Self-contained Navigation System Research Articles

Wheel-INS2: Multiple MEMS IMU-Based Dead Reckoning System With Different Configurations for Wheeled Robots

A reliable self-contained navigation system is essential for autonomous vehicles. Based on our previous study on Wheel-INS <xref ref-type="bibr" rid="ref1" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[1]</xref> , a wheel-mounted inertial measurement unit (Wheel-IMU)-based dead reckoning (DR) system, in this paper, we propose a multiple IMUs-based DR solution for the wheeled robots. The IMUs are mounted at different places on the wheeled vehicles to acquire various dynamic information. In particular, at least one IMU has to be mounted at the wheel to measure the wheel velocity and take advantage of the rotation modulation. The system is implemented through a distributed extended Kalman filter structure where each subsystem (corresponding to each IMU) retains and updates its own states separately. The relative position constraints between the multiple IMUs are exploited to further limit the error drift and improve the system’s robustness. Particularly, we present the DR systems using dual Wheel-IMUs, one Wheel-IMU plus one vehicle body-mounted IMU (Body-IMU), and dual Wheel-IMUs plus one Body-IMU as examples for analysis and comparison. Field tests illustrate that the proposed multi-IMU DR system outperforms the single Wheel-INS in terms of both positioning and heading accuracy. By comparing with the centralized filter, the proposed distributed filter shows unimportant accuracy degradation while holding significant computation efficiency. Moreover, among the three multi-IMU configurations, the one Body-IMU plus one Wheel-IMU design obtains the minimum drift rate. The position drift rates of the three configurations are 0.82% (dual Wheel-IMUs), 0.69% (one Body-IMU plus one Wheel-IMU), and 0.73% (dual Wheel-IMUs plus one Body-IMU), respectively.

A Navigation and Pressure Monitoring System Toward Autonomous Wireless Capsule Endoscopy

Continuous navigation information for medical insertion methods including wireless capsule endoscopy is an important feature to guide a medical instrument/object to the targeted location within a hollow organ or internal cavity of the patient in the best possible way. Also, an autonomous medical insertion or swallowable device with a self-contained navigation system would reduce the role of the high-level operator and hence reduce the human-factor mistake and risk of injury. The navigation techniques suggested for Wireless Capsule Endoscopy are image-based that are required to transfer and process a significant amount of data in real-time operation. This would increase the complexity of the system and would be more difficult in dark or liquid environments. A novel navigation system for Wireless Capsule Endoscopy/ordinary endoscopy that does not depend on any external source for operation and can handle the uncertainties of the path even in a dark or liquid environment ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i.e</i> .mucosa) of the human body is presented in this paper. The key element of the system is based on a capacitive-based pressure sensor array mounted on the capsule with the shape of semi-hemisphere. The place of each node is arranged to represent the variation in the latitude and the longitude of the travelling path. The system can acquire the required information to navigate the capsule in three-dimensional space and enhance the safety of the locomotion by monitoring the pressure between the capsule and the ambient environment. The system determines the variation of the path 180° in longitude and latitude with less than (<0.004%) percentage of error. Working algorithms for flexible and rigid environments are described in this paper.

A New Efficient Filtering Model for GPS/SINS Ultratight Integration System

Global Positioning System (GPS) and strap-down inertial navigation system (SINS) are recognized as highly complementary and widely employed in the community. The GPS has the advantage of providing precise navigation solutions without divergence, but the GPS signals might be blocked and attenuated. The SINS is a totally self-contained navigation system which is hardly disturbed. The GPS/SINS integration system could utilize the advantages of both the GPS and SINS and provide more reliable navigation solutions. According to the data fusion strategies, the GPS/SINS integrated system could be divided into three different modes: loose, tight, and ultratight integration (LI, TI, and UTC). In the loose integration mode, position and velocity difference from the GPS and SINS are employed to compose measurement vector, in which the vector dimension has nothing to do with the amount of the available satellites. However, in the tight and ultratight modes, difference of pseudoranges and pseudorange rates from the GPS and SINS are employed to compose the measurement vector, in which the measurement vector dimension increases with the amount of available satellites. In addition, compared with the loose integration mode, clock bias and drift are included in the integration state model. The two characteristics magnify the computation load of the tight and ultratight modes. In this paper, a new efficient filter model was proposed and evaluated. Two schemes were included in this design for reducing the computation load. Firstly, a difference between pseudorange measurements was determined, by which clock bias and drift were excluded from the integration state model. This step reduced the dimension of the state vector. Secondly, the integration filter was divided into two subfilters: pseudorange subfilter and pseudorange rate subfilter. A federated filter was utilized to estimate the state errors optimally. In the second step, the two subfilters could run in parallel and the measurement vector was divided into two subvectors with lower dimension. A simulation implemented in MATLAB software was conducted to evaluate the performance of the new efficient integration method in UTC. The simulation results showed that the method could reduce the computation load with the navigation solutions almost unchanged.

