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Hot spot of invention : Charles Stark Draper, MIT, and the development of inertial guidance and navigation
\"Charles Stark Draper, often referred to as 'The Father of Inertial Navigation,' was the moving force behind the development of the floated gyroscope in the United States. He was an engineer, a scientist, and an inventor; an inspiring teacher; and a dynamic leader responsible for creating the laboratory that brought inertial navigation to fruition for operational use in submarines, aircraft, and space vehicles. Draper also created and ran the famous laboratory, now bearing his name, that helped make MIT into one of the nation's leading research centers for government research. The story of Draper's life and his accomplishments cannot be separated from those of the Instrumentation Laboratory, which are one and the same. Thus, this biography of Charles Stark 'Doc' Draper, is also a chronological accounting of the MIT Instrumentation Laboratory and its contributions to the nation\"-- Provided by publisher.
Book
A Combination Scheme of Pure Strapdown and Dual-Axis Rotation Inertial Navigation Systems
Compared with the strapdown inertial navigation system (SINS), the rotation strapdown inertial navigation system (RSINS) can effectively improve the accuracy of navigation information, but rotational modulation also leads to an increase in the oscillation frequency of attitude errors. In this paper, a dual-inertial navigation scheme that combines the strapdown inertial navigation system and the dual-axis rotation inertial navigation system is proposed, which can effectively improve the attitude error accuracy in the horizontal direction by using the high-position information of the rotation inertial navigation system and the stability characteristics of the attitude error of the strapdown inertial navigation system. Firstly, the error characteristics of the strapdown inertial navigation system and the rotation strapdown inertial navigation system are analyzed, and then the combination scheme and Kalman filter are designed according to the error characteristics, and finally, the simulation experiment shows that the pitch angle error of the dual inertial navigation system is reduced by more than 35% and the roll angle error is reduced by more than 45% compared with the rotation strapdown inertial navigation system. Therefore, the combination scheme of double inertial navigation proposed in this paper can further reduce the attitude error of the rotation strapdown inertial navigation system, and at the same time, the two sets of inertial navigation systems can also enhance the reliability of ship navigation.
Journal Article
Effect Analysis of GNSS/INS Processing Strategy for Sufficient Utilization of Urban Environment Observations
The occlusion of buildings in urban environments leads to the intermittent reception of satellite signals, which limits the utilization of observations. This subsequently results in a decline of the positioning and attitude accuracy of Global Navigation Satellite System (GNSS)/Inertial Navigation System (INS) integrated system (GNSS/INS). This study implements a smooth post-processing strategy based on a tightly coupled differential GNSS/INS. Specifically, this strategy used the INS-estimated position to reinitialize integer ambiguity. The GNSS raw observations were input into the Kalman filter to update the measurement. The Rauch–Tung–Striebel smoothing (RTSS) algorithm was used to process the observations of the entire period. This study analyzed the performance of loosely coupled and tightly coupled systems in an urban environment and the improvement of the RTSS algorithm on the navigation solution from the perspective of fully mining the observations. The experimental results of the simulation data and real data show that, compared with the traditional tightly coupled processing strategy which does not use INS-aided integer ambiguity resolution and RTSS algorithm, the strategy in this study sufficiently utilized INS observations and GNSS observations to effectively improve the accuracy of positioning and attitude and ensure the continuity of navigation results in an obstructed environment.
