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Journal articles on the topic 'Inertial Navigation System'

Author: Grafiati
Published: 4 June 2021
Last updated: 31 May 2022

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1

Turygin, Yuri, Pavol Božek, Yuri Nikitin, Ella Sosnovich, and Andrey Abramov. "Enhancing the reliability of mobile robots control process via reverse validation." International Journal of Advanced Robotic Systems 13, no. 6 (December 1, 2016): 172988141668052. http://dx.doi.org/10.1177/1729881416680521.

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The article deals with integrating the inertial navigation unit implemented into the system of controlling the robot. It analyses the dynamic properties of the sensors of the inertial unit, for example, gyroscopes and accelerometers. The implementation of the original system of controlling the mobile robot on the basis of autonomous navigation systems is a dominant part of the article. The integration of navigational information represents the actual issue of reaching higher accuracy of required navigational parameters using more or less accurate navigation systems. The inertial navigation is the navigation based on uninterrupted evaluation of the position of a navigated object by utilizing the sensors that are sensitive to motion, that is, gyroscopes and accelerometers, which are regarded as primary inertial sensors or other sensors located on the navigated object.
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2

Kovalenko, A. M., and A. A. Shejnikov. "Model of the inertial and optical navigation system of the unmanned aerial vehicle." «System analysis and applied information science», no. 2 (August 18, 2020): 17–25. http://dx.doi.org/10.21122/2309-4923-2020-2-17-25.

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In article approaches to creation of the complex inertial and optical navigation system of the short-range tactical unmanned aerial vehicle are considered. Algorithms constant and periodic (in intermediate points of a route) are offered correction of the platformless onboard inertial navigation system. At integration of information on parameters of the movement of the unmanned aerial vehicle (received from the considered systems) the invariant loosely coupled scheme of data processing on the basis of the expanded filter of Kallman was used that allowed to lower significantly a systematic component of an error of the platformless inertial navigation system. Advantages of the complex inertial and optical navigation system when ensuring flight of the unmanned aerial vehicle in an area of coverage of means of radio-electronic fight of the opponent are shown. The results of modeling confirming a possibility of ensuring precision characteristics of the inertial and optical navigation system in the absence of signals of satellite radio navigational systems are presented.
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3

Szelmanowski, Andrzej, Mirosław Nowakowski, Zbigniew Jakielaszek, and Piotr Rogala. "Computer-based method for the technical condition evaluation of the Cardan inertial navigation system for the highly maneuverable aircraft." AUTOBUSY – Technika, Eksploatacja, Systemy Transportowe 20, no. 1-2 (February 28, 2019): 344–51. http://dx.doi.org/10.24136/atest.2019.064.

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Paper presents the original computer-based method of the technical condition evaluation of the analog inertial navigation systems on the basis of the calculated inertial speed course analysis. There are presented the mathematical relationships describing the influence of the angular velocity and linear accelerations sensors errors (used in inertial navigation systems on board the military aircraft) with the relation to the discrepancies of the calculated pilot-navigational parameters (such as inertial speed components and navigational position coordinates). On the example of the Cardan navigation system IKW-8 (used on board the highly-maneuverable SU-22 aircraft) there are presented the inertial speed course measurement and analysis possibilities as well as the criteria of technical condition evaluation and determination of the tendency of its changes.
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4

Bodhare, Hemant Gautam, and Asst Prof Gauri Ansurkar. "LEO based Satellite Navigation and Anti-Theft Tracking System for Automobiles." International Journal for Research in Applied Science and Engineering Technology 10, no. 4 (April 30, 2022): 557–63. http://dx.doi.org/10.22214/ijraset.2022.41316.

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Abstract: GPS and Inertial Navigation Systems (INS) are used today in automobile navigation and tracking systems to locate themselves in Four Dimensions (latitude, longitude, altitude, time). However, GNSS or GPS still has its own bottleneck, such as the long initialization period of Precise Point Positioning (PPP) without dense reference network. For navigation, a number of selected LEO satellites can be equipped with a transmitter to transmit similar navigation signals to land users, so they can act like GNSS satellites but with much faster geometric change to enhance GNSS capability, which is named as LEO constellation enhanced GNSS (LeGNSS). This paper focuses on Low Earth Orbit navigation and anti-theft tracking system in automobiles that represents a framework which enables a navigating vehicle to aid its Inertial Navigation System when GNSS or GPS signal becomes unusable. Over the course of following years LEO satellite constellation will be available globally at ideal geometric locations. LEO Satellite aided Inertial navigation system with periodically transmitted satellite positions has the potential to achieve meter-level-accurate location. Keywords: LEO constellation, LEO enhanced GNSS (LeGNSS), Precise Point Positioning (PPP), Inertial Navigation System (INS), Precise Orbit Determination (POD)
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5

Fariz, Outamazirt, Muhammad Ushaq, Yan Lin, and Fu Li. "Enhanced Accuracy Navigation Solutions Realized through SINS/GPS Integrated Navigation System." Applied Mechanics and Materials 332 (July 2013): 79–85. http://dx.doi.org/10.4028/www.scientific.net/amm.332.79.

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Strapdown Inertial Navigation Systems (SINS) displays position errors which grow with time in an unbounded manner. This degradation is due to the errors in the initialization of the inertial measurement unit, and inertial sensor imperfections such as accelerometer biases and gyroscope drifts. Improvement to this unbounded growth in errors can be made by updating the inertial navigation system solutions periodically with external position fixes, velocity fixes, attitude fixes or any combination of these fixes. The increased accuracy is obtained through external measurements updating inertial navigation system using Kalman filter algorithm. It is the basic requirement that the inertial data and data from the external aids be combined in an optimal and efficient manner. In this paper an efficient method for integration of Strapdown Inertial Navigation System (SINS), Global Positioning System (GPS) is presented using a centralized linear Kalman filter.
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6

Wang, Feng Lin, Xiu Lan Wen, and Dang Hong Sheng. "The Influence of Initial Error to the Rate Azimuth Platform Inertial System." Advanced Materials Research 442 (January 2012): 430–35. http://dx.doi.org/10.4028/www.scientific.net/amr.442.430.

