중급성능의 관성항법을 위한 소형 링레이저 자이로 설계 규격 연구

The US Army has a requirement for a highly accurate inertial/TACAN hybrid navigation system. This paper describes the navigation system architecture developed to meet this requirement, the specific hardware selected and the development status. At the beginning of the Integrated Inertial Navigation System (IINS) development program it was anticipated that significant technological advances would take place in its life cycle. In addition, mission requirements were expected to change as the system evolved. Particular attention was therefore given to the IINS system architecture, specifically the partitioning of hardware and software functions as well as the means of data transmittal between the subsystem elements. The paper describes in detail the design trade-offs made as well as hardware selections. The system is configured using several different manufacturers' equipment making the data interface and its configuration control of great importance. The above considerations lead to the conclusion that the appropriate data bus interface standard would be MIL-STD-1553. This interface standard not only facilitates configuration control during system development, but will allow rapid integration with future aircraft systems that will use it as a primary means of data transmittal. The paper describes in detail the signal interface between the subsystem element, onboard mission equipment and flight instruments. The most significant change anticipated in the course of the IINS life cycle is the substitution of Global Positioning System User Equipment for the external update function currently provided by TACAN. Another area where technology insertion may be deemed appropriate is the substitution of a strapdown inertial navigation unit (INU) employing ring laser gyros (RLG) for the currently employed conventional gimballed INU. The INU employed in the IINS is built to a form, fit and function specification, which will allow substitution of a RLG INU when such a unit is qualified and in production. The system hardware and software is structured so that these changes can be accomplished with a minimum of effort. The paper also describes the federated processing structure which allows this flexibility with particular attention to the inertial/TACAN update algorithm and data bus control functions. The paper concludes with a brief summary of the development status of the IINS, currently in full scale engineering development.

In modern aerospace technology, strapdown inertial navigation systems (SINS) are widely used, using fiber-optic (FOG) or ring laser (CLG) gyroscopes. During the operation of such systems, the sensitivity axes are rotated relative to the basic coordinate system. The resulting angles between the axes of the base coordinate system and the axes of sensitivity of the navigation system (non-orthogonality) are one of the factors leading to an increase in the measurement errors of the device, which affects the measurement accuracy. During operation, the system is affected by vibrations of various nature, the impact of which can contribute to the appearance of non-orthogonality. The purpose of this work is to determine the maximum permissible vibration amplitudes affecting the SINS body according to the permissible values ​​of the deviation of the FOG sensitivity axes for two variants of the SINS layout. An approach to determining the permissible amplitudes of an external harmonic impact on the unit of a strapdown inertial navigation system based on fiber-optic or ring laser gyroscopes is considered. A design scheme, mathematical and finite element models for calculating natural frequencies and forced oscillations of a strapdown inertial navigation system unit have been developed. In various frequency ranges, numerical calculations have determined the boundary values ​​of the amplitudes of the external harmonic impact on the base of specific configurations of the SINS assembly. It has been established that dangerous states take place in the region of the 1st natural frequency of the system, as well as near higher frequencies. Comparison of the results for design options 1 and 2 allows us to conclude that in order to weaken the effect of vibrations on the accuracy of the SINS unit, it is advisable that the lowest natural vibration frequencies for the SINS assembly be as high as possible (more than 1000 Hz).
 Key words: vibration; fiber optic gyroscope; strapdown inertial navigation system; finite element method; natural frequencies and modes of vibration.

Suppression of the G-sensitive drift of laser gyro in dual-axis rotational inertial navigation system

A 5 inch diameter high accuracy borehole surveying instrument has been developed using a full 3 axis inertial navigation system (INS). It has the following features: 3 Ring Laser GyrosNo mechanical gimbalsReal-time surface readoutObtains position data directly without the need for intermediate depths stops.Requires no stopping for drift checksUses wireline velocities up to 600 ft/minReduces INS's typical drift error to less than 6 ft/hr. This tool achieves a survey accuracy that is close to that of the 10" INS tool, while at the same time offering a smaller diameter and continuous survey capability.

