Sharif Digital Repository

This article aims to compensate the velocity and position errors that exist when the star sensor starts to work in a strapdown inertial navigation system aided by celestial navigation. These systems are integrated via unscented Kalman filter to estimate the current attitude and the gyros fixed bias, precisely. Since an accurate integration is desired, the nonlinear attitude equations are utilized in filter and these equations are propagated through a precise discretization method. Then, implementing the back-propagation and smoothing techniques, the initial attitude and the accelerometers fixed bias are also estimated. Finally, carrying out a parallel navigation, the velocity and position... 

In this research, Model Aided Inertial Navigation (MAIN) is used during the automatic landing of an Unmanned Aerial Vehicle (UAV). A new MAIN algorithm is proposed which is fast and accurate enough to be used in this phase. In this algorithm, the six Degree of Freedom (6DoF) flight simulation of the UAV is integrated with the Inertial Navigation System (INS) such that the 6DoF model acts as an aiding system for the INS. In the last parts of the landing phase, when the UAV flies in proximity of the ground surface, the proposed integrated navigation system can estimate the altitude of UAV utilizing the “ground effect” phenomenon. Therefore, the method does not have the drawbacks of active... 

In-motion alignment of a strapdown inertial navigation system, during slow maneuvers, is studied. Terrestrial velocity is fed back to the navigation system to estimate and compensate for the navigation errors. Observability of the errors is analyzed since the integrated navigation system is not fully observable. Then, the accuracy bounds of the navigation system in different motion scenarios are obtained analytically. Also, in order to minimize the errors of the navigation system, special maneuvers are designed based on the analytical derivations. The analytical results, obtained using the linearized error model, are verified through nonlinear simulation of different maneuvering and... 

The aim of this paper is to design an inertial navigation system (INS) for use in a geometry pipe inspection gauge, capable of measuring pipeline movements and producing the line's 3D map with a reasonable accuracy. A suitable reference path was generated as a design platform. Solving the navigation equations and compensating for the errors, by using extended Kaiman filter (EKF) approach, the INS path was generated and its position errors in all three directions were considered. Divergence problems due to far apart GPS position observations, was overcome by defining suitable threshold for the variances of the estimated errors. Copyright © 2007 by ASME  

In this paper, a new model-based Fault Detection and Diagnosis (FDD) method for an agile supersonic flight vehicle is presented. A nonlinear model, controlled by a classical closed loop controller and proportional navigation guidance in interception scenario, describes the behavior of the vehicle. The proposed FDD method employs the Inertial Navigation System (INS) data and nonlinear dynamic model of the vehicle to inform fins damage to the controller before leading to an undesired performance or mission failure. Broken, burnt, unactuated or not opened control surfaces cause a drastic change in aerodynamic coefficients and consequently in the dynamic model. Therefore, in addition to the... 

The problem of gyrocompassing using inertial sensors, i.e., gyros and accelerometers, is addressed. North finding, with an order of accuracy of one arc-min, is not only required for the initial alignment of inertial navigation systems, but also has a critical role to play in the guidance and navigation of ships that navigate for long periods of time. In this work, after extracting the error model of an inertial navigation system and augmenting it with the error model of inertial sensors, a processing algorithm based on the Kalman filter is designed and simulated to process the navigation system velocity error, and to estimate and correct tilt and heading errors along with gyro drifts and... 

In this paper, a novel algorithm for correcting the error of attitude in inertial navigation systems is introduced. Since the oftenly used differential equations of the navigation errors show the small rotation angles instead of the error of Euler angles, the nonlinear equation between the small rotation angles and the error of Euler angles, are derived. To obtain an approximative solution for the derived equations, third order multiplication of the small rotation angles are ignored and error of Euler angles are expressed explicitly as functions of the Euler angles and the small rotation angles. Based on the obtained solution, a new algorithm for attitude correction in inertial navigation is... 

Inertial navigation is a method for determining position and orientation of a vehicle, which operates according to Newton's laws of motion. Due to continual increase of output error because of measurement noise, bias, misalignment and so on, one may need one or more additional navigation systems to improve accuracy in long-Term navigation. In this paper, the error compensation based on GPS/INS data fusion algorithm is studied. Then, by designing a DSP processor-based hardware, GPS and INS data are recorded and GPS/INS data fusion algorithm is implemented. Results indicate that the accuracy of the positioning is improved and position, velocity, and orientation errors are confined to a limited... 

By development of ocean exploration, autonomous vehicles are employed to perform on-water and underwater tasks. Using an extended Kalman filter, Inertial Navigation System/Doppler Velocity Log (INS/DVL) integrated systems are trying to navigate in oceans and underwater environments when Global Positioning System (GPS) signals are not accessible. The dependency of DVL signals on acoustic environments may cause any DVL malfunction due to sea creatures or strong wave-absorbing material. In this paper, an improved version of evolutionary TS-fuzzy (eTS) is proposed in order to predict DVL sensor outputs at DVL malfunction moment, by utilizing an artificial intelligent (AI) aided integrated... 

The aim of this study was to determine the workspace of surgeon's body for designing more efficient surgical robots in the operation rooms. Five wearable inertial sensors were placed near the wrist and elbow joints and also on the thorax of surgeons to track the orientation of upper limb. Assuming that the lengths of five segments of an upper limb were known, measurements of the inertial sensors were used to determine the position of the wrist and elbow joints via an established kinematic model. subsequently, to assess the workspace of surgeon upper body, raw data were collected in the arthroscopy and laparoscopy operations. Experimental results demonstrated that the workspaces of surgeon's... 

The use of Model Aided Inertial Navigation (MAIN) during the landing of an Unmanned Aerial Vehicle (UAV) is investigated. A new MAIN algorithm is proposed, which is fast and accurate enough to be used in automatic landing. In this algorithm, the six Degree of Freedom (6DoF) model of the UAV is tightly coupled with the inertial navigation system; thus, the 6DoF model acts as an aiding system for the INS and vice versa. In the last parts of the landing phase in proximity of Earth, the proposed algorithm also estimates and removes the Ground Effect (GE) uncertainties and provides the height controller with a realistic model. An adaptive controller based on a parametric state-space model is used... 

This paper introduces a new method for improving the inertial navigation system errors using information provided by the camera. An unscented Kalman filter is used for integrating the inertial measurement unit data with the features’ constraints extracted from the camera’s image. The constraints, in our approach, comprise epipolar geometry of two consecutive images with more than 65% coverage. Tracking down a known feature in two consecutive images results in emergence of stochastic epipolar constraint. It emerges in the form of an implicit measurement equation of the Kalman filter. Correctly matching features of the two images is necessary for reducing the navigation system errors because... 

In today's world, control and navigation of autonomous underwater vehicles (AUVs) are quite challenging issues. In these fields, obtaining an identified dynamic model of AUV is a vital part. In this paper, a method for parameter estimation of an AUV planar model is proposed, which uses augmented state space technique and Square Root Transformed Unscented Kalman Filter (SR-TUKF) as an estimator. Furthermore, by modeling, misalignment between Inertial Measurement Unit (IMU) and Doppler Velocity Log (DVL) is estimated, simultaneously. Parameter identification is conducted using data of an AUV, equipped with Gyroscope, DVL and Encoder for measuring control inputs, in a planar maneuver. According...