scholarly journals A low-cost indoor localization system based on received signal strength indicator by modifying trilateration for harsh environments

2018 ◽  
Vol 14 (6) ◽  
pp. 155014771877968 ◽  
Author(s):  
Haibin Tong ◽  
Qingxu Deng ◽  
Tianyu Zhang ◽  
Yuanguo Bi
Keyword(s):  
Indoor Localization ◽  
Behavior Pattern ◽  
Signal Strength ◽  
Received Signal Strength ◽  
Harsh Environments ◽  
Monitoring And Control ◽  
Distance Ratio ◽  
Received Signal Strength Indicator ◽  
Localization System ◽  
Acceptable Accuracy

Indoor localization systems using received signal strength indicator are very popular for their low power and low complexity, but some drawbacks limit their accuracy, especially in harsh environments, such as multipath and fluctuation. Most existing approaches solve the problem by “fingerprinting.” However, “fingerprinting” based algorithms are unsuitable for changeable environments like construction, since they all demand prior knowledge of the environment. This article studies a novel localization system to achieve an acceptable accuracy position using received signal strength indicator for harsh environments like construction. Based on analysis of the targets’ behavior pattern, we first use curve fitting to filter the distance derived from received signal strength indicator. And then, we propose a distance ratio location algorithm to estimate the targets’ positions. Furthermore, Kalman filter is considered to smooth the position results. This method has been applied in the “Monitoring and Control System for Underground Tunneling Based on Cyber Physical System” Project in Wuhan for tracking workers and vehicles. Practice results show that our system has an acceptable accuracy.

Improve the Robustness of Indoor Localization Using DRSS

2014 ◽  
Vol 556-562 ◽  
pp. 5922-5925
Author(s):  
Peng Xie
Keyword(s):  
Indoor Localization ◽  
Signal Strength ◽  
Received Signal Strength ◽  
Localization System ◽  
Heterogeneous Devices ◽  
Positioning Technique ◽  
Better Than

In this paper, we present a fingerprint positioning technique based on differential received signal strength (DRSS).By using DRSS fingerprints, the problem of degraded accuracy caused by heterogeneous devices in indoor WLAN localization. The robustness of DRSS fingerprints is proved, both theoretically and practically, to be better than that of RSS, thus the applicability as well as accuracy is improved in a WLAN indoor localization system with various devices.

scholarly journals A three-dimensional pattern recognition localization system based on a Bayesian graphical model

2020 ◽  
Vol 16 (9) ◽  
pp. 155014771988489 ◽  
Author(s):  
Abdulraqeb Alhammadi ◽  
Fazirulhisyam Hashim ◽  
Mohd. Fadlee A Rasid ◽  
Saddam Alraih
Keyword(s):  
Graphical Model ◽  
Indoor Localization ◽  
Three Dimensional ◽  
Signal Strength ◽  
Local Area ◽  
Received Signal Strength ◽  
Reference Points ◽  
Indoor Environments ◽  
Localization System ◽  
Proposed Model

Access points in wireless local area networks are deployed in many indoor environments. Device-free wireless localization systems based on available received signal strength indicators have gained considerable attention recently because they can localize the people using commercial off-the-shelf equipment. Majority of localization algorithms consider two-dimensional models that cause low positioning accuracy. Although three-dimensional localization models are available, they possess high computational and localization errors, given their use of numerous reference points. In this work, we propose a three-dimensional indoor localization system based on a Bayesian graphical model. The proposed model has been tested through experiments based on fingerprinting technique which collects received signal strength indicators from each access point in an offline training phase and then estimates the user location in an online localization phase. Results indicate that the proposed model achieves a high localization accuracy of more than 25% using reference points fewer than that of benchmarked algorithms.

scholarly journals Performance Comparison of Several Range-based Techniques for Indoor Localization Based on RSSI

2021 ◽  
Vol 7 (1) ◽  
pp. 40-53
Author(s):  
Dwi Joko Suroso ◽  
Farid Yuli Martin Adiyatma ◽  
Ahmad Eko Kurniawan ◽  
Panarat Cherntanomwong
Keyword(s):  
Approximation Method ◽  
Indoor Localization ◽  
Classical Method ◽  
Signal Strength ◽  
Received Signal Strength ◽  
Performance Comparison ◽  
Position Estimation ◽  
Received Signal Strength Indicator ◽  
Simple Power ◽  
Distance Parameter