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To lower the cost of the gravity passive navigation system, a rate azimuth inertial platform with a gravity sensor on it was put forward to constitute a navigator with gravity measuring, combined with digital gravity map, the system would come to a simple passive navigation system To master the influence of deterministic system error to navigation system, so can accurately present the precision index of gyroscopes and accelerometers, which are the main components of rate azimuth platform inertial navigation system, and initial calibration precision. With the error equations under static state, the characteristic equation of rate azimuth platform inertial navigation system is set up. Based on the solutions of the error equation, and the system error characteristics caused by the initial navigation error are deduced with analytical method.
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7

Naus, Krzysztof, and Łukasz Marchel. "SLAM aided Inertial Navigation System." Zeszyty Naukowe Akademii Marynarki Wojennej 200, no. 1 (March 30, 2015): 1. http://dx.doi.org/10.5604/0860889x.1161257.

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8

Daniec, Krzysztof, Karol Jędrasiak, Roman Koteras, and Aleksander Nawrat. "Embedded Micro Inertial Navigation System." Applied Mechanics and Materials 249-250 (December 2012): 1234–46. http://dx.doi.org/10.4028/www.scientific.net/amm.249-250.1234.

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This paper presents Embedded Inertial Navigation System designed and manufactured by the Department of Automatic Control and Robotics in Silesian University of Technology, Gliwice, Poland. Designed system is currently one of the smallest in the world. Within it there is implemented INS-GPS loosely coupled data fusion algorithm and point-to-point navigation algorithm. Both the algorithms and the constructed hardware were tested using two unmanned ground vehicles varying in size. Acquired results of those successful tests are presented.
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9

Konstantyan, Vladislav N., Rakhim S. Nakhushev, and Umar M. Yakhutlov. "FLIGHT SIMULATOR INERTIAL NAVIGATION SYSTEM." Electrical and data processing facilities and systems 14, no. 4 (December 2018): 97. http://dx.doi.org/10.17122/1999-5458-2018-14-4-97-103.

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10

Meyer, D., and D. Rozelle. "Milli-HRG inertial navigation system." Gyroscopy and Navigation 3, no. 4 (October 2012): 227–34. http://dx.doi.org/10.1134/s2075108712040086.

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11

Wang, Lin, Wenqi Wu, Guo Wei, Jinlong Li, and Ruihang Yu. "A Novel Information Fusion Method for Redundant Rotational Inertial Navigation Systems Based on Reduced-Order Kalman Filter." MATEC Web of Conferences 160 (2018): 07005. http://dx.doi.org/10.1051/matecconf/201816007005.

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The redundant rotational inertial navigation systems can satisfy not only the high-accuracy but also the high-reliability demands of underwater vehicle on navigation system. However, different systems are usually independent, and lack of information fusion. A reduced-order Kalman filter is designed to fuse the navigation information output of redundant rotational navigation systems which usually include a dual-axis rotational inertial navigation system being master system and a single-axis rotational inertial navigation system being hot-backup system. The azimuth gyro drift of single-axis rotational inertial navigation system can be estimated by the designed filter, whereby the position error caused by that can be compensated with the aid of designed position error prediction model. As a result, the improved performance of single-axis rotational inertial navigation system can guarantee the position accuracy in the case of dual-axis system failure. Semi-physical simulation and experiment verify the effectiveness of the proposed method.
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12

Qian, Kun, Jian-Guo Wang, and Baoxin Hu. "Novel Integration Strategy for GNSS-Aided Inertial Integrated Navigation." GEOMATICA 69, no. 2 (June 2015): 217–30. http://dx.doi.org/10.5623/cig2015-205.

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The conventional integration mechanism in GNSS (Global Navigation Satellite Systems) aided inertial integrated positioning and navigation system is mainly based on the continuous outputs of the navigation mechanization, the associated error models for navigation parameters, the biases of the inertial measurement units (IMU), and the error measurements. Its strong dependence on the a priori error characteristics of inertial sensors may suffer with the low-cost IMUs, e.g. the MEMS IMUs due to their low and unstable performance. This paper strives for a significant breakthrough in a compact and general integration strategy which restructures the Kalman filter by deploying a system model on the basis of 3D kinematics of a rigid body and performing measurement update via all sensor data inclusive of the IMU measurements. This novel IMU/GNSS Kalman filter directly estimates navigational parameters instead of the error states. It enables the direct use of the IMU's raw outputs as measurements in measurement updates of Kalman filter instead of involving the free inertial navigation calculation through the conventional integration mechanism. This realization makes all of the sensors in a system no longer to be differentiated between core and aiding sensors. The proposed integration strategy can greatly enhance the sustainability of low-cost navigation systems in poor GNSS and/or GNSS denied environment compared to the conventional aided error-state-based inertial navigation integration mechanism. The post-processed solutions are presented to show the success of the proposed multisensor integrated navigation strategy.
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13

Ushaq, Muhammad, and Jian Cheng Fang. "An Improved and Efficient Algorithm for SINS/GPS/Doppler Integrated Navigation Systems." Applied Mechanics and Materials 245 (December 2012): 323–29. http://dx.doi.org/10.4028/www.scientific.net/amm.245.323.

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Inertial navigation systems exhibit position errors that tend to grow with time in an unbounded mode. This degradation is due, in part, to errors in the initialization of the inertial measurement unit and inertial sensor imperfections such as accelerometer biases and gyroscope drifts. Mitigation to this growth and bounding the errors is to update the inertial navigation system periodically with external position (and/or velocity, attitude) fixes. The synergistic effect is obtained through external measurements updating the inertial navigation system using Kalman filter algorithm. It is a natural requirement that the inertial data and data from the external aids be combined in an optimal and efficient manner. In this paper an efficient method for integration of Strapdown Inertia Navigation System (SINS), Global Positioning System (GPS) and Doppler radar is presented using a centralized linear Kalman filter by treating vector measurements with uncorrelated errors as scalars. Two main advantages have been obtained with this improved scheme. First is the reduced computation time as the number of arithmetic computation required for processing a vector as successive scalar measurements is significantly less than the corresponding number of operations for vector measurement processing. Second advantage is the improved numerical accuracy as avoiding matrix inversion in the implementation of covariance equations improves the robustness of the covariance computations against round off errors.
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14

Lyu, Donghui, Jiongqi Wang, Zhangming He, Yuyun Chen, and Bowen Hou. "Landmark-Based Inertial Navigation System for Autonomous Navigation of Missile Platform." Sensors 20, no. 11 (May 29, 2020): 3083. http://dx.doi.org/10.3390/s20113083.

