Satellite-pose estimation using IMU sensor data and Kalman filter with RF-433 Mhz powered communication and helical antenna design for ground station

Abstract

Space research relies heavily on satellites, and technological developments are critical to the success of these missions. In order to estimate satellite pose, a simulation of an IMU sensor using Matplotlib is presented in this study. A roll, pitch, and yaw value analysis is performed on data obtained from the BNO-055 IMU sensor. A prototype ground station's helical antenna is used to investigate these parameters. For effective communication between the satellite body and ground station setup, a low-cost transceiver module RF-433Mhz module is connected to the ground station. IMUsensors are essential for inertial measurements in spacecraft, which support ground station monitoring. This study makes use of a four-turn helical antenna that is built for deployment and designed using the 4nec2 simulation program for RF-based satellite-ground station communication. The antenna's VSWR is 1.432, and its directivity is 18.581. Matplotlib is utilized to model variations in roll, pitch, and yaw values. Roll, pitch, and yaw ranges that are observed are −0.375 to 0.25, −0.375 to 0.5625, and −0.3125 to 0.1875, in that order. These ranges are useful in effectively visualizing the body pose of the CubeSat when connecting via PySerial to a Matplotlib-developed program.

Keywords

• Helical antenna
• RF433
• CubeSat
• Bno-055
• Kalman filter