Integration of Global Positioning System (GPS) and Inertial Navigation System (INS) are very practical method to get high precision navigation. GPS/INS data Fusion in navigation has been a research topic for decades. Usually the update time of GPS an INS is different. The update time of GPS is 20HZ, and the time of INS is 100HZ or higher. Since GPS and INS are mainly methods in navigation system. Techniques of fusing GPS and INS data are in high demand in navigation industry. Usually the Karman filter is used to fuse the data from GPS and INS. But the Kalman filter is model-dependent and a priori the model parameters need to be known. In this work, a generic and intelligent approach of GPS and INS data fuse using fuzzy interpolation before Kalman algorithm is proposed. First a simplified interpolation model is introduced in a ordinary GPS and INS data fusion. Second a fuzzy rule-based system is established to fuzzy interpolation with objective fuzzy method. Then the parameters of objective fuzzy system are identified, the best n-rule is determinate and the optimal rule base system is found. Finally this approach is applied on an example for a car GPS and INS data fusion, and the results are calculated with computer system to demonstrate the advantages of this approach.

Inertial navigation system has been the core component of both military and civil navigation systems. Before the INS is put into application, it is supposed to be calibrated in the laboratory in order to compensate repeatability error caused by manufacturing. Discrete calibration method cannot fulfill requirements of high-accurate calibration of the mechanically dithered ring laser gyroscope navigation system with shock absorbers. This paper has analyzed theories of error inspiration and separation in detail and presented a new systematic calibration method for ring laser gyroscope inertial navigation system. Error models and equations of calibrated Inertial Measurement Unit are given. Then proper rotation arrangement orders are depicted in order to establish the linear relationships between the change of velocity errors and calibrated parameter errors. Experiments have been set up to compare the systematic errors calculated by filtering calibration result with those obtained by discrete calibration result. The largest position error and velocity error of filtering calibration result are only 0.18 miles and 0.26m/s compared with 2 miles and 1.46m/s of discrete calibration result. These results have validated the new systematic calibration method and proved its importance for optimal design and accuracy improvement of calibration of mechanically dithered ring laser gyroscope inertial navigation system.

GNSS observation outage occurs inevitably in various situations, e.g., automobile driving in urban environments. Although the ambiguity resolution (AR) significantly shortens the initialization time of precise point positioning (PPP), frequent re-initialization of PPP AR may be needed due to outages. The inertial navigation system (INS) can be used for acquiring highly accurate position information during GNSS outages. In the previous studies, the GPS PPP/INS with the ambiguity resolution model is proposed, and the experimental results confirm that the INS could facilitate the re-fixing of the interrupted GNSS ambiguity. Multiple GNSS can also be used to shorten the PPP convergence time. We compare the contribution of multi-GNSS and the INS to the ambiguity re-fixing during GNSS outage. Results show that the multi-GNSS, e.g., Galileo, GLONASS and BDS, without ambiguity resolution has little contribution to the re-fixing of GPS ambiguity in PPP/INS, while INS can provide highly accurate positioning results during the GNSS outages. The higher the accuracy of the predicted INS positioning, the lower the contribution of multi-GNSS to the re-fixing of the ambiguity in the PPP/INS. The finding is verified by a theoretical analysis, carborne experiment and shipborne experiment. Experiment results show that the re-fixing time is 43 s for GPS PPP and MEMS-grade INS coupled system in GNSS outage of 1 s. The re-fixing time of GPS is slightly changed when adding the multi-GNSS, e.g., Galileo, GLONASS and BDS, without the ambiguity resolution. However, by performing ambiguity resolution to the added GNSS system, the re-fixing time of PPP/INS is significantly reduced from 43 to 4 s. The reason is that, although the multi-GNSS provides little improvement on the accuracy of the ambiguity, it enlarges the number of the ambiguity parameter. The possibility of ambiguity resolution is increased due to the large candidate set of the ambiguity, which reduces re-fixing time.

The medium accuracy standard ring laser gyro (RLG) inertial navigation unit (INU) exemplified by Litton's LN-93 system has benefited from continual improvements during the production process such that the present navigational accuracy and reliability are better by a factor of two or more over the original requirements as defined by SNU 84-1. Performance enhancements are now available which further improve navigation performance to the high-accuracy category while maintaining the reliability of the production system. Two enhancement mechanizations are described-one that requires software-only changes to improve inertial performance, and one that employs a self-contained (embedded) GPS to augment the inertial performance. These enhancements may be applied in combination to provide uniquely effective immunity to GPS spoofing countermeasures. These enhancements retain the present standard RLG INU form factor, mounting, and electrical interface, and are therefore particularly advantageous for retrofit application. Potential retrofit applications with various aircraft avionics architectures are discussed. >