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As a new information provider of autonomous navigation, the on-orbit landmark observation offers a new means to improve the accuracy of autonomous positioning and attitude determination. A novel autonomous navigation method based on the landmark observation and the inertial system is designed to achieve the high-accuracy estimation of the missile platform state. In the proposed method, the navigation scheme is constructed first. The implicit observation equation about the deviation of the inertial system output is derived and the Kalman filter is applied to estimate the missile platform state. Moreover, the physical observability of the landmark and the mathematical observability of the navigation system are analyzed. Finally, advantages of the proposed autonomous navigation method are demonstrated through simulations compared with the traditional celestial-inertial navigation system and the deeply integrated celestial-inertial navigation system.
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15

Wen, Hao, and Da Ke Hu. "ARM Based Low Cost Integrated Navigation System Technology Research." Applied Mechanics and Materials 291-294 (February 2013): 2537–42. http://dx.doi.org/10.4028/www.scientific.net/amm.291-294.2537.

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This paper mainly studies the integrated navigation system technology of GPS and microelectronic mechanical system (MEMS) concerning on embedded processor S3C2440A. The system has the advantages of low cost, fast speed and small size, etc., which give wide prospects in a personal navigation application. This paper introduces the system hardware circuit structure design, emphasize on GPS navigation, MEMS inertial device for auxiliary navigation system software algorithm, and use Matlab to do data simulation on system model. The results show that GPS/MEMS inertial component integrated navigation obviously improved relative to separate GPS navigation or Strapdown inertial navigation in the accuracy and application value.
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16

E, Topolskov, Beljaevskiy L. L, and Serdjuke A. "IMPROVEMENT OF NAVIGATION SYSTEMS OF VEHICLES BY MEANS OF INERTIAL SENSORS AND INFORMATION PROCESSING USING PROBABILITY-GEOMETRIC METHODS." National Transport University Bulletin 1, no. 46 (2020): 353–64. http://dx.doi.org/10.33744/2308-6645-2020-1-46-353-364.

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Providing high accuracy of the coordinates and trajectories of objects by measurements conducted in navigation systems and complexes is an urgent task, which improves safety and efficiency of different modes of transport. However difficult environmental conditions, where vehicles are commonly used, stipulate influence of different factors on performance of onboard satellite navigation receivers, which are used as basic navigation devices for ground vehicle nowadays. Setting on cars used for common purposes additional navigation devices, which provide better performance, in most cases is economically unreasonable. Economically reasonable ways to improve onboard navigation complexes of vehicles, which are used for common purposes, are examined in this article. Functional diagram and principles of work of navigational complex, which uses the satellite navigation receiver and simplified variant of inertial navigation system is pointed as well. Also, the justification of methods for minimizing the error formats of coordinates and trajectories of moving objects based on information processing in multipositional, in particular satellite-inertial navigation systems and complexes, is presented. The obtained research results give an opportunity to develop an algorithm for coordinate refinement, which can be implemented in the improved on-board navigational complex of vehicle. KEY WORDS: NAVIGATION SYSTEMS AND COMPLEXES, INERTIAL SENSORS, NAVIGATION DEFINITIONS, ACCURACY AND RELIABILITY OF COORDINATES AND TRAJECTORIES OF MOVING OBJECTS, ELLIPS OF ERRORS, PROBABILISTIC-GEOMETRIC METHODS.
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17

Nusbaum, Uriel, Ilan Rusnak, and Itzik Klein. "Angular accelerometer‐based inertial navigation system." Navigation 66, no. 4 (December 2019): 681–93. http://dx.doi.org/10.1002/navi.336.

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18

KATAOKA, Kenichiro, and Hirofumi EGUCHI. "Software for strapdown inertial navigation system." Journal of the Japan Society for Aeronautical and Space Sciences 36, no. 408 (1988): 40–45. http://dx.doi.org/10.2322/jjsass1969.36.40.

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19

Larin, V. B., and A. A. Tunik. "On inertial navigation system error correction." International Applied Mechanics 48, no. 2 (March 2012): 213–23. http://dx.doi.org/10.1007/s10778-012-0517-y.

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20

Park, Jun-su, and Soon-Yong Park. "Visual Inertial Navigation System Optimization using The Depth of Features with Stereo." Journal of the Institute of Electronics and Information Engineers 58, no. 7 (July 31, 2021): 77–87. http://dx.doi.org/10.5573/ieie.2021.58.7.77.

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21

Novikov, P. V., A. A. Sheypak, V. N. Gerdi, V. V. Novikov, and V. N. Enin. "Algorithm for navigation of ground-based transport-technological facilities on the basis of integrated inertial-satellite navigation and odometer data." Izvestiya MGTU MAMI 11, no. 2 (June 15, 2017): 31–39. http://dx.doi.org/10.17816/2074-0530-66895.