RETRACTED ARTICLE: Intelligent face recognition and navigation system using neural learning for smart security in Internet of Things

Most of the advancements are now carried out by interconnecting physical devices with computers; this is what known as Internet of Things (IoT). The major problems facing by blind people fall in the category of navigating through indoor and outdoor environments consisting of various obstacles and recognition of person in front of them. Identification of objects or person only with perceptive and audio information is difficult. An intelligent, portable, less expensive, self-contained navigation and face recognition system is highly demanded for blind people. This helps blind people to navigate with the help of a Smartphone, global positioning system (GPS) and a system equipped with ultrasonic sensors. Face recognition can be done using neural learning techniques with feature extraction and training modules. The images of friends, relatives are stored in the database of user Smartphone. Whenever a person comes in front of the blind user, the application with the help of neural network gives the voice aid to the user. Thus this system can replace the regular imprecise use of guide dogs as well as white sticks to help the navigation and face recognition process for people with impaired vision.In this paper, we have proposed a novel image recognition and navigation system which provides precise and quick messages in the form of audio to visually challenged people so that they can navigate easily. The performance of the proposed method is comparatively analyzed with the help of ROC analysis.

高精度激光多普勒测速仪在陆用自主导航系统中的应用

高精度激光多普勒测速仪在陆用自主导航系统中的应用

The characteristic of laser Doppler signal of solid-state surface

In the designed laser Doppler velocimeter (LDV) for the vehicle self-contained navigation system, the reference object is a kind of solid-state surface. This paper expounded the generation mechanism of laser Doppler signal of this solid-state surface according to the order of the speckle field intensity variation. The expression of laser Doppler signal intensity of solid-state surface is derived based on the theory of speckle and stochastic process. Results of theory and experiments show that the essence of laser Doppler signal of solid-state surface is the coherence stack of two speckles. The signal intensity is directly proportional to the diameter of the photosensitive surface of detector and is inversely proportional to the diameter of laser spot on ground.

Terrestrial self-contained navigation system based on a novel laser Doppler velocimeter

In order to improve the accuracy and manoeuvrability of terrestrial self-contained navigation system, an idea of building an integrated navigation system using a novel laser Doppler velocimeter together with an inertial navigation system is proposed. The structure and performance of the split reuse-type structure of the laser Doppler velocimeter are expounded, and the integrated technology of marching initial alignment and real-time errors compensation are also discussed in detail. The static inertial alignment of the inertial navigation system can be skipped over and the position error of navigation has been decreased from 1180 m in 2 h to 6 m in 2 h. The experiment results show that the strapdown inertial navigation system/laser Doppler velocimeter integrated navigation system can work effectively without parking and the high-accuracy self-contained navigation can be achieved.

Spatial filtering velocimeter using frequency shifting by the method of rotating kernel

A new approach of frequency shifting by rotating kernel is proposed to improve the performance of a spatial filtering velocimeter, used to provide accurate velocity information for a vehicle self-contained navigation system. A linear CMOS image sensor was employed both as a spatiotemporal differential spatial filter and as a photodetector. The filtering operation was fully performed in FPGA and is realized by applying a rotating kernel to the pixel values of the image. Theoretical analysis showed this method could double the maximum measurable velocity. The power spectrum of the output signal was obtained by fast Fourier transform (FFT), and was corrected by a frequency spectrum correction algorithm, named energy centrobaric correction. This velocimeter was used to measure the moving velocities of a conveyor belt. Experimental results verified the method’s ability of reducing the output signal frequency and standard uncertainty of velocity measurement. What is more, the undesired output introduced by frequency shifting to the power spectrum of the output signal was deeply investigated and a new method was proposed to eliminate the undesired component in output signals. This velocimeter aims at providing accurate velocity information for vehicle autonomous navigation system.

