Kalman filter is proposed to enhance the performance of the radar aided strapdown inertial navigation system (INS/Radar). This filter involves the concept of residual-based adaptive estimation and adaptive fading Kalman filter and tunes dynamically the fil...
متن کاملGPS/INS Integration for Vehicle Navigation based on INS Error Analysis in Kalman Filtering
The Global Positioning System (GPS) and an Inertial Navigation System (INS) are two basic navigation systems. Due to their complementary characters in many aspects, a GPS/INS integrated navigation system has been a hot research topic in the recent decade. The Micro Electrical Mechanical Sensors (MEMS) successfully solved the problems of price, size and weight with the traditional INS. Therefore...
متن کاملEffective Mechatronic Models and Methods for Implementation an Autonomous Soccer Robot
Omni directional mobile robots have been popularly employed in several applications especially in soccer player robots considered in Robocup competitions. However, Omni directional navigation system, Omni-vision system and solenoid kicking mechanism in such mobile robots have not ever been combined. This situation brings the idea of a robot with no head direction into existence, a comprehensi...
متن کاملAdaptive Iterated Extended Kalman Filter and Its Application to Autonomous Integrated Navigation for Indoor Robot
As the core of the integrated navigation system, the data fusion algorithm should be designed seriously. In order to improve the accuracy of data fusion, this work proposed an adaptive iterated extended Kalman (AIEKF) which used the noise statistics estimator in the iterated extended Kalman (IEKF), and then AIEKF is used to deal with the nonlinear problem in the inertial navigation systems (INS...
متن کامل