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The dynamic development of navigation technologies has led to the emergence of practical applications for the solution of the problem of navigation of ground transport and technological facilities (GTTF). The most promising way of solving the navigation problem of GTTF is the creation of integrated inertial-satellite navigation systems. For a long period of time, the widespread use of navigation systems for transport applications was constrained by their high cost. The appearance of low-cost microelectromechanical (MEMS) inertial sensors on the market of navigation equipment provided the technological basis for the creation of small-scale inertial-satellite navigation systems. For transport applications, integrated inertial-satellite are integrated with additional information sensors, which include the odometer. Implementation of integrated systems is impeded by massively high level of intrinsic errors in MEMS sensors, as well as by the low accuracy of determining navigational parameters in the zone where the satellite signal of the satellite navigation systems is not stable. It is obvious that the development of methods for processing measurement information and the synthesis of specialized algorithms that ensure the accuracy of navigation systems GTTF is an urgent scientific task. In this paper, a schematic and technical solution for constructing an integrated inertial-satellite navigation systems with an integrated odometer sensor is presented and justified. A specialized navigation algorithm is developed that provides an integrated navigation solution for data coming from heterogeneous sources of measurements. A detailed functional diagram of the algorithm is given. A set of functional criteria for the quality and reliability of the navigation solution is defined. Correction algorithms for the main kinematic parameters of the trajectory motion of the GTTF - the true course angle, the location coordinates, the velocity vector components, are developed. The developed algorithm is invariant to the type of inertial sensors and in this sense is unified. Performance was confirmed by the results of full-scale tests of the navigation system of a forklift truck carrying out freight traffic on the territory of the seaport.
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22

Wang, Ning. "Satellite/Inertial Navigation Integrated Navigation Method Based on Improved Kalman Filtering Algorithm." Mobile Information Systems 2022 (May 19, 2022): 1–9. http://dx.doi.org/10.1155/2022/4627111.

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With the continuous development of positioning technology in today’s world, the accuracy requirements for navigation and positioning are also getting higher and higher. Global Positioning and Navigation System (GPS) can provide high-precision long-term navigation and positioning information. However, it has a strong dependence on the external environment, which means that it is easily disturbed by environmental changes and affects the accuracy of navigation and positioning and even leads to positioning failure. The inertial navigation system (INS) is an autonomous navigation system. It uses sensors to measure the specific force and angular velocity of the carrier for positioning and navigation, which means that it is less affected by the environment. However, the inertial navigation device will produce a certain initial error due to the restriction of the manufacturing level, and the error will increase with time, so the inertial navigation method is not suitable for long-term navigation. Therefore, it is of great practical significance to realize satellite/inertial navigation integrated navigation by combining the respective advantages of satellite navigation and inertial navigation methods and avoiding their respective disadvantages. This paper is aimed at studying the satellite/inertial navigation integrated navigation method based on the improved Kalman filter algorithm. The satellite inertial navigation integrated navigation experiment is carried out based on the improved Kalman filter algorithm. In the experiment, the noise reduction experiment of the designed satellite inertial navigation system was carried out by using the filtering noise reduction function of the improved Kalman filter algorithm, and the conclusion was drawn after the experiment. The navigation accuracy of the satellite inertial navigation system is improved by a total of 2 m after the improved Kalman filter algorithm is used to filter the noise reduction.
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23

Novikov, P. V., A. A. Sheypak, V. N. Gerdi, and V. V. Novikov. "Increase of the accuracy and reliability of output parameters determination of vehicle Integrated Navigation Systems." Izvestiya MGTU MAMI 10, no. 4 (December 15, 2016): 50–56. http://dx.doi.org/10.17816/2074-0530-66919.

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Dynamic development of navigation technologies opens up possibilities for the successful solution of a wide range of navigation tasks of mobile objects. For a long time the extension of the scope of navigation systems for transport applications was constrained by their high cost. The emergence of a small cheap inertial sensors, based on MEMS technology have resulted in integrated navigation systems, including the inertial and satellite GPS/GLONASS inertial modules. For solving problems of navigation of ground vehicles the integrated system is combinated with odometer. Nowadays a number of car navigation systems were made including the odometer along with the inertial measurement unit and a receiver of a satellite navigation system. However, most of these systems only exists in the form of models. The article provides the option of constructing the integrated navigation system of a vehicle brought to practical implementation. The analysis of the errors of the navigation system was made. The method of correction of errors due to the damping of the errors in speed with subsequent consideration of the damping of the amendments was proposed. Method is distinguished by ease of implementation and reliability. Correction of the navigation parameters calculated on the base of measurements of inertial sensors and odometer is permissible only when it is known that their accumulated errors have exceeded the corresponding error of the satellite navigation solution. Essentially new to the theory and practice of operation of vehicle is the introduction of a system of criteria characterizing the stability of mode generation navigation parameters. In article the numerical value of criteria-based assessments are of interest to developers of navigation systems, since accounting provides the reliability of the determination of output parameters of the system. The practical value of the presented research results, is that they can be used in the construction of high-precision navigation system of a ground vehicle.
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Duan, Yabo, Huaizhan Li, Suqin Wu, and Kefei Zhang. "INS Error Estimation Based on an ANFIS and Its Application in Complex and Covert Surroundings." ISPRS International Journal of Geo-Information 10, no. 6 (June 4, 2021): 388. http://dx.doi.org/10.3390/ijgi10060388.

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Inertial navigation is a crucial part of vehicle navigation systems in complex and covert surroundings. To address the low accuracy of vehicle inertial navigation in multifaced and covert surroundings, in this study, we proposed an inertial navigation error estimation based on an adaptive neuro fuzzy inference system (ANFIS) which can quickly and accurately output the position error of a vehicle end-to-end. The new system was tested using both single-sequence and multi-sequence data collected from a vehicle by the KITTI dataset. The results were compared with an inertial navigation system (INS) position solution method, artificial neural networks (ANNs) method, and a long short-term memory (LSTM) method. Test results indicated that the accumulative position errors in single sequence and multi-sequences experiments decreased from 9.83% and 4.14% to 0.45% and 0.61% by using ANFIS, respectively, which were significantly less than those of the other three approaches. This result suggests that the ANFIS can considerably improve the positioning accuracy of inertial navigation, which has significance for vehicle inertial navigation in complex and covert surroundings.
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Guang, Xingxing, Yanbin Gao, Henry Leung, Pan Liu, and Guangchun Li. "An Autonomous Vehicle Navigation System Based on Inertial and Visual Sensors." Sensors 18, no. 9 (September 5, 2018): 2952. http://dx.doi.org/10.3390/s18092952.