How to achieve continuous, reliable and accurate positioning performance using low-cost sensors is one of the main challenges for aviation navigation system. Global Positioning System (GPS) can provide the primary means of navigation in a number of aviation navigation applications (e.g., manned and unmanned aircraft vehicle, airport ground vehicle). However, GPS signal deteriorations typically occur due to aircraft itself during maneuvering, ionospheric scintillation, Doppler shift, multipath and so on. Thus, there is a need to research GPS augmentation strategies which can be used in the Communication, Navigation, Surveillance/Air Traffic Management. GPS integration with Inertial Navigation system (INS) is one of the key strategies. But once GPS signal outages, the integrated navigation system works in pure INS, and positioning accuracy deteriorates with time. When using low cost GPS/INS integration, a primary problem is the rapid performance deteriorate during GPS outages. To provide continuous, accurate and reliable positioning information in aviation, discrete grey prediction model (DGPM) aided fusion methodology is proposed. The DGPM provides pseudo-GPS position information for INS during GPS outages. The mathematical model of integrated navigation system is established, including INS error equations, Kalman filter and DGPM. The model works in the update mode when there is no GPS failure, whereas it switches to the prediction mode in case of GPS outages. To verify the feasibility and effectiveness of the proposed methodology, real road test is performed. The comparison results show that accuracy of longitude and latitude are improved by more than 80% and 70%, respectively. The DGPM can effectively provide position corrections for standalone INS during GPS outages.

Although a USV navigation system is an important application of unmanned systems, combining Inertial Navigation System (INS) with Global Positioning System (GPS) can provide reliable and continuous solutions of positioning and navigation based on its several advantages; the random error characteristics of INS and the instability derived from the GPS signal blockage represent a potential threat to the INS/GPS integration of USV. Under this background, a composition framework based on nonlinear generalization capability of support vector machines (SVM) and multi-resolution ability of wavelet transform is used to solve the difficulty that the INS suffers from the interference of stochastic errors, and the dynamic information of the USV is not influenced. An innovative fuzzy broad learning structure based on the broad learning (BL) method is utilized in the INS/GPS integration of USV, in which the navigation information of INS and GPS are deemed as the input of the Fuzzy Broad Learning System (FBLS) to train the network, and then the trained network of FBLS and navigation information of INS are applied for estimating the optimal navigation solution during the GPS signal blockage. Based on the USV platform, a sea trial was carried out to confirm the validity and feasibility of the proposed method by comparing with existing algorithms for INS/GPS integration. The experimental results show that the proposed approach could achieve the better denoising effect from random errors of INS and provide high-accuracy navigation solutions during GPS signal blockage.

Inertial navigation provides a unique ability to know where one has been, where one is currently, and where one is going, given only a starting position. The laws of physics permit the sensing of dynamic motion without external information, making inertial systems impervious to jamming, masking, or spoofing. Measurements of six degrees of freedom are required - three linear accelerations, and three angular rates - to fully propagate the velocity, position, and orientation of the system. The first inertial sensors are traced to the early 19th century and specialized inertial guidance systems appeared in the 1940s, yet inertial navigation systems did not become commonplace until the 1960s. This is largely due to the fact that requirements for navigation accuracy inertial sensors - accelerometers and gyroscopes - are very challenging. In the past fifty years, significant evolutionary and revolutionary changes have taken place in the designs of inertial sensors and systems. These include the progression from fluid-filled to dry instruments and the transition from mechanically complex stabilized inertial platforms to computationally intensive strapdown systems. Gyroscopes have evolved from large mechanical devices to highly refined precision mechanical sensors. Optical rotation sensors such as the ring laser gyro and the fiber optic gyro have enabled new system designs and capabilities. Coriolis vibratory gyroscopes such as the hemispherical resonator gyro are capable of extreme accuracy and reliability; new opportunities for miniaturizing these types of sensors will lead to new classes of accuracy for inertial navigation systems. Advanced gyroscope technologies such as the nuclear magnetic resonance gyroscope which uses atomic spin to detect rotation have already been demonstrated to achieve navigation accuracy requirements. Cold atom technologies may also provide the opportunity for very high accuracy accelerometers and gyroscopes in the future. Inertial navigation technologies and applications of the past, present, and future are discussed.

