Design of Continuous Indoor Navigation System Based on INS and Wifi

2013 ◽  
Vol 303-306 ◽  
pp. 2046-2049 ◽  
Author(s):  
Yi Hu ◽  
Lei Sheng ◽  
Shan Jun Zhang
Keyword(s):  
Navigation System ◽  
Smart Phone ◽  
Dead Reckoning ◽  
Indoor Positioning ◽  
Indoor Navigation ◽  
High Price ◽  
Position Information ◽  
Positioning Method ◽  
Indoor Navigation System ◽  
Navigation Service

The application of navigation, such as guidance of pedestrians, requires a certain accuracy of continuous outdoor and indoor positioning. In outdoor environments GPS system has proved to be effective. However in indoor it is challenging to control the accuracy within 2 to 3 meters. At present several approaches have been developed for indoor positioning, such as RFID. But they are mainly been implemented in professional areas, for general user such as tourists and visual incapable users it is difficult to take advantage of these technologies because of the high price of terminal and the navigation service covered area is extremely limited. In this paper, a new approach of indoor navigation method is proposed to solve the problems of traditional methods. It is based on INS and wifi positioning technology. As hardware, wifi receiver, smart phone built-in accelerometer and digital compass are selected and investigated. User’s indoor position is first estimated by dead reckoning method with INS navigation system and then be recalibrated by wifi position information. Several experiments performed in the test verified the effectiveness of this indoor continuous positioning method described in this paper.

scholarly journals PDR Combined with Magnetic Fingerprint Algorithm for Indoor Positioning

Proceedings ◽  
2018 ◽  
Vol 4 (1) ◽  
pp. 24
Author(s):  
He Huang ◽  
Kaiyue Qiu ◽  
Wei Li ◽  
Dean Luo
Keyword(s):  
Relative Position ◽  
Dead Reckoning ◽  
Indoor Positioning ◽  
Fingerprint Matching ◽  
Localization Algorithm ◽  
Position Information ◽  
Matching Algorithm ◽  
Advantages And Disadvantages ◽  
Positioning Method ◽  
Particle Filter Algorithm

Geomagnetism has become a popular technology for indoor positioning, and its accuracy mainly depends on the accuracy of the geomagnetic matching algorithm. Pedestrian dead reckoning technology can calculate the relative position of pedestrians based on sensor information, but only obtain relative position information. According to the advantages and disadvantages of these two techniques, a high-precision GPDR indoor positioning method is proposed, and the improved particle filter algorithm is used to solve the problem of geomagnetic fingerprint fuzzy solution. Finally, a simulation experiment was conducted. The experimental results show that the accuracy of the proposed fusion localization algorithm is 42% higher than that of the PDR algorithm. Compared with a single geomagnetic fingerprint matching algorithm, the positioning accuracy is improved by 57%.

scholarly journals Hybrid Onboard Smartphone Sensors Measurements to Improve Heading Estimation for Indoors Positioning Solutions

2019 ◽  
Vol 4 (2) ◽  
pp. 50-60 ◽  
Author(s):  
Haval Darwesh Abdalkarim ◽  
Halgurd Sarhang Maghdid
Keyword(s):  
Angular Displacement ◽  
Dead Reckoning ◽  
Indoor Positioning ◽  
Indoor Navigation ◽  
Positioning Accuracy ◽  
Position Information ◽  
Precise Position ◽  
Current Location ◽  
Smartphone Sensors ◽  
Heading Estimation