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The strapdown inertial navigation system (SINS) is widely used in autonomous vehicles. However, the random drift error of gyroscope leads to serious accumulated navigation errors during long continuous operation of SINS alone. In this paper, we propose to combine the Inertial Measurement Unit (IMU) data with the line feature parameters from a camera to improve the navigation accuracy. The proposed method can also maintain the autonomy of the navigation system. Experimental results show that the proposed inertial-visual navigation system can mitigate the SINS drift and improve the accuracy, stability, and reliability of the navigation system.
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Zhang, Ji Wei, Xiao Dong Xu, and Bo Wang. "Multi-Position Self-Calibration Method of Inertial Navigation System." Advanced Materials Research 580 (October 2012): 146–50. http://dx.doi.org/10.4028/www.scientific.net/amr.580.146.

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In order to solve the problem that in the dual axle rotating modulation inertial navigation system the angle between the horizon roller of the system and horizontal plane can't be removed, this paper provides an on-line self calibration method based on inertial navigation system, and this method realized the on-line self calibration of the inertial navigation system by calculating bias and scale factor both of the gyroscope and accelerometer, solving the problem that in the dual axle rotating modulation inertial navigation system the angle between the horizon roller of the system and horizontal plane can't be removed, providing an calculable basis for the prediction of attitude angle and realizing on-line autonomous self-calibration.
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27

Shrivastava, N. P., and S. Shrotriya. "Asynchronous Message Transmission Technique for Latency Requirements in Time Critical Ship-borne System." Defence Science Journal 66, no. 1 (January 27, 2016): 26. http://dx.doi.org/10.14429/dsj.66.8502.

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<p>A solution to data ageing requirements in time critical ship system like fire control system is presented. In an operational sea borne platform, navigation requirements for the onboard systems are fulfilled by ring laser gyro-based inertial navigation system. For critical systems like fire control system, navigational data must be delivered in real time without any delay. However due to delay occurring in processing of raw information and transmission of data on interface bus some latency is introduced. Algorithm for an asynchronous message transmission technique from inertial navigation system to user system to meet its latency requirements is discussed. Latency requirement is achieved by sending a separate message with the time stamp for the instance the first byte of 100 Hz attitude data is received at the processing computer of navigation system.</p><p><strong>Defence Science Journal, Vol. 66, No. 1, January 2016, pp. 26-29, DOI: http://dx.doi.org/10.14429/dsj.66.8502</strong></p>
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Ghasemzadeh, Vahid, and Mohammad M. Arefi. "Design, modeling, and simulation of an INS system using an asymmetric structure of six accelerometers and its error analysis in the ECEF frame." Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 231, no. 13 (August 11, 2016): 2345–61. http://dx.doi.org/10.1177/0954410016662059.

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The inertial navigation system is one of the most important and common methods of navigation. In this system, accelerometers and gyroscopes are used to measure linear accelerations and angular velocities, respectively. Accelerometers have simpler manufacture techniques, lower cost, and smaller volume and weight in comparison with gyroscopes. Therefore, in some application of navigation systems, non-gyro inertial navigation systems based on accelerometers are used. In this paper, an asymmetric structure of six accelerometers is proposed. Then dynamic relations of this structure are extracted. This structure and its relations can determine linear accelerations and angular velocities, completely. Moreover, the algorithm of inertial navigation in earth centered earth fixed (ECEF) frame is suggested. Error analysis as of the most important issues in inertial navigation is discussed. Thus, bias, misalignment, sensitivity, and noise of accelerometers are modeled appropriately. In addition, a symmetric structure of accelerometers is proposed and its equations are derived. Finally, the designed system, error model of accelerometers, and algorithm of inertial navigation in ECEF frame are simulated. The results of simulation show that the designed system has suitable accuracy and applications for short time navigation. Furthermore, results confirm that the proposed asymmetric structure requires less accelerometer in comparison with symmetric structure.
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Chen, Danhe, Konstantin Neusypin, Maria Selezneva, and Zhongcheng Mu. "New Algorithms for Autonomous Inertial Navigation Systems Correction with Precession Angle Sensors in Aircrafts." Sensors 19, no. 22 (November 17, 2019): 5016. http://dx.doi.org/10.3390/s19225016.

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This paper presents new algorithmic methods for accuracy improvement of autonomous inertial navigation systems of aircrafts. Firstly, an inertial navigation system platform and its nonlinear error model are considered, and the correction schemes are presented for autonomous inertial navigation systems using internal information. Next, a correction algorithm is proposed based on signals from precession angle sensors. A vector of reduced measurements for the estimation algorithm is formulated using the information about the angles of precession. Finally, the accuracy of the developed correction algorithms for autonomous inertial navigation systems of aircrafts is studied. Numerical solutions for the correction algorithm are presented by the adaptive Kalman filter for the measurement data from the sensors. Real data of navigation system Ts-060K are obtained in laboratory experiments, which validates the proposed algorithms.
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Jiang, Changhui, Yuwei Chen, Shuai Chen, Yuming Bo, Wei Li, Wenxin Tian, and Jun Guo. "A Mixed Deep Recurrent Neural Network for MEMS Gyroscope Noise Suppressing." Electronics 8, no. 2 (February 4, 2019): 181. http://dx.doi.org/10.3390/electronics8020181.

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Currently, positioning, navigation, and timing information is becoming more and more vital for both civil and military applications. Integration of the global navigation satellite system and /inertial navigation system is the most popular solution for various carriers or vehicle positioning. As is well-known, the global navigation satellite system positioning accuracy will degrade in signal challenging environments. Under this condition, the integration system will fade to a standalone inertial navigation system outputting navigation solutions. However, without outer aiding, positioning errors of the inertial navigation system diverge quickly due to the noise contained in the raw data of the inertial measurement unit. In particular, the micromechanics system inertial measurement unit experiences more complex errors due to the manufacturing technology. To improve the navigation accuracy of inertial navigation systems, one effective approach is to model the raw signal noise and suppress it. Commonly, an inertial measurement unit is composed of three gyroscopes and three accelerometers, among them, the gyroscopes play an important role in the accuracy of the inertial navigation system’s navigation solutions. Motivated by this problem, in this paper, an advanced deep recurrent neural network was employed and evaluated in noise modeling of a micromechanics system gyroscope. Specifically, a deep long short term memory recurrent neural network and a deep gated recurrent unit–recurrent neural network were combined together to construct a two-layer recurrent neural network for noise modeling. In this method, the gyroscope data were treated as a time series, and a real dataset from a micromechanics system inertial measurement unit was employed in the experiments. The results showed that, compared to the two-layer long short term memory, the three-axis attitude errors of the mixed long short term memory–gated recurrent unit decreased by 7.8%, 20.0%, and 5.1%. When compared with the two-layer gated recurrent unit, the proposed method showed 15.9%, 14.3%, and 10.5% improvement. These results supported a positive conclusion on the performance of designed method, specifically, the mixed deep recurrent neural networks outperformed than the two-layer gated recurrent unit and the two-layer long short term memory recurrent neural networks.
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31