We describe an integrated navigation system based on Global Navigation Satellite Systems (GNSS), an Inertial Navigation System (INS) and terrestrial ranging technologies that can support accurate and seamless indoor-outdoor positioning. To overcome severe multipath disturbance in indoor environments, Locata technology is used in this navigation system. Such a “Locata-augmented” navigation system can operate in different positioning modes in both indoor and outdoor environments. In environments where GNSS is unavailable, e.g. indoors, the proposed system is designed to operate in the Locata/INS “loosely-integrated” mode. On the other hand, in outdoor environments, all GNSS, Locata and INS measurements are available, and all useful information can be fused via a decentralised Federated Kalman filter. To evaluate the proposed system for seamless indoor-outdoor positioning, an indoor-outdoor test was conducted at a metal-clad warehouse. The test results confirmed that the proposed navigation system can provide continuous and reliable position and attitude solutions, with the positioning accuracy being better than five centimetres.

Global Positioning System and Inertial Navigation System can be used to determine position and velocity. A Global Positioning System module is able to accurately determine position without sensor drift, but its usage is limited in heavily urbanized environments and heavy vegetation. While high-cost tactical-grade Inertial Navigation System can determine position accurately, low-cost micro-electro-mechanical system Inertial Navigation System sensors are plagued by significant errors. Global Positioning System is coupled with Inertial Navigation System to correct the errors, while Inertial Navigation System itself can be used to provide navigation solution during a Global Positioning System outage. Data from Global Positioning System and Inertial Navigation System can be integrated by extensive Kalman filtering, using loosely coupled integration architecture to provide navigation solutions. In this study, real-time low-cost loosely coupled micro-electro-mechanical system Inertial Navigation System/Global Positioning System sensors have been used for pedestrian navigation. Trial runs of Global Positioning System outages have been conducted to determine the accuracy of the system described. The micro-electro-mechanical system Inertial Navigation System/Global Positioning System can successfully project a trajectory during a Global Positioning System outage and produces a root mean square error of 9.35 m in latitude direction and 10.8 m in longitude direction. This technology is very suitable for visually impaired pedestrians.

Navigation in total hip arthroplasty has been shown to improve acetabular positioning and can decrease the incidence of mal-positioned acetabular components. This study aimed to assess two surgical guidance systems by comparing intra-operative measurements of acetabular component inclination and anteversion with a post-operative CT scan. We prospectively collected intra-operative navigation data from 102 hips receiving conventional THA or hip resurfacing arthroplasty through either a direct anterior or posterior approach. Two guidance systems were used simultaneously: an inertial navigation system (INS) and an optical navigation system (ONS). Acetabular component anteversion and inclination were measured on a post-operative CT. The average age of the patients was 64years (range: 24-92) and the average BMI was 27kg/m2 (range 19-38). 52% had hip surgery through an anterior approach. 98% of the INS measurements and 88% of the ONS measurements were within 10° of the CT measurements. The mean (and standard deviation) of the absolute difference between the postoperative CT and the intra-operative measurements for inclination and anteversion were 3.0° (2.8) and 4.5° (3.2) respectively for the ONS, along with 2.1° (2.3) and 2.4° (2.1) respectively for the INS. There was a significantly lower mean absolute difference to CT for the INS when compared to ONS in both anteversions (p<0.001) and inclination (p=0.02). We found that both inertial and optical navigation systems allowed for adequate acetabular positioning as measured on postoperative CT, and thus provide reliable intraoperative feedback for optimal acetabular component placement. Therapeutic Level II.

In present days, real time navigation depends on Kalman filter to fuse data from Global Positioning System (GPS) and Inertial Navigation System (INS). But there exist drawbacks like long design time, requirement of prior knowledge in fusing data from GPS and INS using Kalman Filter. In order to overcome the drawbacks of Kalman filter, GPS and INS integration are done using Artificial Neural Networks (ANN) like FFNNs. But still there exists certain drawbacks like less accuracy in FFNNs for GPS and INS data integration. Therefore, this paper introduces Higher Order Neural Networks (HONNs) approach for INS and GPS data integration to overcome the drawback. A higher order feed forward neural network architecture with optimum number of nodes is used. In the given architectures, the replacement of summation at each node by multiplication results in more powerful mapping, because of its capability of processing higher-order information from training data. Performance comparison of HONNs with FFNNs shows that the proposed architecture provides satisfactory results in terms of error rate and number of epochs. The HONNs like Multiplicative Neural Network (MNN) module and Sigma-Pi-ANN module and Traditional Feed Forward Neural Networks(FFNNs) like Radial Basis Function Neural Network (RBF) module and Back propagation Neural Network (BPN) module are trained to predict the INS position error and provide accurate position of the moving aircrafts. Sigma-Pi ANN is found to be the best in terms of accuracy, number of epochs and execution time among the two HONNs.