Spatial filtering self-velocimeter for vehicle application using a CMOS linear image sensor

The idea of using a spatial filtering velocimeter (SFV) to measure the velocity of a vehicle for an inertial navigation system is put forward. The presented SFV is based on a CMOS linear image sensor with a high-speed data rate, large pixel size, and built-in timing generator. These advantages make the image sensor suitable to measure vehicle velocity. The power spectrum of the output signal is obtained by fast Fourier transform and is corrected by a frequency spectrum correction algorithm. This velocimeter was used to measure the velocity of a conveyor belt driven by a rotary table and the measurement uncertainty is ∼0.54%. Furthermore, it was also installed on a vehicle together with a laser Doppler velocimeter (LDV) to measure self-velocity. The measurement result of the designed SFV is compared with that of the LDV. It is shown that the measurement result of the SFV is coincident with that of the LDV. Therefore, the designed SFV is suitable for a vehicle self-contained inertial navigation system.

Research on speckle noise of laser Doppler velocimeter for the vehicle self-contained navigation

A novel multipoint layer-type laser Doppler velocimeter (MLLDV) is designed to measure the velocity of a vehicle for the self-contained navigation system. In order to investigate the speckle's influence on the Doppler spectrum, formulas of time-lagged covariance and speckle broadening were derived for our MLLDV. Simulations and experiments are made for detailed analysis. The results show that the time-lagged covariance of photocurrent is directly proportional to the incident angle, and is inversely proportional to the elevation fluctuation of the ground together with the velocity of the vehicle. Speckle broadening is a function of the vehicle's velocity, the 1/e2 Gaussian spot radius and the phase correlation length of the ground. For our MLLDV, Doppler frequency and Doppler broadening are both directly proportional to the velocity of the vehicle. Besides, the ratio between Doppler broadening and the corresponding Doppler frequency is about 0.72% when the speed of the vehicle varies from 0 to 9.6m/s.

Surgical navigation with a head-mounted tracking system and display.

We present the design of a self-contained head-mounted surgical navigation system, which consists of an optical tracking system and an optical see-through head-mounted display (HMD). While the current prototype is bulky, we envision a more compact solution via the eventual integration of the tracking camera(s) into the HMD goggles. Rather than attempting to accurately overlay preoperative models onto the field of view, we adopted a simpler approach of displaying a small "picture-in-picture" virtual view in the HMD. We believe this approach will provide suitable assistance for some image-guided procedures, such as tumor resection, while improving the ergonomics by reducing the need for the surgeon to look away from the patient to view an external monitor. We report the results of initial experiments performed with this system, while preparing for a more clinically realistic study.

Velocity correction of the Janus configuration laser Doppler velocimeter

The error of laser Doppler velocimeter (LDV) based on Janus configuration is analyzed as the vehicle inclines. Analysis shows that the error of the Janus configuration LDV depends on the vertical velocity to horizontal velocity ratio (VHR) only. But the measurement accuracy of the Janus configuration LDV will be not high enough to meet the requirement of vehicle self-contained navigation system, if the VHR of the vehicle is overlarge in powerful rough ground. The error of the Janus configuration LDV is corrected through an inclinometer whose precision of angle needed is only 2%. Simulation shows that the error of the Janus configuration LDV after correction can be limited below 0.1% even as the VHR reaches 0.3 and pitch angle is 15°.

유비쿼터스 주차관리 시스템에서 내장 맵 및 센서를 이용한 인프라 독립 네비게이션 시스템

오늘날 사용하고 있는 네비게이션의 신뢰성은 기술적인 발전을 통해 상당히 높아졌다. GPS는 위성기반 위치추적 시스템으로 가장 광범위하게 사용되는 기술이다. 하지만 GPS기반 시스템은 위성이 정확한 뷰를 제공해줄 때에만 위치추적이 정확하다. 본 연구에서는 추적을 위해 내부구조에 의존하지 않는 독자적인 네비게이션을 제안한다. 스마트폰의 내장센서와 내장 맵을 사용하여 정확한 차량 위치추적을 구현한다. 성능평가 결과 정확한 차량의 위치 지원 면에서 우리가 제안한 시스템이 GPS보다 성능이 우수함을 나타내었다. Significant advancements in technology enhanced the reliability of navigation systems that are in use today. The GPS is the most widely used technique for satellite-based location estimation. However, systems based on GPS can only be accurate in providing location data when there is a clear view of the satellites. This paper proposes a self-contained navigation system that does not depend on any tracking infrastructure. Using the built-in sensors of a smartphone and a self-contained map, we implemented an accurate car locator. Evaluation results show that our proposed system outperforms GPS in providing accurate car location assistance.