Gao, Wei, and Lei Zhang. "Simulating Gyro of Strapdown Inertial Navigation System Based on Star Sensor." Applied Mechanics and Materials 182-183 (June 2012): 1090–94. http://dx.doi.org/10.4028/www.scientific.net/amm.182-183.1090.

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In inertial navigation system, gyro is used to measure the angular velocity of carrier relative to inertial space for achieve attitude matrix updated in real time. Gyro difficult to eliminate the error, results in strapdown inertial navigation system precision decrease with time. Star sensor is a high-precision attitude measuring instrument and don’t require any priori information, the attitude date can be provided by star sensor. Thus, gyro is simulated by star sensor in order to improve the precision of strapdown inertial navigation system.
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32

Ben, Yueyang, Xinle Zang, Qian Li, Xingyu Liu, and Hainan Chen. "System reset for underwater strapdown inertial navigation system." Ocean Engineering 182 (June 2019): 552–62. http://dx.doi.org/10.1016/j.oceaneng.2019.04.025.

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33

Zhang, H., L. Wang, TX Song, and K. Li. "Error analysis and compensation for dual-axis inertial navigation system with horizontal rotation modulation." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 233, no. 1 (February 13, 2018): 313–22. http://dx.doi.org/10.1177/0954406218756940.

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Rotational inertial navigation system can significantly improve the navigation accuracy by rotating the inertial measurement unit about gimbals periodically. The precise calibration for installation errors and scale factor errors in rotational inertial navigation system can contribute to better navigation performance further. Especially in application requiring excellent azimuth precision, the horizontal rotation modulation will be badly required to modulate the vertical sensors’ errors as periodic variation, which can make inhibiting effect on the navigation errors. However, it also enlarges the impact of specific errors, which contains gyro’s scale factor error and the installation errors of inertial components. To meet the requirement of navigation precision, this paper has made error analysis and established mathematical model for a proposed horizontal rotation modulation in dual-axis rotational inertial navigation system. The crucial error parameters can be calibrated based on the measurements of attitude and velocity output without additional equipment. The results of experiment performed in an actual system demonstrate that navigation accuracy has been improved significantly, fully illustrating the significance and necessity of the calibration for specific errors in the horizontal rotation modulation.
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34

Ibrahim, M. A., and V. V. Luk'yanov. "Algorithms and Configuration for a Moving Object Attitude Control System Based on Microelectromechanical Sensors." Herald of the Bauman Moscow State Technical University. Series Instrument Engineering, no. 2 (131) (June 2020): 44–58. http://dx.doi.org/10.18698/0236-3933-2020-2-44-58.

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Inertial systems for attitude control, stabilisation and navigation of moving objects boast a range of unique qualities, the most important of which are autonomy and interference immunity. At present, strap-down inertial navigation systems using inexpensive and compact microelectromechanical sensors are popular. The biggest disadvantage of the attitude control systems utilising microelectromechanical sensors is rapid error accumulation over time. The main error sources in strap-down inertial navigation systems are the errors of angular velocity sensors and accelerometers. Currently the accuracy required is ensured by the attitude control system processing the following two signals simultaneously: the magnetometer signal and the signal received from global navigation satellite systems such as GPS (NAVSTAR) and/or GLONASS. We developed an unconventional approach to integrating the two systems, that is, a strap-down inertial navigation system and a global navigation satellite system. It involves using the difference between the accelerations computed according to the global navigation satellite systems and those computed by the acelerometers and transformed to the geographic coordinate system for evaluating and compensating for the error of attitude angle assessment via the kinematic channel. Since this approach does not use integration of accelerometer readings, the attitude angle errors at the initial stage do not accumulate over time. Numerical simulation results of the algorithms developed show that the attainable attitude angle estimation accuracy significantly exceeds the accuracy of conventional methods
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35

Mwenegoha, Hery, Terry Moore, James Pinchin, and Mark Jabbal. "Model-Based Autonomous Navigation with Moment of Inertia Estimation for Unmanned Aerial Vehicles." Sensors 19, no. 11 (May 29, 2019): 2467. http://dx.doi.org/10.3390/s19112467.

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The dominant navigation system for low-cost, mass-market Unmanned Aerial Vehicles (UAVs) is based on an Inertial Navigation System (INS) coupled with a Global Navigation Satellite System (GNSS). However, problems tend to arise during periods of GNSS outage where the navigation solution degrades rapidly. Therefore, this paper details a model-based integration approach for fixed wing UAVs, using the Vehicle Dynamics Model (VDM) as the main process model aided by low-cost Micro-Electro-Mechanical Systems (MEMS) inertial sensors and GNSS measurements with moment of inertia calibration using an Unscented Kalman Filter (UKF). Results show that the position error does not exceed 14.5 m in all directions after 140 s of GNSS outage. Roll and pitch errors are bounded to 0.06 degrees and the error in yaw grows slowly to 0.65 degrees after 140 s of GNSS outage. The filter is able to estimate model parameters and even the moment of inertia terms even with significant coupling between them. Pitch and yaw moment coefficient terms present significant cross coupling while roll moment terms seem to be decorrelated from all of the other terms, whilst more dynamic manoeuvres could help to improve the overall observability of the parameters.
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36

Gao, Yang, Wan Chun Gao, Jing Shuo Xu, and Rui Li Zhang. "Design and Implementation of Visual Simulation System for Strapdown Inertial Navigation." Applied Mechanics and Materials 336-338 (July 2013): 343–47. http://dx.doi.org/10.4028/www.scientific.net/amm.336-338.343.

