• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.2
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• pp.445-452
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• 2024

This paper analyzes the navigation error for each rotational motion in order to design an optimal rotation sequence, which is a key technology in the rotational inertial navigation. Rotational inertial navigation system is designed to cancel out navigation errors caused by inertial sensor errors by periodically rotating the inertial measurement unit. A properly sequenced rotational motion cancels out the maximum amount of navigation error and is known as an optimal rotation sequence. To design such an optimal turning procedure, this paper identifies the feasible rotational motions that can be implemented in a rotational inertial navigation system and analyzes the navigation error introduced by each rotational motion. In addition, by analyzing the characteristics of the navigation error generated during a rotation sequence in combination, this paper presents the conditions for designing an optimal rotation sequence.

• Journal of Advanced Navigation Technology
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• v.27 no.1
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• pp.50-56
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• 2023

INS(Inertial Navigation System) calculates navigation information using a vehicle's acceleration and angular velocity without the outside information. However, when navigation is performed for a long time, navigation error gradually diverges and the performance decreases. To enhance INS's performance, the rotation of inertial measurement unit is developed to compensate error sources of inertial sensors, which is called RINS(Rotational Inertial Navigation System). This paper analyzes the influence of several errors for dual-axis RINS and the shows the results using simulation.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.46 no.11
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• pp.921-933
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• 2018

There is a method to enhance the pure navigation performance of INS(Inertial Navigation System) through the rotation of inertial measurement unit to compensate error sources of inertial sensors each other and that INS using this principle of operation is called rotational INS. In this paper, the exact error analysis of rotational INS based on ring laser gyro considering the coupling effect with gravity and earth rate is performed to evaluate the navigation performance by inertial sensor error sources. And error analysis and performance evaluation result confirmed by modelling and simulation is also proposed in this paper.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.2
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• pp.437-444
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• 2024

The rotational inertial navigation system can provide more accurate navigation information by mounting an IMU (Inertial Measurement Unit) on the gimbal and rotating the gimbal regularly to cancel out the errors of the IMU. However, when an attitude change occurs due to waves, the attitude error is not removed to 0 at the end of one cycle of the rotation procedure and causes a large position error. In this paper, considering this problem, we propose a method of stabilizing the external gimbal by rotating it based on the roll information of the vehicle. Based on simulation, the impact of waves is analyzed and the performance of external gimbal stabilization is verified.

• Journal of the Korea Institute of Military Science and Technology
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• v.22 no.2
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• pp.189-196
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• 2019

The inertial sensor errors in SDINS(Strapdown Inertial Navigation System) can be compensated by rotating the inertial measurement unit and it is called RINS(Rotational Inertial Navigation System). It is assumed that the error of the inertial sensor in RINS is a static bias. However, the error of the inertial sensor actually developed and produced is not a static bias due to the change of the temperature applied to the sensor and the influence of the earth's gravity acceleration. In this paper, we propose a six-position gyro bias calibration method to evaluate the gyro bias required for RINS and present the test results of applying it to a ring laser gyro inertial navigation system under development.

• Journal of Positioning, Navigation, and Timing
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• v.12 no.4
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• pp.409-421
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• 2023

In order to develop navigation systems, simulators that provide navigation sensors data are required. A trajectory generator that simulates vehicle motion is needed to generate navigation sensors data in the simulator. In this paper, a trajectory generator for evaluating navigation system performance is proposed. The proposed trajectory generator consists of two parts. The first part obtains parameters from the motion scenario file whereas the second part generates position, velocity, and attitude from the parameters. In the proposed trajectory generator six degrees of freedom, halt, climb, turn, accel turn, spiral, combined, and waypoint motions are given as basic motions with parameters. These motions can be combined to generate complex trajectories of the vehicle. Maximum acceleration and jerk for linear motion and maximum angular acceleration and velocity for rotational motion are considered to generate trajectories. In order to show the usefulness of the proposed trajectory generator, trajectories were generated from motion scenario files and the results were observed. The results show that the proposed trajectory generator can accurately simulate complex vehicle motions that can be used to evaluate navigation system performance.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1958-1961
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• 2004

Ring Laser Gyroscopes used as navigational sensors inherently experience a lock-in region, where very low rotational rates are not measurable. Most RLG manufacturers use a mechanical dither motor that applies a small oscillatory rotational motion larger than this region to resolve this problem. Any input acceleration that bends this dithering axis causes flexure error, which is a noncommutative error that can not be compensated by simply using integrated gyro sensor output. This paper introduces noncommutative error equations that define attitude errors caused by flexure errors. In this paper, flexure error is classified as sensor level error if the sensing axis coincides with the dithering axis and as system level error if the two axes do not coincide. The relationship between gyro output and the rotation vector is introduced and is used to define the coordinate transformation matrix and angular motion. Equations are derived for both sensor level and system level flexure error analysis. These equations show that RLG based INS attitude error caused by flexure is directly proportional to time, amount of input acceleration and the dynamic frequency of the vehicle.

• International Journal of Aeronautical and Space Sciences
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• v.1 no.1
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• pp.81-91
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• 2000

The mechanization of navigation equation is depending on the designer according to the orientation vector relating the body frame to a chosen to inertial and navigation frames for its purposes. This paper considers the appropriate Earth Fixed frame for short range vehicle and develops a mechanization and algorithm for Strapdown Inertial Navigation System(SDINS). This mechanization consists of two parts : translational mechanization and rotational mechanization{attitude determination). The accuracy, availability and performance of this SDINS mechanization are verified on the simulation and the numerical method for integration attitude propagation is compared with a well-known method in a precession motion.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.2
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• pp.381-389
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• 2012

This paper proposes a method which corrects location data of GPS for navigation of outdoor mobile robot. The method uses a Bayesian filter approach called the particle filter(PF). The method iterates two procedures: prediction and correction. The prediction procedure calculates robot location based on translational and rotational velocity data given by the robot command. It incorporates uncertainty into the predicted robot location by adding uncertainty to translational and rotational velocity command. Using the sensor characteristics of the GPS, the belief that a particle assumes true location of the robot is calculated. The resampling from the particles based on the belief constitutes the correction procedure. Since usual GPS data includes abrupt and random noise, the robot motion command based on the GPS data suffers from sudden and unexpected change, resulting in jerky robot motion. The PF reduces corruption on the GPS data and prevents unexpected location error. The proposed method is used for navigation of a mobile robot in the 2011 Robot Outdoor Navigation Competition, which was held at Gwangju on the 16-th August 2011. The method restricted the robot location error below 0.5m along the navigation of 300m length.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.2
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• pp.94-102
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• 2012

There have been many homing navigation algorithms for robotic system. In this paper, we suggest a bio-inspired navigation model. It builds path integration based on optical flow. We consider two factors on robot movements, translational movement and rotational movement. For each movement, we found distinguishable optical flows. Based on optical flow, we estimate ego-centric robot movement and integrate the path optimally. We can determine the homing direction and distance. We test this algorithm and evaluate the performance of homing navigation for robotic system.