Precision navigation system design for Moon penetrator

2016 ◽  
Vol 88 (6) ◽  
pp. 791-798
Author(s):  
Xiaogang Wang ◽  
Wutao Qin ◽  
Yuliang Bai ◽  
Naigang Cui
Keyword(s):  
System Design ◽  
Kalman Filtering ◽  
Navigation System ◽  
Estimation Accuracy ◽  
Line Of Sight ◽  
Accurate Estimation ◽  
Navigation Systems ◽  
Vision Sensor ◽  
Content Type ◽  
Sigma Point

Purpose Penetrator plays an important role in the exploration of Moon and Mars. The navigation method is a key technology during the development of penetrator. To meet the high accuracy requirements of Moon penetrator, this paper aims to propose two kinds of navigation systems. Design/methodology/approach The line of sight of vision sensor between the penetrator and Moon orbiter could be utilized as the measurement during the navigation system design. However, the analysis of observability shows that the navigation system cannot estimate the position and velocity of penetrator, when the line of sight measurement is the only resource of information. Therefore, the Doppler measurement due to the relative motion between penetrator and the orbiter is used as the supplement. The other option is the relative range measurement between penetrator and the orbiter. The sigma-point Kalman Filtering is implemented to fuse the information from the vision sensor and Doppler or rangefinder. The observability of two navigation system is analyzed. Findings The sigma-point Kalman filtering could be used based on vision sensor and Doppler radar or laser rangefinder to give an accurate estimation of Moon penetrator position and velocity without increasing the payload of Moon penetrator or decreasing the estimation accuracy. However, the simulation result shows that the last method is better. The observability analysis also proves this conclusion. Practical implications Two navigation systems are proposed, and the simulations show that both systems can provide accurate estimation of states of penetrator. Originality/value Two navigation methods are proposed, and the observability of these navigation systems is analyzed. The sigma-point Kalman filtering is first introduced to the vision-based navigation system for Moon penetrator to provide precision navigation during the descent phase of Moon penetrator.

scholarly journals Interval Kalman Filtering in Navigation System Design for an Uninhabited Surface Vehicle

2013 ◽  
Vol 66 (5) ◽  
pp. 639-652 ◽  
Author(s):  
A Motwani ◽  
SK Sharma ◽  
R Sutton ◽  
P Culverhouse
Keyword(s):  
Kalman Filter ◽  
System Design ◽  
State Space ◽  
Kalman Filtering ◽  
Navigation System ◽  
Potential Application ◽  
State Space Model ◽  
Space Model ◽  
Heading Angle ◽  
Modelling Assumptions

This paper reports on the potential application of interval Kalman filtering techniques in the design of a navigation system for an uninhabited surface vehicle namedSpringer. The interval Kalman filter (IKF) is investigated for this task since it has had limited exposure for such usage. A state-space model of theSpringersteering dynamics is used to provide a framework for the application of the Kalman filter (KF) and IKF algorithms for estimating the heading angle of the vessel under erroneous modelling assumptions. Simulations reveal several characteristics of the IKF, which are then discussed, and a review of the work undertaken to date presented and explained in the light of these characteristics, with suggestions on potential future improvements.

scholarly journals Improving the cost estimates of complex projects in the project-based industries

2017 ◽  
Vol 7 (2) ◽  
pp. 173-184 ◽  
Author(s):  
Pournima Sridarran ◽  
Kaushal Keraminiyage ◽  
Leon Herszon
Keyword(s):  
Best Practices ◽  
Cost Estimation ◽  
Estimation Accuracy ◽  
Effective Practices ◽  
Accurate Estimation ◽  
Content Type ◽  
Complex Projects ◽  
Cost Implications ◽  
The Cost ◽  
Improve Cost

Purpose Project-based industries face major challenges in controlling project cost and completing within the budget. This is a critical issue as it often connects to the main objectives of any project. However, accurate estimation at the beginning of the project is difficult. Scholars argue that project complexity is a major contributor to cost estimation inaccuracies. Therefore, recognising the priorities of acknowledging complexity dimensions in cost estimation across similar industries is beneficial in identifying effective practices to reduce cost implications. Hence, the purpose of this paper is to identify the level of importance given to different complexity dimensions in cost estimation and to recognise best practices to improve cost estimation accuracy. Design/methodology/approach An online questionnaire survey was conducted among professionals including estimators, project managers, and quantity surveyors to rank the identified complexity dimensions based on their impacts in cost estimation accuracy. Besides, in-depth interviews were conducted among experts and practitioners from different industries, in order to extract effective practices to improve the cost estimation process of complex projects. Findings Study results show that risk, project and product size, and time frame are the high-impact complexity dimensions on cost estimation, which need more attention in reducing unforeseen cost implications. Moreover, study suggests that implementing a knowledge sharing system will be beneficial to acquire reliable and adequate information for cost estimation. Further, appropriate staffing, network enhancement, risk management, and circumspect estimation are some of the suggestions to improve cost estimation of complex projects. Originality/value The study finally provides suggestions to improve cost estimation in complex projects. Further, the results are expected to be beneficial to learn lessons from different industries and to exchange best practices.

