scholarly journals Robust Special Strategies Re Sampling for Mobile Inertial Navigation Systems

2019 ◽  
Vol 9 (2) ◽  
pp. 3196-3204
Keyword(s):  
Particle Filtering ◽  
Inertial Sensor ◽  
Low Cost ◽  
Navigation Systems ◽  
Inertial Navigation Systems ◽  
Computing Platform ◽  
Mobile Navigation ◽  
Global Positioning ◽  
Particle Measurement ◽  
Special Strategy

The mobile navigation services in an obstructed area can be extremely challenging especially if the Global Positioning System (GPS) is blocked. In such conditions, users will find it difficult to navigate directly on-site. This needs to use inertial sensor in order to determine the location as standalone, low cost and ubiquity. However, the usage of accurate inertial sensor and fast localization module in the system would lead the phenomenon of sample impoverishment, which it is contribute computation burden to the system. There are different situation of the sample impoverishment, and the solution by using special strategies resampling algorithm cannot be used or fitted in different cases in altogether. Adaptations relating to particle filtering attribute need to be made to the algorithm in order to make resampling more intelligent, reliable and robust. In this paper, we are proposes a robust special strategy resampling algorithm by adapting particle filtering attribute such as; noise and particle measurement. This adaptation is used to counteract sample impoverishment in different cases in altogether. Finally, the paper presents the proposed solution can survive in three (3) types of sample impoverishment situation inside mobile computing platform.

scholarly journals Robust Special Strategies Resampling for Mobile Inertial Navigation Systems

2019 ◽  
Author(s):  
WAN MOHD YAAKOB WAN BEJURI ◽  
MOHD MURTADHA MOHAMAD ◽  
HADRI OMAR ◽  
FARHANA SYED AHMAD ◽  
Nurfarah Ain Limin
Keyword(s):  
Mobile Computing ◽  
Particle Filtering ◽  
Inertial Sensor ◽  
Inertial Navigation ◽  
Navigation Systems ◽  
Inertial Navigation Systems ◽  
Computing Platform ◽  
Mobile Navigation ◽  
Particle Measurement ◽  
Special Strategy

The mobile navigation services in an obstructed areacan be extremely challenging especially if the Global PositioningSystem (GPS) is blocked. In such conditions, users will find itdifficult to navigate directly on-site. This needs to use inertialsensor in order to determine the location as standalone, low costand ubiquity. However, the usage of accurate inertial sensor andfast localization module in the system would lead the phenomenonof sample impoverishment, which it is contribute computationburden to the system. There are different situation of the sampleimpoverishment, and the solution by using special strategiesresampling algorithm cannot be used or fitted in different cases inaltogether. Adaptations relating to particle filtering attribute needto be made to the algorithm in order to make resampling moreintelligent, reliable and robust. In this paper, we are proposes arobust special strategy resampling algorithm by adapting particlefiltering attribute such as; noise and particle measurement. Thisadaptation is used to counteract sample impoverishment indifferent cases in altogether. Finally, the paper presents theproposed solution can survive in three (3) types of sampleimpoverishment situation inside mobile computing platform.

INS/GNSS Integration with Account for Timing Skew and Displacement of GNSS Antenna. Experience of Practical Realization

2021 ◽  
Vol 29 (3) ◽  
pp. 52-68
Author(s):  
N.B. Vavilova ◽  
◽  
A.A. Golovan ◽  
A.V. Kozlov ◽  
I.A. Papusha ◽  
...  
Keyword(s):  
Spatial Separation ◽  
Measurement Unit ◽  
Complex Data ◽  
Navigation Systems ◽  
Inertial Navigation Systems ◽  
Positioning Systems ◽  
Global Positioning ◽  
Antenna Phase ◽  
Antenna Phase Center ◽  
Timing Skew

We examine two aspects specific to complex data fusion algorithms in integrated strapdown inertial navigation systems aided by global positioning systems, with their inherent spatial separation between the GNSS antenna phase center and the inertial measurement unit, as well as with the timing skew between their measurements. The first aspect refers to modifications of mathematical models used in INS/GNSS integration. The second one relates to our experience in their application in onboard airborne navigation algorithms developed by Moscow Institute of Electromechanics and Automatics.

