Accuracy Of Inertial Navigation System Research Articles

Performance improvement and study of the space-oriented strapdown inertial navigation system

The inertial navigation system (INS) has been playing a prominent role in space navigation applications. However, the selected order of conventional integration schemes limits the computational accuracy of the strapdown INS (SINS) and its availability during different mission phases of space flight. A space-oriented SINS scheme, based on modern multispeed (two/three-speed) algorithms, is implemented in this paper to meet the increasing space navigation requirement. Instructive guidelines are proposed to promote the practical realization and computational efficiency of the improved scheme in space SINSs. Making use of Monte Carlo simulation, both the multispeed scheme and the conventional one are evaluated. Performance comparison between the algorithms indicates that the attitude algorithms associated with both schemes have the same degree of accuracy in the test scenario, and three times accuracy improvement is verified involving the velocity and position algorithms of the multispeed scheme in comparison with those of the conventional one.

The integration of strap-down INS and GPS based on adaptive error damping

The concept and results of integration of a strap-down inertial navigation system (INS) based on low-accuracy inertial sensors and the global positioning system (GPS) have been presented in this paper. This system is aimed for the purposes of navigation, automatic control, and remote tracking of land vehicles. The integration is made by the implementation of an extended Kalman filter (EKF) scheme for both the initial alignment and navigation phases. Traditional integration schemes (centralized and cascaded) are dominantly based on the usage of high-accuracy inertial sensors. The idea behind the suggested algorithm is to use low-accuracy inertial sensors and the GPS as the main source of navigation information, while the acceptable accuracy of INS is achieved by the proper damping of INS errors. The main advantage of integration consists in the availability of reliable navigation parameters during the intervals of absence of GPS data. The influence of INS error damping coefficients is different depending on the fact whether the moving object is maneuvering or is moving with a constant velocity at that time. It is proposed that INS error damping gain coefficients generally should take higher values always when GPS data are absent, while at the same time their values in the error model (EKF prediction phase) can be additionally adapted according to the actual values of vehicle acceleration. The analysis of integrated navigation system performances is made experimentally. The data are acquired along the real land vehicle’s trajectory while the intervals of absence of GPS data are introduced artificially on the parts characterized both by maneuver and by constant velocity.

English

This paper presents error modelling and error analysis of microelectromechnical systems (MEMS) inertial measurement unit (IMU) for a low-cost strapdown inertial navigation system (INS). The INS consists of IMU and navigation processor. The IMU provides acceleration and angular rate of the vehicle in all the three axes. In this paper, errors that affect the MEMS IMU, which is of low cost and less volume, are stochastically modelled and analysed using Allan variance. Wavelet decomposition has been introduced to remove the high frequency noise that affects the sensors to obtain the original values of angular rates and accelerations with less noise. This increases the accuracy of the strapdown INS. The results show the effect of errors in the output of sensors, easy interpretation of random errors by Allan variance, the increase in the accuracy when wavelet decomposition is used for denoising inertial sensor raw data. Defence Science Journal, 2009, 59(6), pp.650-658 , DOI:http://dx.doi.org/10.14429/dsj.59.1571

Accommodation Rule of Double Faults for Seven Inertial Sensors

This paper considers a fault accommodation problem for inertial navigation systems (INS) which have 7 inertial sensors such as gyroscopes and accelerometers. When it is decided that double faults occur in the inertial sensors due to the fault detection and isolation (FDI), it is necessary to decide whether the faulty sensors should be excluded or not. An accommodation rule of double faults for 7 sensors is obtained based on the error covariance of triad-solution of redundant inertial sensors, which is related to the navigation accuracy of INS. Monte Carlo simulation is performed for coplanar configuration and the obtained accommodation rule is drawn in the decision space of two-dimensional Cartesian coordinate system.

FDI using Multiple Parity Vectors for Redundant Inertial Sensors

This paper discusses fault detection, isolation, and accommodation (FDIA) problem of redundant sensors in inertial navigation systems (INS). The averaged parity vector (APV) method is suggested to improve the probability of correct isolation and reduce the numbers of false alarms and wrong isolation. The proposed method employs a new accommodation threshold based on the error covariance of an estimated variable, which is related to the navigation accuracy of INS. This accommodation threshold is also used as the fault detection threshold, so the APV algorithm detects only non-tolerable faults. Given a conditional probability of correct isolation, the minimum number of sample measurements is given with respect to fault size. Computer simulation and experimental results verify the validity of the proposed method.