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To obtain real-time navigation data, actual flight involves a lot of efforts as well as a heavy financial budget, and the collected data can hardly be reused. Visual simulation system for strapdown inertial navigation was developed. The system is based on object-oriented thought and modular design, outputs SINS simulation data in different flight conditions and precisions, and shows simulation data on virtual multi function display. The system has the feature of flexibility and extensibility and can be used to reduce effectively the experimental expense and shorten the developing period of strapdown inertial navigation system. The real-time SINS simulation data output is of enormous engineering significance to verify the inertial navigation system algorithm, and complete the integrated avionics systems cross-linking experiments in laboratory.
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37

Fang, Susu, Zengcai Wang, and Lei Zhao. "Research on the automotive sensor–aided low-cost inertial navigation system for land vehicles." Advances in Mechanical Engineering 11, no. 1 (January 2019): 168781401882287. http://dx.doi.org/10.1177/1687814018822876.

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When a low-cost micro-electro-mechanical system inertial measurement unit is used for a vehicle navigation system, errors will quickly accumulate because of the large micro-electro-mechanical system sensor measurement noise. To solve this problem, an automotive sensor–aided low-cost inertial navigation system is proposed in this article. The error-state model of the strapdown inertial navigation system has been derived, and the measurements from the wheel speed sensor and steer angle sensor are used as the new observation vector. Then, the micro-electro-mechanical system inertial measurement unit/wheel speed sensor/steer angle sensor–integrated system is established based on adaptive Kalman filtering. The experimental results show that the positioning error of micro-electro-mechanical system inertial measurement unit/wheel speed sensor/steer angle sensor is 94.67%, 98.88%, and 97.88% less than the values using pure strapdown inertial navigation system in the east, north, and down directions, respectively. The yaw angle error is reduced to less than 1°, and the vehicle velocity estimation of micro-electro-mechanical system inertial measurement unit/wheel speed sensor/steer angle sensor–integrated navigation system is closer to the reference value. These results show the precision of the integrated navigation solution.
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38

Li, Ziyuan, Huapeng Yu, Ye Li, Tongsheng Shen, Chongyang Wang, and Zheng Cong. "Position Correction and Trajectory Optimization of Underwater Long-Distance Navigation Inspired by Sea Turtle Migration." Journal of Marine Science and Engineering 10, no. 2 (January 27, 2022): 163. http://dx.doi.org/10.3390/jmse10020163.

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Accumulating evidence suggests that migrating animals store navigational “maps” in their brains, decoding location information from geomagnetic information based on their perception of the magnetic field. Inspired by this phenomenon, a novel geomagnetic inversion navigation framework was proposed to address the error constraint of a long-distance inertial navigation system. In the first part of the framework, the current paper proposed a geomagnetic bi-coordinate inversion localization approach which enables an autonomous underwater vehicle (AUV) to estimate its current position from geomagnetic information like migrating animals. This paper suggests that the combination of geomagnetic total intensity (F) and geomagnetic inclination (I) can determine a unique geographical location, and that there is a non-unique mapping relationship between the geomagnetic parameters and the geographical coordination (longitude and latitude). Then the cumulative error of the inertial navigation system is corrected, according to the roughly estimated position information. In the second part of the framework, a cantilever beam model is proposed to realize the optimal correction of the INS historical trajectory. Finally, the correctness of the geomagnetic bi-coordinate inversion localization model we proposed was verified by outdoor physical experiments. In addition, we also completed a geomagnetic/inertial navigation integrated long-distance semi-physical test based on the real navigation information of the AUV. The results show that the geomagnetic inversion navigation framework proposed in this paper can constrain long-distance inertial navigation errors and improve the navigation accuracy by 73.28% compared with the pure inertial navigation mode. This implies that the geomagnetic inversion localization will play a key role in long-distance AUV navigation correction.
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39

Zhang, Ling, Jianye Liu, Jizhou Lai, and Zhi Xiong. "Performance Analysis of Adaptive Neuro Fuzzy Inference System Control for MEMS Navigation System." Mathematical Problems in Engineering 2014 (2014): 1–7. http://dx.doi.org/10.1155/2014/961067.

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Characterized by small volume, low cost, and low power, MEMS inertial sensors are widely concerned and applied in navigation research, environmental monitoring, military, and so on. Notably in indoor and pedestrian navigation, its easily portable feature seems particularly indispensable and important. However, MEMS inertial sensor has inborn low precision and is impressionable and sometimes goes against accurate navigation or even becomes seriously unstable when working for a period of time and the initial alignment and calibration are invalid. A thought of adaptive neuro fuzzy inference system (ANFIS) is relied on, and an assistive control modulated method is presented in this paper, which is newly designed to improve the inertial sensor performance by black box control and inference. The repeatability and long-time tendency of the MEMS sensors are tested and analyzed by ALLAN method. The parameters of ANFIS models are trained using reasonable fuzzy control strategy, with high-precision navigation system for reference as well as MEMS sensor property. The MEMS error nonlinearity is measured and modulated through the peculiarity of the fuzzy control convergence, to enhance the MEMS function and the whole MEMS system property. Performance of the proposed model has been experimentally verified using low-cost MEMS inertial sensors, and the MEMS output error is well compensated. The test results indicate that ANFIS system trained by high-precision navigation system can efficiently provide corrections to MEMS output and meet the requirement on navigation performance.
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40

Pivarčiová, Elena, Pavol Božek, Yuri Turygin, Ivan Zajačko, Aleksey Shchenyatsky, Štefan Václav, Miroslav Císar, and Boris Gemela. "Analysis of control and correction options of mobile robot trajectory by an inertial navigation system." International Journal of Advanced Robotic Systems 15, no. 1 (January 1, 2018): 172988141875516. http://dx.doi.org/10.1177/1729881418755165.