Application of Hilbert–Huang transform to laser Doppler velocimeter

A new method based on Hilbert–Huang transform is proposed to analyze the laser Doppler signal with a large acceleration. The Doppler signal is decomposed into several Intrinsic Mode Functions (IMFs) via empirical mode decomposition (EMD). And the Hilbert transform is used to compute the instantaneous frequency. The vehicle velocity parameter is estimated by taking linear fitting on the instantaneous frequency of the relevant IMF. The simulation results show that the HHT-based method is quite useful for the LDV that offers velocity parameter to the vehicle self-contained navigation system when the vehicle moves at a large acceleration.

A novel laser Doppler velocimeter

The idea of using a reference-beam laser Doppler velocimeter (LDV) to measure the velocity of a vehicle for an inertial navigation system is proposed. In order to reduce the measurement error produced by the vehicle's jolt, a novel laser Doppler velocimeter (LDV) based on the Janus configuration is presented. The system mounted at the bottom of the vehicle is composed of two single reference-beam subsystems, one of the laser probes looks forward and the other looks backward. Each of the subsystems transmits a laser at 532 nm with the same inclination angle and detects its own Doppler frequency from the scattered light. The pitch angle of the vehicle is calculated by the two detected Doppler frequencies and the inclination angle, and then the measured velocity of the vehicle is compensated. The results of the theory analysis and experiments show that the vehicle's jolt affects conventional reference-beam LDV strongly. LDV with a Janus configuration is insensitive to the inclination angle, and its measurement accuracy is much better than that of a conventional reference-beam LDV. Comparing with the DZL-1 electronic speedometer, the measurement mean error is less than 0.9%, so it is suitable to offer the parameter of velocity for a vehicle self-contained inertial navigation system.

The Potential Impact of GNSS/INS Integration on Maritime Navigation

A version of this paper was presented at ENC-GNSS 2007, Geneva. Its reproduction was kindly authorised by the ENC-GNSS 07 Paper Selection Committee.The General Lighthouse Authorities of the UK &amp; Ireland commissioned an assessment of the impact that the integration of Global Navigation Satellite Systems (GNSS) with Inertial Navigation Systems (INS) would have on the aids to navigation (AtoN) services currently provided, and those to be provided in the future. There is concern about the vulnerability of GNSS, and the provision of complementary and backup systems is seen to be of great importance. The integration of INS could provide an independent and self-contained navigation system, for a limited time period, invulnerable to external intentional or unintentional interference, or the influences of changes in national policies. The study included an analysis of the potential use of GNSS-INS in three of the four phases of a vessel's voyage: coastal, port approach and docking. The project consisted of a technology assessment, looking at the different inertial technologies that might be suitable for each phase. This was followed by a technology proving stage, evaluating suitable equipment using simulation and field trials to prove that the claimed performance could be achieved in practice. The final stage of the project was to assess the effects of the availability of such systems on existing and planned aids to navigation services.

Joint estimation of coefficients of gyrostabilized platform and the state vector of an object

The problem of jointly identifying parameters of a drift model of a gyrostabilized platform and estimating the state vector of a self-contained navigation system is solved. For a drift model of the gyroplatform, a second-order polynomial with nonstationary coefficients is chosen. The stated problem is solved without any simplifying assumptions on the character of motion of an object and distribution of measurement noise.

Use of Absolute Acceleration Measurements in Self-Contained Inertial Navigation

The basis is given of the possibility of constructing an asymptotically stable self-contained inertial navigation system.

Determination of an Estimation of Parameters of Motion of a Spacecraft on the Stage of Its Descent on the Basis of Integration of Inertial and Optoelectronic Navigation Systems

The problem of determining an estimation of current spacecraft motion parameters on the stage of its descent is solved on the basis of readings of an optoelectronic navigation system and additional information from the self-contained inertial navigation system at the most general assumptions on the nature of motion of the object and the statistical properties of the noise of the measuring devices.

Geometrical aspects of a sonar-based navigation system for underwater vehicles

A novel self-contained navigation system has been devised for underwater vehicles operating in and around offshore installations. This system matches data from a sector-scanning sonar device to a computer model of the installation. The paper begins by highlighting the existing approaches to subsea navigation before outlining the main features of the proposed system. It then concentrates on a key component of this system which is a method for calculating the position and heading of an underwater vehicle navigating in the vincinity of tubular steel structures. An iterative solution method is presented which incorporates six degree of freedom vehicle motions and this is verified in a series of laboratory experiments with various arrangements of structural members and using a commercial sonar device. The key features, applications and performance of this method are discussed. The main conclusion is that the proposed method for calculating the position and heading of an underwater vehicle contributes towards achieving an accurate and reliable subsea navigation capability.