In the last decade, there is a significant progression and huge demand in using technology; specifically, those technologies are embedded in smartphones (SP). Examples of these technologies are embedding various sensors for multi-purposes. Positioning sensors (Accelerometer, Gyroscope, and Magnetometer) are one of the significant technologies. Besides this, indoor positioning services on smartphones are the main advantage of these sensors. There are many indoor positioning applications, for instance; billing, shopping, security and safety, indoor navigation, entertainment applications, and other point-of-interest (POI) applications. Nevertheless, precise position information through current positioning techniques is the main issue of these applications. The pedestrian dead reckoning (PDR) technique is one of the techniques in which the integration of onboard sensors is used for locating smartphones. Estimated distance, heading, and typical speed can be measured to determine the estimated position of the smartphone via using the PDR technique. The PDR technique offers a low positioning accuracy due to existing accumulated errors of the embedded sensors. To solve this issue, this article proposes a hybrid multi-sensors measurement to reduce the existing sensors drifts and errors and to increase estimated heading accuracy of the smartphone. Further, the sensors’ measurements with the previously estimated position are fused by using KALMAN Filter to determine the current location of the smartphone in each step of walking with better angular displacement accuracy. Proposed algorithm depends on increasing estimated angular displacement of the smartphone using combination of the integrated sensors’ measurements. The achieved positioning accuracy through the proposed approach and based on trial experiments is around 2 meters, which is equivalent to 10% improvement in comparison with state of the art.

scholarly journals IOT ENABLED INDOOR NAVIGATION SYSTEM DESIGN FOR EMERGENCIES

2019 ◽  
Vol XLII-4/W12 ◽  
pp. 61-64
Author(s):  
A. Duru ◽  
I. R. Karas
Keyword(s):  
System Design ◽  
Navigation System ◽  
Signal Propagation ◽  
Satellite System ◽  
Indoor Positioning ◽  
Indoor Navigation ◽  
Positioning Accuracy ◽  
Indoor Navigation System ◽  
Global Navigation Satellite ◽  
High Building

<p><strong>Abstract.</strong> Global Navigation Satellite System is widely accepted and it has good positioning accuracy for outdoor applications. However, it does not provide sufficient positioning accuracy for inside of buildings. Signals are attenuated inside of buildings or dense high building areas because various materials between satellites and receiver create interference to the signal propagation. Thus, indoor positioning technologies have emerged to cover the problem. In this paper, indoor positioning technologies have been investigated and UWB based indoor positioning technology has been chosen between them. In addition to indoor positioning, accelerometer and Wi-Fi connection has been added to the system for mobility. The accelerometer detects emergency cases and alerts relatives of an intended person by using web service. Hereby, remote navigation system design is presented for first aid of the user. The system can detect emergencies, especially falls using the accelerometer and it can locate patients anywhere in the world. The designed system showed that it is possible to detect emergencies and transfer to the web with a 24.17&amp;thinsp;cm average positioning error. Also, it is an assuring system for future remote positioning applications.</p>

scholarly journals Indore Navigation Mobile Application using Indore Positioning System (IPS)

2020 ◽  
Vol 2 (10) ◽  
pp. 5-7
Author(s):  
Anusha Sanampudi* ◽  
Keyword(s):  
Mobile Application ◽  
Smart Phone ◽  
Dead Reckoning ◽  
Steel Structures ◽  
Indoor Positioning ◽  
Indoor Navigation ◽  
Smart Phones ◽  
Positioning System ◽  
Shopping Malls ◽  
Indoor Positioning System

Indoor Positioning system (IPS) is the technology that is used to locate smart phones, people or other objects inside a building where Global Positioning System (GPS) doesn’t work or lack precision such as airports, underground locations, parking, multi-storey buildings etc…There is no fixed standard for implementing IPS rather it could be customized according to the location chosen. IPS in turn uses a number of technologies such as Wi-Fi, Bluetooth, Beacons, magnetic positioning, dead reckoning etc…Among the various technologies available studies prove that Magnetic localization provides a most efficient solution for Indoor positioning. Our paper focuses on building an indoor navigation mobile application for a retail store that allows users to search for a product and navigate them to the particular aisle in which the product is located. There by enabling the application to be location sensitive and context aware. In order to collect magnetic fingerprints and convert the obtained data into latitude and longitude values we make use of an API called IndoorAtlas, which helps in locating smart phones inside a building using the accelerometer, gyroscope, magnetometer and Bluetooth in a mobile. Magnetic localization is the concept where deflections of magnetic field from the steel structures inside the building will be captured by the magnetometer and other sensors within a mobile and that will be used to locate a smart phone inside a building. The same application could be utilized for various use cases such as Supermarkets & Hypermarkets, museums & galleries, Libraries, Hospitals, Airports & stations, Shopping malls, Exhibition and Conferences.

