Outdoor Localization System with Augmented State Extended Kalman Filter and Radio-Frequency Received Signal Strength

2019 ◽  
Author(s):  
Renan Maidana ◽  
Alexandre Amory ◽  
Aurelio Salton
Keyword(s):  
Kalman Filter ◽  
Radio Frequency ◽  
Extended Kalman Filter ◽  
Signal Strength ◽  
Received Signal Strength ◽  
Localization System ◽  
Augmented State ◽  
Outdoor Localization

scholarly journals A Novel Indoor Ranging Algorithm Based on a Received Signal Strength Indicator and Channel State Information Using an Extended Kalman Filter

2020 ◽  
Vol 10 (11) ◽  
pp. 3687 ◽  
Author(s):  
Jingjing Wang ◽  
Joon Goo Park
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Channel State Information ◽  
Signal Strength ◽  
Received Signal Strength ◽  
Cumulative Distribution ◽  
Estimation Accuracy ◽  
Channel State ◽  
Received Signal Strength Indicator ◽  
State Information

With the increasing demand of location-based services, the indoor ranging method based on Wi-Fi has become an important technique due to its high accuracy and low hardware requirements. The complicated indoor environment makes it difficult for wireless indoor ranging systems to obtain accurate distance measurements. This paper presents an Extended Kalman filter-based approach for indoor ranging by utilizing transmission channel quality metrics, including Received Signal Strength Indicator (RSSI) and Channel State Information (CSI). The proposed ranging algorithm scheme is implemented and validated with experiments in two typical indoor environments. A real indoor experiment demonstrates that the ranging estimation accuracy of our algorithms can be significantly enhanced compared with the typical algorithms. The ranging estimation accuracy is defined as the cumulative distribution function of the distance error.

scholarly journals Target Localization with Unknown Transmit Power and Path-Loss Exponent Using a Kalman Filter in WSNs

Sensors ◽  
2020 ◽  
Vol 20 (22) ◽  
pp. 6582
Author(s):  
SeYoung Kang ◽  
TaeHyun Kim ◽  
WonZoo Chung
Keyword(s):  
Kalman Filter ◽  
Path Loss ◽  
Target Position ◽  
Signal Strength ◽  
Received Signal Strength ◽  
Target Localization ◽  
Wireless Sensor ◽  
Transmit Power ◽  
Path Loss Exponent ◽  
Localization Algorithms

We present a novel hybrid localization algorithm for wireless sensor networks in the absence of knowledge regarding the transmit power and path-loss exponent. Transmit power and the path-loss exponent are critical parameters for target localization algorithms in wireless sensor networks, which help extract target position information from the received signal strength. In the absence of information on transmit power and path-loss exponent, it is critical to estimate them for reliable deployment of conventional target localization algorithms. In this paper, we propose a simultaneous estimation of transmit power and path-loss exponent based on Kalman filter. The unknown transmit power and path-loss exponent are estimated using a Kalman filter with the tentatively estimated target position based solely on angle information. Subsequently, the target position is refined using a hybrid method incorporating received signal strength measurements based on the estimated transmit power and path-loss exponent. Our proposed algorithm accurately estimates transmit power and path-loss exponent and yields almost the same target position accuracy as the simulation results confirm, as the hybrid target localization algorithms with known transmit power and path-loss exponent. Simulation results confirm the proposed algorithm achieves 99.7% accuracy of the target localization performance with known transmit power and path-loss exponent, even in the presence of severe received signal strength measurement noise.

scholarly journals Outdoor Localization for Returning of Quad-rotor using Cell Divide Algorithm and Extended Kalman Filter

2013 ◽  
Vol 17 (4) ◽  
pp. 440-445 ◽  
Author(s):  
Ki-Jung Kim ◽  
Yoon-Ki Kim ◽  
Seung-Hwan Choi ◽  
Jang-Myung Lee
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Outdoor Localization

scholarly journals Study on the Signal Transmission Characteristics of 2.4GHz Wireless Network in Dorms

2016 ◽  
Vol 12 (10) ◽  
pp. 58 ◽  
Author(s):  
Guoqiang Hu
Keyword(s):  
Radio Frequency ◽  
Wireless Network ◽  
Signal Transmission ◽  
Signal Strength ◽  
Received Signal Strength ◽  
Relational Model ◽  
Transmission Characteristics ◽  
Cubic Polynomial ◽  
Communication Distance

<p><span style="font-size: small;"><span style="font-family: Times New Roman;">In accordance with the deployment requirements of WLAN node in college student dorms and its features of application environment, this paper studies the relevance among factors like radio-frequency signal transmission characteristics, communication distance, AP height and transmission path, etc., with a case study of AP radio frequency 2.4GHz. Experiments show that the attenuation of wireless network signal in student dorms conforms to Keenan-Motley model. When AP is fixed, the signal strength received by laptop generally reduces with the increase of communication distance, yet just opposite with packet loss rate. When deploying AP, 1.25-1.75 height is ideal, and one-side coverage of 3 dorm rooms optimal. Based on the above researches, a relational model of AP height, communication distance and received signal strength is established. In it, model parameter  and AP height display a cubic polynomial relationship, and attenuation coefficient  and AP height show a quadratic polynomial relationship. Experiment results demonstrate that this model can satisfactorily predict the received signal strength of different AP heights and communication distances, providing technical support for wireless network deployment in student dorms. </span></span></p>

Sign in / Sign up

Export Citation Format

Share Document