An Improved Indoor Location Technique using Kalman Filter (original) (raw)
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An Improved Indoor Location Technique Using Combination of Kalman Filter and Centroid Positioning
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Indoor positioning technique is used to trace the location of entities within a non-space environment riding from the incapability of GPS to do so. Most of indoor localization techniques proposed by researchers to discover an optimized solution for indoor location tracking that has high precision and accuracy. This paper proposes an improved indoor location technique by implementing Trilateration and Kalman Filter that can manipulate noise signal reduced from raw Received Signal Strength Indicator (RSSI). This paper also proposed the uses of Centroid Positioning that be amended on top of Kalman Filter which to study whether it can improve the accuracy rate or not. Upon implementing the technique, observation and comparison are made to measure the effectiveness and reliability of the uses of Kalman Filter and Centroid Positioning. Our analysis and finding show that the enhanced indoor positioning technique has improved the accuracy tremendously.
Indoor Positioning System for Location based Healthcare using Trilateration with Corrections
23rd ICE/IEEE ITMC International Technology Management Conference, 2017
Indoor positioning systems are becoming a required subsystem in many ambient assisted living scenarios. Another area that would greatly benefit from the enriched context of localization is the IoT (Internet of Things) device interaction. However, at this moment there aren't any satisfying technologies or approaches for precise indoor positioning. This paper proposes an indoor positioning method based on trilateration using Wi-Fi RSSI measurements with corrections to eliminate the noise and the bias. The proposed method is tested in a laboratory environment and results are described.
Filtering Effect on RSSI-Based Indoor Localization Methods
Tanzania Journal of Engeering and Technology, 2022
Indoor positioning systems are used to locate and track objects in an indoor environment. Distance estimation is done using received signal strength indicator (RSSI) of radio frequency signals. However, RSSI is prone to noise and interference which can greatly affect the accuracy performance of the system. In this paper Internet of Things (IoT) technologies like low energy Bluetooth (BLE), WiFi, LoRaWAN and ZigBee are used to obtain indoor positioning. Adopting the existing trilateration and positioning algorithms, the Kalman, Fast Fourier Transform (FFT) and Particle filtering methods are employed to denoise the received RSSI signals to improve positioning accuracy. Experimental results show that choice of filtering method is of significance in improving the positioning accuracy. While FFT and Particle methods had no significant effect on the positioning accuracy, Kalman filter has proved to be the method of choice for BLE, WiFi, LoRaWAN and ZigBee. Compared with unfiltered RSSI, results showed that accuracy was improved by 2% in BLE, 3% in WiFi, 22% in LoRaWAN and 17% in ZigBee technology for Kalman filtering method. ARTICLE INFO
Sensors, 2021
Indoor positioning has become a very promising research topic due to the growing demand for accurate node location information for indoor environments. Nonetheless, current positioning algorithms typically present the issue of inaccurate positioning due to communication noise and interferences. In addition, most of the indoor positioning techniques require additional hardware equipment and complex algorithms to achieve high positioning accuracy. This leads to higher energy consumption and communication cost. Therefore, this paper proposes an enhanced indoor positioning technique based on a novel received signal strength indication (RSSI) distance prediction and correction model to improve the positioning accuracy of target nodes in indoor environments, with contributions including a new distance correction formula based on RSSI log-distance model, a correction factor (Beta) with a correction exponent (Sigma) for each distance between unknown node and beacon (anchor nodes) which are ...
A new method for improving Wi-Fi-based indoor positioning accuracy
Wi-Fi and smartphone based positioning technologies are play-ing a more and more important role in Location Based Service (LBS) industries due to the rapid development of the smartphone market. However, the low positioning accuracy of these technologies is still an issue for indoor positioning. To ad-dress this problem, a new method for improving the indoor posi-tioning accuracy was developed. The new method initially used the Nearest Neighbor (NN) algorithm of the fingerprinting meth-od to identify the initial position estimate of the smartphone us-er. Then two distance correction values in two roughly perpen-dicular directions were calculated by the path loss model based on the two signal strength indicator (RSSI) values observed. The errors from the path loss model were eliminated by differencing two model-derived distances from the same access point. The new method was tested and the results compared and assessed against that of the commercial Ekahau RTLS system and the NN algorithm. The preliminary results showed that the positioning accuracy has been improved consistently after the new method was applied and the root mean square accuracy improved to 3.3 m from 3.8 m compared with the NN algorithm.
