Abstract
Consumer-Grade global positioning system (GPS) is widely used in many domains. The obvious issue of this consumer-grade device is low accuracy and reading fluctuation results. In terms of using an application that requires a more precise location, the output could be difficult. In this study, the authors deploy various methods to reduce the global positioning system data fluctuation and present field test results. Two main types of the device worked together to collect data from global positioning systems, such as Microcontroller for algorithm processing and presenting data and global positioning system receivers for receiving data from a satellite. We combine three global positioning system modules to received signals in a single device and test calculated data compared with the Kalman filtering methods in many cases, including moving and static devices. Implementing the Standard Kalman Filter to multiple global positioning system Modules has improved the constancy of cheap global positioning system equipment. The experiment algorithm is presented significant improvement to overcome the retrieved data fluctuation problem. This study's contribution will enable creating a cheap global positioning system locator device for various applications that require more accuracy than the standard consumer-grade receiver.
Highlights
It is widely known that Global Positioning System or global positioning system (GPS) [1], which was invented during the 1960s–1970s, has been broadly used in several sectors such as service, academics, economics, and development
A Quadcopter drone could solely control the Hover Control System by itself using the Microcontroller and Inertial Measurement Unit (IMU), which could be found in general markets [7]
The first experiment was the estimation and improvement of GPS coordinates in UAV to be more stable via an algorithm called Kalman Filter (a command set estimating possible data via variance variables of sensors [13]) with GPS and Barometer based on PositionVelocity-Acceleration model [14]
Summary
It is widely known that Global Positioning System or GPS [1], which was invented during the 1960s–1970s, has been broadly used in several sectors such as service, academics, economics, and development. Kalman Filter is an algorithm used to estimate possible variables and lower the discrepancy of GPS. In consequence, it is making the inexpensive GPS locator for many projects that limited fund is complicated, for example, the guidance device in entree level drone, personal location device, and forest fire locator for the rescue team. The prototype has the limitation of hardware durability due to using a prototype grade sensor and Universal printed circuit board (PCB). This experiment aspires to present a new concept derives from combining two calculation techniques using different algorithms but sharing the same objectives. It is expected that this innovation is an alternative to better technological development
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