scholarly journals Incorporating Landmarks in Driver Navigation System Design: An Overview of Results from the REGIONAL Project

2005 ◽  
Vol 58 (1) ◽  
pp. 47-65 ◽  
Author(s):  
Andrew J. May ◽  
Tracy Ross ◽  
Steven H. Bayer
Keyword(s):  
System Design ◽  
Navigation System ◽  
Vehicle Navigation ◽  
Navigation Systems ◽  
Key Characteristics ◽  
Wide Range ◽  
Regional Project ◽  
Integral Feature

This paper presents an overview of results from the two year REGIONAL project. The aims of REGIONAL were to undertake research to enable landmarks to be an integral feature of future vehicle navigation systems. Results from the project, including five empirical road-based trials, are summarised. The main findings were: landmarks were widely used by drivers as key navigation cues; the incorporation of good landmarks within navigation instructions has the potential to considerably enhance vehicle navigation systems; although a wide range of landmarks are potentially useful to a driver, only a limited set, which displayed key characteristics, were consistently effective as navigation cues.

Parametric identification of the error model for the aircraft inertial navigation system

2021 ◽  
Author(s):  
Keyword(s):  
Navigation System ◽  
Inertial Navigation System ◽  
Inertial Navigation ◽  
Estimation Algorithm ◽  
Parametric Identification ◽  
Average Frequency ◽  
Estimation Accuracy ◽  
Navigation Systems ◽  
Random Drift ◽  
Simple Method

The problem of increasing the accuracy at estimating the inertial navigation systems errors by using identifying the parameters of the model is investigated. A scheme for correcting navigation systems with an estimation algorithm is presented. The accuracy of the errors estimation for the inertial navigation system by using the nonstationary adaptive Kalman filter when the average frequency of the gyroscope random drift changes is determined. A simple method for parametric identification of the change average frequency of a random drift by using a tuning coefficient is proposed. The results analysis of the estimation algorithm modeling by using the data of laboratory experiments with the serial navigation system Ts-060K is carried out. In the models of the estimation algorithm different average frequency values of the random drift change are used. Keywords aircraft; inertial navigation system; estimation algorithm; parametric identification; average frequency of random gyroscope drift; tuning factor; estimation accuracy

Spatial Mental Representation: Implications for Navigation System Design

2008 ◽  
Vol 4 (1) ◽  
pp. 1-40 ◽  
Author(s):  
Holly A. Taylor ◽  
Tad T. Brunyé ◽  
Scott T. Taylor
Keyword(s):  
System Design ◽  
Spatial Cognition ◽  
Mental Representation ◽  
Navigation System ◽  
Spatial Information ◽  
The Body ◽  
Navigation Systems ◽  
Design Consideration ◽  
Information Preferences ◽  
Domain Specific

Similarities exist in how people process and represent spatial information and in the factors that contribute to disorientation, whether one is moving through airspace, on the ground, or surgically within the body. As such, design principles for presenting spatial information should bear similarities across these domains but also be somewhat specific to each. In this chapter, we review research in spatial cognition and its application to navigation system design for within-vehicle, aviation, and endoscopic navigation systems. Taken together, the research suggests three general principles for navigation system design consideration. First, multimedia displays should present spatial information visually and action and description information verbally. Second, display organizations should meet users' dynamic navigational goals. Third, navigation systems should be adaptable to users' spatial information preferences. Designers of adaptive navigation display technologies can maximize the effectiveness of those technologies by appealing to the basic spatial cognition processes employed by all users while conforming to user's domain-specific requirements.

II—A Navigation System Model

1972 ◽  
Vol 25 (2) ◽  
pp. 152-161
Author(s):  
Shigeaki Mabuchi
Keyword(s):  
Kalman Filtering ◽  
Navigation System ◽  
Satellite System ◽  
System Model ◽  
Navigation Satellite ◽  
Navigation Systems ◽  
Automated Systems ◽  
Inertial Navigation Systems ◽  
Electronic Computers ◽  
Marine Navigation

Modern marine navigation is experiencing a more drastic change than ever before; automated systems are being introduced extensively in various parts of ships at various levels, inertial navigation systems are on the verge of introduction, the Navy Navigation Satellite system is now open for civilian use, and parallel with these developments modern data processing systems armed with electronic computers are being used at sea. In the processing of data, the application of modern statistical methods such as Kalman filtering should be noted.