The classical rang-based technique for position estimation is still reliably used for indoor localization. Trilateration and multilateration, which include three or more references to locate the indoor object, are two common examples. These techniques use at least three intersection-locations of the references' distance and conclude that the intersection is the object's position. However, some challenges have appeared when using a simple power-to-distance parameter, i.e., received signal strength indicator (RSSI). RSSI is known for its fluctuated values when used as the localization parameter. The improvement of classical range-based has been proposed, namely min-max and iRingLA algorithms. These algorithms or methods use the approximation in a bounding-box and rings for min-max and iRingLA, respectively. This paper discusses the comparison performance of min-max and iRingLA with multilateration as the classical method. We found that min-max gives the best performance, and in some positions, iRingLA gives the best accuracy error. Hence, the approximation method can be promising for indoor localization, especially when using a simple and straightforward RSSI parameter.

The Location Algorithm Based on Square-Root Cubature Kalman Filter

2013 ◽  
Vol 325-326 ◽  
pp. 1525-1529
Author(s):  
Ying Liu ◽  
Jun Feng Su ◽  
Ming Qiang Zhu
Keyword(s):  
Kalman Filter ◽  
Indoor Localization ◽  
Signal Strength ◽  
Estimation Algorithm ◽  
Received Signal Strength ◽  
Square Root ◽  
Received Signal Strength Indicator ◽  
Cubature Kalman Filter ◽  
Wireless Signal ◽  
Parameter Estimation Algorithm

When wireless signal is used for indoor localization, there is no consistent relationship between signal strength received by the receiving nodes and distance from the receiving nodes to the receiving nodes, so there is a larger localization error for the Received Signal Strength Indication (RSSI) in the indoor environment. A new received signal strength indicator parameter estimation algorithm based on square-root cubature kalman filter is proposed in this paper, this algorithm utilizes Square-root Cubature Kalman filter (SCKF) to estimate the target’s position and the RSSI channel attenuation parameter simultaneously. The experimental results demonstrate that there is a better accuracy for the algorithm based on SCKF than the traditional method.

KAJIAN KEKUATAN SINYAL RADIO (RSSI) XBEE DALAM RANGKA PEMASANGAN LANDSLIDE EARLY WARNING SYSTEM (LEWS) DI KABUPATEN GARUT, TASIKMALAYA DAN MAJALENGKA

2019 ◽  
Vol 3 (2) ◽  
pp. 88
Author(s):  
Riski Fitriani
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Signal Strength ◽  
Received Signal Strength ◽  
Received Signal Strength Indicator ◽  
Landslide Early Warning ◽  
Point To Point

Salah satu inovasi untuk menanggulangi longsor adalah dengan melakukan pemasangan Landslide Early Warning System (LEWS). Media transmisi data dari LEWS yang dikembangkan menggunakan sinyal radio Xbee. Sehingga sebelum dilakukan pemasangan LEWS, perlu dilakukan kajian kekuatan sinyal tersebut di lokasi yang akan terpasang yaitu Garut, Tasikmalaya, dan Majalengka. Kajian dilakukan menggunakan 2 jenis Xbee yaitu Xbee Pro S2B 2,4 GHz dan Xbee Pro S5 868 MHz. Setelah dilakukan kajian, Xbee 2,4 GHz tidak dapat digunakan di lokasi pengujian Garut dan Majalengka karena jarak modul induk dan anak cukup jauh serta terlalu banyak obstacle. Topologi yang digunakan yaitu topologi pair/point to point, dengan mengukur nilai RSSI menggunakan software XCTU. Semakin kecil nilai Received Signal Strength Indicator (RSSI) dari nilai receive sensitivity Xbee maka kualitas sinyal semakin baik. Pengukuran dilakukan dengan meninggikan antena Xbee dengan beberapa variasi ketinggian untuk mendapatkan kualitas sinyal yang lebih baik. Hasilnya diperoleh beberapa rekomendasi tinggi minimal antena Xbee yang terpasang di tiap lokasi modul anak pada 3 kabupaten.

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