Accurate INS position solution during GPS outages or degraded GPS

Temporary degraded GPS (DGPS) position loss, in circumstances such as an overhead bridge, can be alleviated by an inertial navigation system (INS) that uses onboard sensors, such as yaw and speed sensors, to determine vehicle position. This paper introduces a post-processing DGPS/INS integration approach based on using the INS solution during DGPS outages or periods of low accuracy DGPS position solutions. In this approach, the INS solution initialization is performed using the DGPS solution before DGPS position solution loss, and measurements from the Inertial Measurement Unit (IMU). The final post-processed INS solution is a weighted average of the INS forward and backward solutions. This work constitutes two parts: the INS initialization methods for different degrees of freedom vehicle positioning models, and the developed weighting model necessary to combine the forward and the backward solutions. The former part is essential in obtaining acceptable INS initial states for both the stand-alone INS or any post-processing or real time INS/GPS integrated system. The latter part is based on the use of the complementary error behaviours of the backward and the forward solutions, and can be used as a survey method with acceptable position solutions accuracies. Applying the forward/backward INS combined solution method on real data shows that the resultant INS solution accuracy is 35 cm or less over a 1000 m road segment. This method is used to survey freeways interchange road segments where 50% of the surveyed distance has no DGPS solution or has a degraded DGPS solution. The average achieved accuracy over the whole freeways interchange is around 40 cm over a 23 km distance.

Wavelet Analysis For Improving INS and INS/DGPS Navigation Accuracy

The integration of the Global Positioning System (DGPS) with an Inertial Navigation System (INS) has been implemented for several years. In an integrated INS/DGPS system, the DGPS provides positions while the INS provides attitudes. In case of DGPS outages (signal blockages), the INS is used for positioning until the DGPS signals are available again. One of the major issues that limit the INS accuracy, as a stand-alone navigation system, is the level of sensor noise. The problem with inertial data is that the required signal is buried into a large window of high frequency noise. If such noise component could be removed, the overall inertial navigation accuracy is expected to improve considerably. The INS sensor outputs contain actual vehicle motion and sensor noise. Therefore, the resulting position errors are proportional to the existing sensor noise and vehicle vibrations. In this paper, wavelet techniques are applied for de-noising the inertial measurements to minimize the undesirable effects of sensor noise and other disturbances. To test the efficiency of inertial data de-noising, two road vehicle INS/DGPS data sets are utilized. Compared to the obtained position errors using the original inertial measurements, the results showed that the positioning performance using de-noised data improves by 34%–63%.

Butterworth Low-Pass Filter for Processing Inertial Navigation System Raw Data

This article tries to apply the Butterworth low-pass filter to inertial navigation system (INS) data processing. A set of INS heading data of a practical example has been calculated and the filtering tested. This filtering method is used to examine the correction of the results made by Guo and Wang. Based on the discrete Fourier transformation and the digital filter design technique, a Butterworth low-pass digital filter has been designed and performed to process INS heading raw data. The design of a special Butterworth filter includes determination of the technical specification of the filter and of the response function in the time domain or the frequency domain (determination of the order and cutoff frequency of the digital filter). For the high-frequency noise of INS raw data, a Butterworth low-pass filter has been designed to obtain a more accurate INS heading. The choice of the parameters and orders of the filter is also discussed in the paper. Finally, an example of INS heading data calculation is presented. The signal-processing TOOLBOX of MATLAB software is used for calculating and mapping the results. The result (RMS) is at the level of 0.01 degrees. The method described here is simpler than Kalman filtering or the smoothing method and has sufficient accuracy for INS processing. It also provides ideas for some other series of raw data with high-frequency noise.

Web-based resources on GPS/INS integration

The global positioning system (GPS) and inertial navigation systems (INSs) have complementary operational characteristics; GPS has long-term stability with a homogeneous accuracy, while the short-term stability of the INS is excellent with high navigation accuracy but the standalone positioning accuracy of INSs deteriorate very rapidly with time. Integrating GPS with INS combines the advantages of each system while mitigating the disadvantages. The result is a robust navigation and positioning with a high data rate of complete navigation solutions (e.g., position, velocity, and attitude) with superior shortterm and long-term accuracy, improved availability, smoother trajectories, and greater integrity. The integrated GPS/INS system has become an indispensable tool for providing precise and continuous position, velocity and attitude information for many positioning and navigation applications, from surveying and mapping to vehicle navigation, guidance and control. There is an extensive variety of websites that are directly or indirectly related to the technologies and applications of GPS/INS integration. This column presents a selection of the publicly available web-based resources on research-based activities for GPS/INS integration. The selection encompasses those international universities and companies that provide electronic versions of their publications.

