The Integrated Inertial Navigation System AN/ASN-132

Integration of inertial navigation system (INS) and global navigation satellite system (GNSS) is usually implemented in engineering applications by way of Kalman-like filtering. This form of INS/GNSS integration is prone to attitude initialization failure, especially when the host vehicle is moving freely. This paper proposes an online constrained-optimization method to simultaneously estimate the attitude and other related parameters including GNSS antenna's lever arm and inertial sensor biases. This new technique benefits from self-initialization in which no prior attitude or sensor measurement noise information is required. Numerical results are reported to validate its effectiveness and prospect in high accurate INS/GNSS applications.

In the integrated inertial navigation system (INS) and celestial navigation system (CNS), the attitudes and positions of probes are estimated based on the auxiliary measurement of an infrared Earth sensor. The poor accuracy of the infrared Earth sensor compared to that of the star sensor significantly limits the navigation accuracy of the integrated navigation system. This paper proposes a novel INS/CNS integrated navigation system that uses the specific force with noncumulative error to correct infrared Earth measurements. The probe azimuth angle and elevation angle relative to the Earth's inertial frame are first estimated according to the specific force provided by the INS to filter the infrared Earth sensor's measurement error. Then, the corrected infrared Earth measurement assists the CNS to obtain accurate celestial measurements. The integrated INS/CNS navigation system in the tightly coupled mode finally estimates the accurate probe attitude and position. Compared to the integrated navigation system, which directly uses the uncorrected infrared Earth measurement, the yaw, pitch, and roll angle are improved under the proposed method by 76.73%, 77.64%, and 75.39% on average, respectively; the latitude and longitude estimation errors improve under the proposed method by 70.44% and 61.92% on average, respectively. In short, the proposed method is a feasible and highly accurate approach to the INS/CNS integrated navigation system.

The Kalman filter is an optimal state estimator used in many of the engineering applications. In general, Kalman filter has two typical forms for non-linear estimation they are, the extended Kalman filter and unscented Kalman filter. This paper discusses the implementation of GPS-based Inertial navigation system (a combination of accelerometers and gyroscopes) using an extended Kalman filter (EKF). Both GPS and INS sensors are used to update the position and velocity in a land vehicle so that real time guidance and navigation tasks are performed. Due to the low sampling rate of GPS, continuous and reliable position cannot be obtained regularly. Similarly, the INS output tends to accumulate error over time which makes it unreliable. These limitations are overcome by integrating these systems due to their complementary characteristics in order to achieve long term accuracy. The method discussed involves collecting the data from GPS and INS sensors and processing them using EKF to obtain better estimates on the position and velocity. The vehicle orientation is linearized using the quaternion in the prediction and correction stages of EKF.

Self-localization is a basic service for Intelligent Transportation Systems (ITS) such as traffic regulation services. Most of the used techniques are based on integration of Inertial Navigation System (INS) and Global Positioning System (GPS). However, navigation through areas such as tunnels, where GPS coverage is vulnerable, obliges the use of a different approach. Based on this observation, we designed and implemented a lightweight cooperative positioning algorithm based on Adaptive Localization Protocol (ALP). In this paper, we apply our method as support to an intersection service for traffic regulation, in which a group of concurrent cars shares an intersection/critical section. We found that our algorithm improves car position and regulates the traffic.

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.

Based on analyzing current independent navigation methods, this paper presents a new underwater navigation system, which is integrated inertial navigation system (INS) and side scan sonar (SSS). Firstly we introduce the component of the underwater navigation system and the functions of each unit in the system. Then, we study the algorithm of the matching navigation used in the system. A fast image match method by integrating wavelet transform and improved sequential similarity detection algorithm (SSDA) is given out. Based on above researches, we implement simulation experiments. Experimental results show that the system presented in this paper can acquire high navigation accuracy under the background with characteristic seabed relief. Finally, some valuable conclusions and suggestions are given.

In a traditional integrated inertial navigation system (INS) and celestial navigation system (CNS) setup, measurements from both systems are only fused at the data output phase. Navigation ...

With the development of the intelligent vehicle navigation systems and vehicle networking systems, vehicle positioning and state estimation become very important. This paper investigates the integration of Global Positioning System (GPS), Inertial Navigation System (INS) and Dead Reckoning based on Anti-lock Braking System (ABSDR) positioning based on Kalman filter, and aims at achieving full-time vehicle positioning. In this paper, we use Kalman Filter to estimate INS positioning error based on GPS or ABSDR solution, take the INS solution compensated with estimated error as system output. This paper introduces INS positioning algorithm, dead reckoning method based on the ABS wheel speed and Kalman filtering method. After that, simulation analysis and experimental verification of the positioning algorithm are carried out. The results show that the system output high-precision high-frequency positioning information when GPS is available, and when GPS is unavailable, INS positioning errors can be compensated well with ABSDR introduced, achieving the full-time positioning of the vehicle.

In this paper, we present the requirements specification to develop the small ring laser gyroscope(RLG) which is applicable to the medium-grade inertial navigation system(INS) widely used as a main navigation system. To this end, first we analyse the performance specifications of RLG which is needed to configure the medium-grade INS and then we present the design results of RLG to meet the performance specifications, based on the overseas technology survey and the theoretical analysis. It is also shown in this paper what technology is required to develop a small RLC.

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.

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.

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.

A novel intelligent adaptive Kalman Filter for estimating the Submarine's velocity: With experimental evaluation

Navigation includes the integration of methodologies and systems for estimating time-varying position, velocity and attitude of moving objects. Navigation incorporating the integrated inertial navigation system (INS) and global positioning system (GPS) generally requires extensive evaluations of nonlinear equations involving double integration. Currently, integrated navigation systems are commonly implemented using the extended Kalman filter (EKF). The EKF assumes a linearized process, measurement models and Gaussian noise distributions. These assumptions are unrealistic for highly nonlinear systems like land vehicle navigation and may cause filter divergence. A particle filter (PF) is developed to enhance integrated INS/GPS system performance as it can easily deal with nonlinearity and non-Gaussian noises. In this paper, a hybrid extended particle filter (HEPF) is developed as an alternative to the well-known EKF to achieve better navigation data accuracy for low-cost microelectromechanical system sensors. The results show that the HEPF performs better than the EKF during GPS outages, especially when simulated outages are located in periods with high vehicle dynamics.