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The article deals with the research of the supplementation of industrial robot effector trajectory’s control systems by an inertial navigation system. The method of reverse validation and location of an object in a navigated reference system does not require additional calibration. The goal of the research is to verify the assumption that it is possible to control and correct the programmed mobile robot trajectory by implementing an inertial navigation system even in a case when the inertial navigation system is used as the only trajectory control device. The data obtained are processed by the proposed and detailed application.
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41

Meng, Yujing, Liying Zhao, Shuli Guo, and Lintong Zhang. "An Improved Navigation Method of Inertial Navigation System for Three-Dimensional Positioning." Journal of Nanoelectronics and Optoelectronics 16, no. 11 (November 1, 2021): 1725–32. http://dx.doi.org/10.1166/jno.2021.3114.

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An inertial navigation system (INS) that uses portable and service inertial measurement units (IMUs) can potentially obtain two-dimensional (2D) trajectories of pedestrians. The use of updated algorithms is useful in reducing drift accumulation errors of inertial sensors. This paper introduces an improved navigation technique based on the zero-velocity update (ZUPT) method in order to measure the displacement length. Meanwhile, the zero-height update (ZHUPT) and the modified heuristic drift reduction (HDR) methods are adopted to decrease measurement error within a 2D plane. Experimental results indicate that the navigation errors of 2D trajectories are below 2%. Furthermore, a height update method has been proposed for three-dimensional (3D) navigation that uses the actual slope angle of the stairs and can restrain the height divergence. The terminal height error accounts for 1.28% of the total altitude variation.
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42

Yan, Fei, Wangyang Zhao, Xingling Wang, Kai Wang, and Yuanming Wang. "Research on master-slave filtering of Celestial Navigation System / Inertial Navigation System." Journal of Physics: Conference Series 1732 (January 2021): 012189. http://dx.doi.org/10.1088/1742-6596/1732/1/012189.

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43

Pintér, Tomáš, and Pavol Božek. "Industrial Robot Control Using Inertial Navigation System." Advanced Materials Research 605-607 (December 2012): 1600–1604. http://dx.doi.org/10.4028/www.scientific.net/amr.605-607.1600.

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The paper deals with constructing the inertial navigation system (hereafter INS) which will be utilized for the calibration of a robotic workplace. The calibration is necessary for adapting the simulation of a production device model to real geometric conditions. The goal is to verify experimentally the proposed inertial navigation system in real conditions of the industrial robot operation.
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44

Zhang, Xiaoyue, Haitao Shi, Jianye Pan, and Chunxi Zhang. "Integrated navigation method based on inertial navigation system and Lidar." Optical Engineering 55, no. 4 (April 12, 2016): 044102. http://dx.doi.org/10.1117/1.oe.55.4.044102.

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45

Xu, Bo, Dan Dan Wang, and Zhen Sheng Cheng. "Error Modeling and Simulation Analysis for the Vehicle Launching System Erecting." Advanced Materials Research 566 (September 2012): 680–84. http://dx.doi.org/10.4028/www.scientific.net/amr.566.680.

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Horizontal collimation is the development tendency of the vehicle launching system. During the erect process, the launching system's navigation precision depends on the strap-down inertial navigation system calculation on the launch carrier. So the analysis of every inertial component's error which produces in the inertial navigation process is very necessary. This paper sets the model of the whole erect process, including the launch of the erect drive, the scaling factor,and zero position and installation error of the inertial components. It analyzes the various factors influence on the navigation precision in detail. It provides a good simulation basis and design basis for the error distribution and precision analysis of horizontal collimation technology. And it also provides analysis results for its application and extension, plan making, precision evaluation.
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46

Rahimi, Hossein, and Amir Ali Nikkhah. "Improving the speed of initial alignment for marine strapdown inertial navigation systems using heading control signal feedback in extended Kalman filter." International Journal of Advanced Robotic Systems 17, no. 1 (January 1, 2020): 172988141989484. http://dx.doi.org/10.1177/1729881419894849.

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In this article, a method was proposed for strapdown inertial navigation systems initial alignment by drawing on the conventional alignment method for stable platform navigation systems. When a vessel is moored, the strapdown inertial navigation system contributes to the disturbing motion. Moreover, the conventional methods of accurate alignment fail to succeed within an acceptable period of time due to the slow convergence of the heading channel in the mooring conditions. In this work, the heading was adjusted using the velocity bias resulting from the component of the angular velocity of the Earth on the east channel on the strapdown inertial navigation systems analytic platform plane to accelerate convergence in the initial alignment of navigation system. To this end, an extended Kalman filter with control signal feedback was used. The heading error was calculated using the north channel residual velocity of the strapdown inertial navigation systems analytic platform plane and was entered into an extended Kalman filter. Simulation and turntable experimental tests were indicative of the ability of the proposed alignment method to increase heading converge speed in mooring conditions.
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47

Wei, Yong Sen. "The Design of Vehicle Integrated Navigation System Based on FPGA." Advanced Materials Research 442 (January 2012): 441–45. http://dx.doi.org/10.4028/www.scientific.net/amr.442.441.

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A GPS/inertial navigation system design scheme is introduced. Combination of DSP and FPGA is used on the navigation board, and micro inertial navigation measuring element --ADIS16405 is used to sample required navigation data. DSP mainly implements navigation calculating based on navigation data, and realizes different navigation algorithms; FPGA in the system plays centeral control role, and not only samples IMU and GPS data, but also synchronize IMU and GPS in the real time, and preprocess and packet the navigation data. This paper also introduces the design of the software on FPGA. Practice proves that the scheme is feasible, and achieves the good balance between the cost, reliability and efficiency.
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48

Larin, Vladimir B., and Anatoliy A. Tunik. "On Correcting the System of Inertial Navigation." Journal of Automation and Information Sciences 42, no. 8 (2010): 13–26. http://dx.doi.org/10.1615/jautomatinfscien.v42.i8.20.

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49

Zhuravlev, V. Ph. "Strapdown inertial navigation system of pendulum type." Mechanics of Solids 49, no. 1 (January 2014): 1–10. http://dx.doi.org/10.3103/s0025654414010014.

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50

Munoz Diaz, Estefania. "Inertial Pocket Navigation System: Unaided 3D Positioning." Sensors 15, no. 4 (April 17, 2015): 9156–78. http://dx.doi.org/10.3390/s150409156.

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