Robust Trilateration Based Algorithm for Indoor Positioning Systems
Indoor Positioning Systems (IPS) plays crucial role in indoor environment items positioning used in self-navigating robots and helping hands. To obtain position information, positioning algorithms employing Received Signal Strength Indicator (RSSI) are of great benefit since they reuse the existing radio wireless infrastructures for indoor positioning. Due to multipath, non-line of sight propagation, metal reflection and interference noise in the indoor environment which is constantly changing, different algorithms have been developed to fit particular environments. The environment changes in indoor environment are inevitable which decreases the overall accuracy of the developed indoor positioning algorithms. With the aim of solving the challenging nature of environment dependency in indoor environment, a robust radio signal strength indicator-based algorithm for radio signal identification (RFID) indoor positioning system was developed. The algorithm uses circle expansion and reduc...
Indoor positioning using circle expansion-based adaptive trilateration algorithm
Journal of Electrical Systems and Information Technology
The increasing availability of mobile devices with wireless communications capabilities has stimulated the growth of indoor positioning services. Indoor positioning is used to locate, in real time, devices’ positions for easy access. The indoor positioning, however, is challenging compared to outdoor positioning due to the large number of obstacles. Global positioning system is ideal for outdoor localization but fails in indoor environments with limited space. Recent development of the Internet of Things (IoT) has brought forth portable and cost-effective wireless technologies that can be used for indoor positioning. In this work, an adaptive trilateration algorithm based on received signal strength indicator (RSSI) was proposed. To assess the positioning accuracy of the proposed algorithm, Bluetooth Low Energy (BLE), Wi-Fi (IEEE 802.11n), ZigBee and LoRaWAN IoT technologies were used. Results show that the error performance is improved by 4% in BLE, 17% in ZigBee, 22% in Wi-Fi and ...
Positioning is the most attractive technology today. Various technologies are used now days for positioning purpose. GPS is mainly used for outdoor environment. Non-suitability of GPS in indoor conditions because of its NLOS conditions and signal attenuation has lead to several other techniques of indoor positioning. This paper compares few indoor positioning methods and proposes indoor positioning system using tri-lateration method which uses RSSI data from wi-fi access points to do localization in indoor environment.
JURNAL INFOTEL
Wireless network technology that is used today is developing rapidly because of the increasing need for location information of an object with high accuracy. Global Positioning System (GPS) is a technology to estimate the current location. Unfortunately, GPS has a disadvantage of low accuracy of 10 meters when used indoors. Therefore, it began to be developed with the concept of an indoor positioning system. This is a technology used to estimate the location of objects in a building by utilizing WSN (Wireless Sensor Network). The purpose of this study is to estimate the location of the unknown nodes in the lecturer room as an object and obtain the accuracy of the system being tested. The positioning process is based on the received signal strength (RSSI) on the unknown node using the ZigBee module. The trilateration method is used to estimate unknown node located at the observation area based on the signal strength received at the time of testing. The result shows that the path loss...
Indoor Localization Method Based on Wi-Fi Trilateration Technique
—This paper describes a Wi-Fi trilateration method for indoor localization using Android-based mobile device. Approaches based on signal propagation model and received signal strength measurement collection are considered. The indoor signal propagation problem is resolved by received signal strength measurement collection that improves localization accuracy. Indoor positioning technique opens possibilities for development various intelligent systems that provide the user location-based information inside buildings. These systems include positioning functionality based on such technologies as Wi-Fi, Bluetooth, and GSM.