Journal Article
An Enhanced, Real-Time, Low-Cost GNSS/INS Integrated Navigation Algorithm and Its Platform Design
The integration of the global navigation satellite system (GNSS) and the inertial navigation system (INS) is a well-established method for achieving accurate positioning, especially in applications involving unmanned aerial vehicles (UAVs). UAVs are increasingly used across various fields, yet they face challenges such as the need for real-time processing and the impact of low-quality measurements from cost-effective devices. To address these challenges, we propose a velocity-constrained, enhanced, real-time, low-cost, GNSS/INS integrated navigation algorithm and design an algorithmic platform based on the open-source software KF_GINS. The algorithm supports loosely coupled integration of GNSS position data and raw inertial measurement unit (IMU) data, utilizing a 4G data transmission unit (DTU) for real-time data transmission and performing loosely coupled computations on the received data. Subsequently, we successfully applied this algorithm to low-cost integrated navigation devices, such as UAVs. We tested the algorithm platform using one set of vehicle-mounted data and six UAV datasets. Experimental results indicate that the algorithm platform effectively performs computations under various conditions, improving single-point positioning (SPP) accuracy by up to 15.38% horizontally and 6.78% vertically. These findings demonstrate the algorithm platform’s capability to significantly enhance the accuracy and stability of integrated navigation positioning for UAVs.
Journal Article
Study on the Robust Filter Method of SINS/DVL Integrated Navigation Systems in a Complex Underwater Environment
This paper proposes an improved adaptive filtering algorithm based on the Sage–Husa adaptive Kalman filtering algorithm to address the issue of measurement noise characteristics impacting the navigation accuracy in strapdown inertial navigation system (SINS)/Doppler Velocity Log (DVL) integrated navigation systems. Addressing the non-positive definite matrix problem prevalent in traditional adaptive filtering algorithms and aiming to enhance measurement noise estimation accuracy, this method incorporates upper and lower thresholds determined by a discrimination factor. In the presence of abnormal measurement data, these thresholds are utilized to adjust the covariance of the innovation, subsequently re-estimating the system’s measurement noise through a decision factor based on the innovation. Simulation and experiment results demonstrate that the proposed improved adaptive filtering algorithm outperforms the classical Kalman filter (KF) in terms of navigation accuracy and stability. Furthermore, the filtering performance surpasses that of the Sage–Husa algorithm. The simulation results in this paper show that the relative position positioning error of the improved method is reduced by 49.44% compared with the Sage–Husa filtering method.
Journal Article
Stationary Detection for Zero Velocity Update of IMU Based on the Vibrational FFT Feature of Land Vehicle
The inertial navigation system (INS) and global satellite navigation system (GNSS) are two of the most significant systems for land navigation applications. The inertial measurement unit (IMU) is a kind of INS sensor that measures three-dimensional acceleration and angular velocity measurements. IMUs based on micro-electromechanical systems (MEMSs) are widely employed in vehicular navigation thanks to their low cost and small size, but their magnitude and noisy biases make navigation errors diverge very fast without external constraint. The zero-velocity update (ZVU) function is one of the efficient functions that constrain the divergence of IMUs for a stopped vehicle, and the key of the ZVU is the correct stationary detection for the vehicle. When a land vehicle is stopped, the idling engine produces a very stable vibration, which allows us to perform frequency analysis and a comparison based on the fast Fourier transform (FFT) and IMU measurements. Hence, we propose a stationary detection method based on the FFT for a stopped land vehicle with an idling engine in this study. An urban vehicular navigation experiment was carried out with our GNSS/IMU integration platform. Three stops for 10 to 20 min were set to analyze, generate and evaluate the FFT-based stationary detection method. The FFT spectra showed clearly idling vibrational peaks during the three stop periods. Through the comparison of FFT spectral features with decelerating and accelerating periods, the amplitudes of vibrational peaks were put forward as the key factors of stationary detection. For the consecutive stationary detection in the GNSS/IMU integration process, a three-second sliding window with a one-second updating rate of the FFT was applied to check the amplitudes of peaks. For the assessment of the proposed stationary detection method, GNSS observations were removed to simulate outages during the three stop periods, and the proposed detection method was conducted together with the ZVU. The results showed that the proposed method achieved a 99.7% correct detection rate, and the divergence of the positioning error constrained via the ZVU was within 2 cm for the experimental stop periods, which indicates the effectiveness of the proposed method.
