Design of vehicle position tracking system using short message services and its implementation on FPGA

Author(s):  
Arias Tanti Hapsari ◽  
E.Y. Syamsudin ◽  
Imron Pramana
Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 35
Author(s):  
Jae-Min Shin ◽  
Yu-Sin Kim ◽  
Tae-Won Ban ◽  
Suna Choi ◽  
Kyu-Min Kang ◽  
...  

The need for drone traffic control management has emerged as the demand for drones increased. Particularly, in order to control unauthorized drones, the systems to detect and track drones have to be developed. In this paper, we propose the drone position tracking system using multiple Bluetooth low energy (BLE) receivers. The proposed system first estimates the target’s location, which consists of the distance and angle, while using the received signal strength indication (RSSI) signals at four BLE receivers and gradually tracks the target based on the estimated distance and angle. We propose two tracking algorithms, depending on the estimation method and also apply the memory process, improving the tracking performance by using stored previous movement information. We evaluate the proposed system’s performance in terms of the average number of movements that are required to track and the tracking success rate.


Sensors ◽  
2018 ◽  
Vol 18 (4) ◽  
pp. 939 ◽  
Author(s):  
Safa Ouerghi ◽  
Rémi Boutteau ◽  
Xavier Savatier ◽  
Fethi Tlili

Author(s):  
V. L. Satyanarayana ◽  
R V S K Vyshnavi ◽  
Sk Nagoor Basha ◽  
Manoja Sagiri ◽  
L Siva Sai Prasad

Sensors ◽  
2020 ◽  
Vol 20 (15) ◽  
pp. 4126 ◽  
Author(s):  
Taeklim Kim ◽  
Tae-Hyoung Park

Detection and distance measurement using sensors is not always accurate. Sensor fusion makes up for this shortcoming by reducing inaccuracies. This study, therefore, proposes an extended Kalman filter (EKF) that reflects the distance characteristics of lidar and radar sensors. The sensor characteristics of the lidar and radar over distance were analyzed, and a reliability function was designed to extend the Kalman filter to reflect distance characteristics. The accuracy of position estimation was improved by identifying the sensor errors according to distance. Experiments were conducted using real vehicles, and a comparative experiment was done combining sensor fusion using a fuzzy, adaptive measure noise and Kalman filter. Experimental results showed that the study’s method produced accurate distance estimations.


2019 ◽  
Vol 1363 ◽  
pp. 012002 ◽  
Author(s):  
Oktaf B Kharisma ◽  
A A Dzikra ◽  
Mustakim ◽  
Rian Vebrianto ◽  
Rice Novita ◽  
...  

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