A Universal Approach for Processing any MEMS Inertial Sensor Configuration for Land-Vehicle Navigation

2007 ◽  
Vol 60 (2) ◽  
pp. 233-245 ◽  
Author(s):  
Xiaoji Niu ◽  
Sameh Nasser ◽  
Chris Goodall ◽  
Naser El-Sheimy
Keyword(s):  
Inertial Sensor ◽  
Low Cost ◽  
Navigation Systems ◽  
Micro Electro Mechanical Systems ◽  
Land Vehicle ◽  
Mems Sensor ◽  
Navigation Algorithm ◽  
Main Challenge ◽  
Universal Approach ◽  
Sensor Configuration

Recent navigation systems integrating GPS with Micro-Electro-Mechanical Systems (MEMS) Inertial Measuring Units (IMUs) have shown promising results for several applications based on low-cost devices such as vehicular and personal navigation. However, as a trend in the navigation market, some applications require further reductions in size and cost. To meet such requirements, a MEMS full IMU configuration (three gyros and three accelerometers) may be simplified. In this context, different partial IMU configurations such as one gyro plus three accelerometers or one gyro plus two accelerometers could be investigated. The main challenge in this case is to develop a specific navigation algorithm for each configuration since this is a time-consuming and costly task. In this paper, a universal approach for processing any MEMS sensor configuration for land vehicular navigation is introduced. The proposed method is based on the assumption that the omitted sensors provide relatively less navigation information and hence, their output can be replaced by pseudo constant signals plus noise. Using standard IMU/GPS navigation algorithms, signals from existing sensors and pseudo signals for the omitted sensors are processed as a full IMU. The proposed approach is tested using land-vehicle MEMS/GPS data and implemented with different sensor configurations. Compared to the full IMU case, the results indicate the differences are within the expected levels and that the accuracy obtained meets the requirements of several land-vehicle applications.

The Use of Auxiliary Airborne Sensor Data in SPACE-M Photogrammetric Block Adjustments

1984 ◽  
Vol 38 (1) ◽  
pp. 3-14
Author(s):  
J. A. R. Blais ◽  
M. A. Chapman
Keyword(s):  
Global Positioning System ◽  
Mathematical Formulation ◽  
Real Data ◽  
Sensor Data ◽  
Navigation Systems ◽  
Test Results ◽  
Inertial Navigation Systems ◽  
Adjustment Program ◽  
Global Positioning ◽  
Topographical Mapping

The mathematical formulation used in the photogrammetric block adjustment program SPACE-M has recently been extended to accommodate auxiliary airborne sensor data corresponding to the position and/or attitude of the aerial camera at the time of film exposure. Examples of such systems are statoscopes, laser profilometers, Inertial Navigation Systems (INS) and the Global Positioning System (GPS). The description of the use of these auxiliary data in SPACE-M is outlined and references are given to other related formulations. Test results with simulated and limited real data are presented with some analysis of the implications for topographical mapping and other applications.

Low-Altitude and High-Speed Terrain Tracking Method for Lightweight AUVs

2018 ◽  
Vol 30 (6) ◽  
pp. 971-979 ◽  
Author(s):  
Toshihiro Maki ◽  
Yukiyasu Noguchi ◽  
Yoshinori Kuranaga ◽  
Kotohiro Masuda ◽  
Takashi Sakamaki ◽  
...  
Keyword(s):  
High Speed ◽  
Low Cost ◽  
Autonomous Underwater Vehicles ◽  
Vertical Plane ◽  
Potential Method ◽  
Visual Observation ◽  
Doppler Velocity ◽  
Navigation Systems ◽  
Inertial Navigation Systems ◽  
Constant Altitude