Journal Article
An Angle-Dependent Bias Compensation Method for Hemispherical Resonator Gyro Inertial Navigation Systems
In the whole-angle mode of a hemispherical resonator gyro (HRG), the external input rotation angle is obtained by detecting the standing-wave rotation angle through electrodes. Due to this operational principle and manufacturing constraints of HRGs, the gyro output in an HRG inertial navigation system exhibits angle-dependent errors that are highly sensitive to temperature variations. To address this issue, this paper proposes a system-level calibration scheme to characterize and compensate for these correlated errors. Angle-dependent bias models were established through multi-temperature point experiments. A Kalman filter was subsequently designed, and a calibration path satisfying observability requirements was developed. System-level calibration experiments were conducted to determine and compensate for the identified errors. Finally, navigation experiments demonstrated the effectiveness of the proposed method, showing that the navigation accuracy of the HRG inertial navigation system was improved by up to 94.35%.
Journal Article
A Comprehensive Error Modeling and On-Field Calibration Method for HRG SINS by Tumbling the Hexahedron
On-field calibration for SINS often uses right hexahedron, but the influence of the structure errors, such as mutual position tolerances towards parallelism or the perpendicularity of two arbitrary planes of the hexahedron, on the calibration accuracy is often neglected. In this paper, a hexahedron structure error model and a comprehensive corresponding SINS calibration error model are developed based on hemispherical resonator gyroscope (HRGs). The proposed method introduces the comprehensive hexahedron errors through defining the normal vectors of the exterior surfaces of the hexahedron. A 24-position calibration scheme is designed to identify accelerometer-related errors, while a 48-rotation scheme is developed to identify gyro-related errors. The complete calibration procedure enables simultaneous identification of hexahedron structure errors, installation misalignments, scale factor errors, and biases. Experimental validation is conducted using a high-precision three-axis turntable, which simulates the hexahedron structure errors. The results show that the proposed method significantly improves the calibration accuracy of both accelerometers and HRGs compared with traditional methods. Furthermore, it reduces the accuracy requirements for the hexahedron structure, thus lowering the cost of SINS on-field calibration.
Journal Article
Principles of GNSS, Inertial, and Multisensor Integrated Navigation Systems
Navigation systems engineering is a red-hot area. More and more technical professionals are entering the field and looking for practical, up-to-date engineering know-how. This single-source reference answers the call, providing both an introduction to overall systems operation and an in-depth treatment of architecture, design, and component integration. This book explains how satellite, on-board, and other navigation technologies operate, and it gives practitioners insight into performance issues such as processing chains and error sources. Providing solutions to systems designers and engineers, the book describes and compares different integration architectures, and explains how to diagnose errors. Moreover, this hands-on book includes appendices filled with terminology and equations for quick referencing.
eBook
Analysis of Gyro Bias Depending on the Position of Inertial Measurement Unit in Rotational Inertial Navigation Systems
In this paper, a calibration method for gyro bias that changes depending on the position of the IMU (inertial measurement unit) is proposed to improve the navigation performance of RLG-based RINS (ring-laser-gyro-based rotational inertial navigation system). RINS is a navigation device that compensates for the inertial sensor errors by utilizing the rotation of the IMU. In previous studies, the rotation scheme of the IMU is designed assuming that inertial sensor errors are not affected by position of the IMU. However, changes in temperature distribution, direction of gravity, and dithering according to the rotation of the IMU affect the inertial sensor errors, such as gyro bias. These errors could degrade the long-term navigation performance of RLG-based RINS. To deal with this problem, this paper proposed a compensation method of the gyro bias that changes depending on the position of the IMU. First, RINS is reviewed using a dual-axis 16-position rotation scheme and RLG. Next, the attitude error of RLG-based RINS is derived utilizing navigation equations. The effect of the gyro bias change caused by the change in the IMU attitude for the navigation performance of RINS is analyzed based on navigation equations and simulations. Finally, system-level indirect calibrations for the Z–axis up position and Z–axis down position are performed to calculate the gyro bias change caused by the IMU attitude. The accuracy of the proposed calibration method is verified by long-term navigation test. The test results show that the proposed calibration method improves the navigation performance of RINS compared with the conventional calibration method.
Journal Article