Fuzzy corrections in a GPS/INS hybrid navigation system

A new concept regarding GPS/INS integration, based on artificial intelligence, i.e. adaptive neuro-fuzzy inference system (ANFIS) is presented. The GPS is used as reference during the time it is available. The data from GPS and inertial navigation system (INS) are used to build a structured knowledge base consisting of behavior of the INS in some special scenarios of vehicle motion. With the same data, the proposed fuzzy system is trained to obtain the corrected navigation data. In the absence of the GPS information, the system will perform its task only with the data from INS and with the fuzzy correction algorithm. This paper shows, using Matlab simulations, that as long as the GPS unavailability time is no longer than the previous training time and for the scenarios a priori defined, the accuracy of trained ANFIS, in absence of data from a reference navigation system, is better than the accuracy of stand-alone INS. The flexibility of model is also analyzed.

A High Accuracy Hybrid Navigation System for Unmanned Underwater Vehicle

The development of small, light weight, low power navigation system for guidance of both tethered and autonomous Unmanned Underwater Vehicle (UUV) is required in applications such as deep salvage, oil and gas well head and pipe line laying and maintenance, etc. All have stringent position requirements in order to define target locations followings the initial find, minimize search time for return missions, as well as support of autopilot functions. In these applications mainly an accurate Sonar Doppler Velocity Log (DVL) was used for Inertial Navigation System (INS) error corrections. But the settlement of DVL is not affordable to various UUV so that not convenient to low cost and small UUV. In this paper we propose a new algorithm for combining the low cost but highly accurate INS with Water Screw Speed (WSS) of the UUV efficiently. In order to evaluate our algorithm we produced the data acquisition system and after several experimental run, we simulated this algorithm searching the error correlation time and noise variance of these estimations.

Establishing Requirements for Gravity Surveys for Very Accurate Inertial Navigation

Many types of gravity surveys have been conducted or proposed to support very accurate inertial navigation. For example, gravimetry and satellite altimetry data now exist over many areas of the world and new techniques are being developed such as satellite-to-satellite tracking and airborne gravity gradiometry. This paper presents a universal approach for analyzing the navigation system improvements afforded by these surveys. Comparisons are shown of the navigation RMS errors for five survey methods. These comparisons reveal the tradeoff between gravity survey resolution and inertial navigation system accuracy.

Standard INS Program Status

In December 1976, Aeronautical Systems Division was directed to establish a competitive development program for a form, fit and function medium accuracy inertial navigation system which would be provided as government furnished equipment to aircraft production and modification programs. Start of the program was delayed due to funding problems; however, contracts were finally awarded in June 1978 to Litton Systems, Rockwell International and The Singer Company for each to design, develop and test four preproduction Standard Inertial Navigation Systems. The preproduction program involved extensive testing at the Central Inertial Guidance Test Facility (CIGTF), Holloman AFB, NM and A-10 flight testing at the Air Force Flight Test Center (AFFTC), Edwards AFB, CA. F-16 Systems Integration Lab (SIL) testing and multiplex data bus compliance testing were also conducted. In addition to these tests, the contractors performed production verification tests, safety of flight tests and a maintainability demonstration. Preliminary CIGTF and AFFTC flight test results are presented. During the preproduction program, studies were performed to develop an acquisition and logistics support approach for the initial production application, the A-10 aircraft. Four logistics support approaches were selected for life cycle cost evaluation during the production source selection. The acquisition and logistics support approach is described. The preproduction effort was structured to support the production source selection. A $33.7 million production contract was awarded to Litton Industries on January 31, 1980 for 237 inertial navigation units. Details of the production contract are presented. The paper concludes with a discussion of future Standard INS competition. The key to success for the Standard INS program is the ability to maintain viable competition.

Accurate INS Transfer Alignment Using a Monitor Gyro and External Navigation Measurements

A particular alignment mechanization for a nonmaneuvering vehicle is described which uses a monitor gyro to estimate the slave inertial navigation system (INS) equivalent east gyro drift rate and thus improves azimuth alignment. A state-space model of the dynamic system with measurements is developed. Results of covariance simulations employing Kalman filter estimation are presented for two master INS position update scenarios, one involving frequent and very accurate updates and the other including infrequent and coarse updates. The ef fects of position updates and the monitor gyro on the quality of transfer alignment are demonstrated and analyzed.

Adaptive Kalman filter for inertial navigation system accuracy improvement

Adaptive Kalman filter for inertial navigation system accuracy improvement

Synthesis of a Very Accurate Inertial Navigation System

A philosophy for the synthesis of a very accurate inertial navigation system is developed here. First, the requirements for a spherical earth navigator are determined, and the basis for a navigator error analysis is developed through the use of mathematical error models. Four types of redundant information are then considered in sequence: external speed information, redundant system gyro, external discrete position source, and additional inertial navigators. The complete inertial navigation system arrived at utilizes all of this redundant information. The presentation is tutorial, emphasizing system accuracy considerations. Reliability as a result of redundant navigators is discussed briefly.