This paper proposes a new method for cruising-type autonomous underwater vehicles (AUVs) to track rough seafloors at low altitudes while also maintaining a high surge velocity. Low altitudes are required for visual observation of the seafloor. The operation of AUVs at low altitudes and high surge velocities permits rapid seafloor imaging over a wide area. This method works without high-grade sensors, such as inertial navigation systems (INS), Doppler velocity logs (DVL), or multi-beam sonars, and it can be implemented in lightweight AUVs. The seafloor position is estimated based on a reflection intensity map defined on a vertical plane, using measurements from scanning sonar and basic sensors of depth, attitude, and surge velocity. Then, based on the potential method, a reference pitch angle is generated that allows the AUV to follow the seafloor at a constant altitude. This method was implemented in the AUV HATTORI, and a series of sea experiments were carried out to evaluate its performance. HATTORI (Highly Agile Terrain Tracker for Ocean Research and Investigation) is a lightweight and low-cost testbed designed for rapid and efficient imaging of rugged seafloors, such as those containing coral reefs. The vehicle succeeded in following a rocky terrain at an altitude of approximately 2 m with a surge velocity of approximately 0.8 m/s. This paper also presents the results of sea trials conducted at Ishigaki Island in 2017, where the vehicle succeeded in surveying the irregular, coral-covered seafloor.

scholarly journals INDOOR NAVIGATION ASSISTANCE SYSTEM USING BLUETOOTH

2016 ◽  
pp. 44-45
Author(s):  
APURVA MEHTA ◽  
D. D. PUKALE ◽  
RADHIKA BHAGAT ◽  
RUJAL SHAH
Keyword(s):  
Short Range ◽  
Low Cost ◽  
Indoor Navigation ◽  
Assistance System ◽  
Navigation Systems ◽  
Positioning Systems ◽  
Navigation Assistance ◽  
The Past ◽  
Current Location ◽  
Global Positioning

In the past few years, a number of ideas have been proposed for indoor navigation systems. These ideas were not as widely implemented as outdoor positioning systems like GPS(Global Positioning Systems). We propose an indoor navigation assistance system using Bluetooth which is low cost and feasible to use in daily life. Our system enables users with handheld mobile devices to steer with ease through the indoor premises using the short range radio frequencies of Bluetooth. It also establishes user’s current location and the various paths leading to the destination. Dijkstra’s algorithm is used to determine the shortest path from the source to the required destination.

Adaptive Anti-Disturbance Method for Magnetometer and INS Integration in a Road Vehicle

2019 ◽  
Vol 72 (06) ◽  
pp. 1513-1532
Author(s):  
Zongkai Wu ◽  
Wei Wang
Keyword(s):  
Kalman Filter ◽  
Low Cost ◽  
Navigation Systems ◽  
Extend Kalman Filter ◽  
Inertial Navigation Systems ◽  
Road Vehicle ◽  
Practical Applications ◽  
Short And Long Term ◽  
Magnetic Disturbances

The integration of magnetometers and Inertial Navigation Systems (INS) is widely used in low-cost navigation systems. However, even if the system has been calibrated, random magnetic disturbances still appear in practical applications, which lead to large heading errors. To solve this problem, an adaptive anti-disturbance method to overcome random magnetic disturbance is proposed. First, disturbances are classified and analysed in detail based on actual road vehicle driving data. Then an Adaptive Robust Extend Kalman Filter (AREKF) is designed to resist sudden disturbances. However, an AREKF may accumulate errors slowly when a long-term disturbance exists. Considering this situation, this paper proposes that AREKF is used to maintain accuracy in the early stages, at the same time as the magnetometer is quickly calibrated with a Kalman filter. Then, the new magnetometer parameters are put into the AREKF to suppress long-term disturbances. Finally, cascading these two modules, not only the sudden disturbance can be overcome, but the situation of long-term disturbances can be suppressed. The results of simulation and an actual driving test show that the proposed method can effectively overcome random magnetic disturbances in both the short and long term.

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