scholarly journals DEVELOPMENT OF A PEDESTRIAN INDOOR NAVIGATION SYSTEM BASED ON MULTI-SENSOR FUSION AND FUZZY LOGIC ESTIMATION ALGORITHMS

2015 ◽  
Vol XL-4/W5 ◽  
pp. 81-86 ◽  
Author(s):  
Y. C. Lai ◽  
C. C. Chang ◽  
C. M. Tsai ◽  
S. Y. Lin ◽  
S. C. Huang
Keyword(s):  
Fuzzy Logic ◽  
Sensor Fusion ◽  
Navigation System ◽  
Indoor Environment ◽  
Inertial Sensors ◽  
Low Cost ◽  
Dead Reckoning ◽  
Indoor Navigation ◽  
Estimation Algorithms ◽  
Indoor Navigation System

This paper presents a pedestrian indoor navigation system based on the multi-sensor fusion and fuzzy logic estimation algorithms. The proposed navigation system is a self-contained dead reckoning navigation that means no other outside signal is demanded. In order to achieve the self-contained capability, a portable and wearable inertial measure unit (IMU) has been developed. Its adopted sensors are the low-cost inertial sensors, accelerometer and gyroscope, based on the micro electro-mechanical system (MEMS). There are two types of the IMU modules, handheld and waist-mounted. The low-cost MEMS sensors suffer from various errors due to the results of manufacturing imperfections and other effects. Therefore, a sensor calibration procedure based on the scalar calibration and the least squares methods has been induced in this study to improve the accuracy of the inertial sensors. With the calibrated data acquired from the inertial sensors, the step length and strength of the pedestrian are estimated by multi-sensor fusion and fuzzy logic estimation algorithms. The developed multi-sensor fusion algorithm provides the amount of the walking steps and the strength of each steps in real-time. Consequently, the estimated walking amount and strength per step are taken into the proposed fuzzy logic estimation algorithm to estimates the step lengths of the user. Since the walking length and direction are both the required information of the dead reckoning navigation, the walking direction is calculated by integrating the angular rate acquired by the gyroscope of the developed IMU module. Both the walking length and direction are calculated on the IMU module and transmit to a smartphone with Bluetooth to perform the dead reckoning navigation which is run on a self-developed APP. Due to the error accumulating of dead reckoning navigation, a particle filter and a pre-loaded map of indoor environment have been applied to the APP of the proposed navigation system to extend its usability. The experiment results of the proposed navigation system demonstrate good navigation performance in indoor environment with the accurate initial location and direction.

scholarly journals INTEGRATION OF PDR AND IMAGE-BASED POSITIONING AIDED BY ARTIFICIAL NEURAL NETWORKS IN INDOOR ENVIRONMENT

2020 ◽  
Vol XLIII-B1-2020 ◽  
pp. 181-185
Author(s):  
M. C. Hung ◽  
K. W. Chiang
Keyword(s):  
Dead Reckoning ◽  
Satellite System ◽  
Indoor Positioning ◽  
Indoor Navigation ◽  
Positioning Method ◽  
Pros And Cons ◽  
Positioning Technique ◽  
The Mean ◽  
Global Navigation Satellite ◽  
The Cost

Abstract. Location based service (LBS) is a popular issue in recent years, which can be applied widely. The most common one is providing the local information and the guide of the Point of Interesting (POI) to users, which means positioning is the necessary technique to put LBS into practice. In an outdoor scenario, the user’s position can be obtained relying on the Global Navigation Satellite System (GNSS), however, the signal of GNSS might be blocked in a building. So, many indoor positioning techniques are developed in the decades, which have the pros and cons respectively. This paper proposes an indoor positioning technique by integrating Pedestrian Dead Reckoning (PDR) with the image-based positioning method, which can decrease the cost significantly because it only needs a camera built-in the smartphone. In the first experiment, we verify the accuracy of positioning by the proposed method, that the mean error in the horizontal direction is about 0.25 meters. In the following experiment, comparing with the misclosure of PDR only and PDR integrated with the proposed method, it can decrease from 8.53% to 1.44%. The improvement is about 83%, therefore, this method is suitable for applying to indoor navigation.

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