Technical Analysis and Implementation Cost Assessment of Sigma-Point Kalman Filtering and Particle Filtering in Autonomous Navigation Systems

2010 ◽  
pp. 125-151 ◽  
Author(s):  
Gerasimos G. Rigatos
Keyword(s):  
Kalman Filtering ◽  
Particle Filtering ◽  
State Vector ◽  
Autonomous Navigation ◽  
Technical Analysis ◽  
Cost Assessment ◽  
Navigation Systems ◽  
Implementation Cost ◽  
State Distribution ◽  
Sigma Point

The chapter provides technical analysis and implementation cost assessment of Sigma-Point Kalman Filtering and Particle Filtering in autonomous navigation systems. As a case study, the sensor fusion-based navigation of an unmanned aerial vehicle (UAV) is examined. The UAV tracks a desirable flight trajectory by fusing measurements coming from its Inertial Measurement Unit (IMU) and measurements which are received from a satellite or ground-based positioning system (e.g. GPS or radar). The estimation of the UAV’s state vector is performed with the use of (i) Sigma-Point Kalman Filtering (SPKF), (ii) Particle Filtering (PF). Trajectory tracking is succeeded by a nonlinear controller which is derived according to flatness-based control theory and which uses the UAV’s state vector estimated through filtering. The performance of the autonomous navigation system which is based on the aforementioned state estimation methods is evaluated through simulation tests. Implementation cost assessment shows that PF requires more sample points than SPKF to approximate the state distribution. Therefore PF is a computationally more demanding method which needs more costly computing machines. However, the PF is a nonparametric filter which can be applied to any kind of state distribution, while the SPKF state estimators are still based on the assumption of a Gaussian process and measurement noise.

scholarly journals Performance Enhancement for Conventional Tightly Coupled INS/DVL Navigation System Using Regeneration of Partial DVL Measurements

2020 ◽  
Vol 2020 ◽  
pp. 1-15 ◽  
Author(s):  
Taesuk Yoo ◽  
Moonhwan Kim ◽  
Seonil Yoon ◽  
Daejoong Kim
Keyword(s):  
Navigation System ◽  
Performance Enhancement ◽  
Measurement Data ◽  
Estimation Accuracy ◽  
Doppler Velocity ◽  
Navigation Systems ◽  
Integrated Navigation ◽  
Loosely Coupled ◽  
Velocity Error ◽  
Tightly Coupled

Inertial navigation systems/Doppler velocity log (INS/DVL) integrated navigation systems are widely used in underwater environments where GPS is unavailable. An INS/DVL integrated navigation system is generally loosely coupled; however, this does not work if any of the DVL transducers do not work. If a system is tightly coupled, velocity error can be estimated with fair accuracy even if some of the transducers fail. However, despite the robustness of a tightly coupled system compared to a loosely coupled one, velocity error estimation accuracy of the former decreases as the number of faulty transducers increases. Therefore, this paper proposes an INS/DVL/revolutions per minute (RPM) integrated navigation filter designed to improve the performance of conventional tightly coupled integrated systems by estimating data from faulty transducers using RPM data. Two salient features of the proposed filter are (1) estimating RPM data accounting for error from the effect of tidal currents and (2) continuous estimation of error in RPM data by selectively converting only the measurements of faulty transducers. The performance of the proposed filter was first verified using Monte Carlo numerical simulations with the analysis range set to 1 standard deviation (1σ, 68%) and then with real sea test measurement data.

Vision-based relative navigation using cubature Huber-based filtering

2018 ◽  
Vol 90 (5) ◽  
pp. 843-850 ◽  
Author(s):  
Cheng Chen ◽  
Xiaogang Wang ◽  
Wutao Qin ◽  
Naigang Cui
Keyword(s):  
Kalman Filtering ◽  
Estimation Method ◽  
Accurate Estimation ◽  
Relative Navigation ◽  
Extended Kalman Filtering ◽  
Filtering Algorithms ◽  
Content Type ◽  
Gaussian Filtering ◽  
Non Gaussian ◽  
Better Than

Purpose A novel vision-based relative navigation system (VBRNS) plays an important role in aeronautics and astronautics fields, and the filter is the core of VBRNS. However, most of the existing filtering algorithms used in VBRNS are derived based on Gaussian assumption and disregard the non-Gaussianity of VBRNS. Therefore, a novel robust filtering named as cubature Huber-based filtering (CHF) is proposed and applied to VBRNS to improve the navigation accuracy in non-Gaussian noise case. Design/methodology/approach Under the Bayesian filter framework, the third-degree cubature rule is used to compute the cubature points which are propagated through state equation, and then the predicted mean and the associated covariance are taken. A combined minimum l1 and l2-norm estimation method referred as Huber’s criterion is used to design the measurement update. After that, the vision-based relative navigation model is presented and the CHF is used to integrate the line-of-sight measurements from vision camera with inertial measurement of the follower to estimate the precise relative position, velocity and attitude between two unmanned aerial vehicles. During the design of relative navigation filter, the quaternions are used to represent the attitude and the generalized Rodrigues parameters are used to represent the attitude error. The simulation is conducted to demonstrate the effectiveness of the algorithm. Findings By this means, the VBRNS could perform better than traditional VBRNS whose filter is designed by Gaussian filtering algorithms. And the simulation results demonstrate that the CHF could exhibit robustness when the system is non-Gaussian. Moreover, the CHF has more accurate estimation and faster rate of convergence than extended Kalman Filtering (EKF) in face of inaccurate initial conditions. Originality/value A novel robust nonlinear filtering algorithm named as CHF is proposed and applied to VBRNS based on cubature Kalman filtering (CKF) and Huber’s technique. The CHF could adapt to the non-Gaussian system effectively and perform better than traditional Gaussian filtering such as EKF.

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