Dynamic Height Measurement using Sonar Sensor Based on Single Dimension Kalman Filter in Embedded Controller

Abstract

The aim of this paper is to evaluate real-time accurateness of low-altitude height measurement using a single sonar sensor via Kalman filter algorithm in embedded controller. The function of the one dimension embedded Kalman filter of sonar sensor is to reduce and resolve the error of low altitude height measurement that produced from the sensor for mapping application. Series data of varied height measurement with Kalman filter was gathered and implemented using a 16-bit microcontroller unit. A structure model was constructed to allow for dynamic height measurement between ground surface and the sensor.The tabulated data are shown for comparison of accuracy and error analysis between both with Kalman and without Kalman filter. After several scanned surfaces and analysis of the recorded data, the technique shows the usefulness in height measurement application that used surface scan method which the sonar project to the ground such as UAV in order to reduce error of the detected varied height.

Indoor Drone Positioning: Accuracy and Cost Trade-Off for Sensor Fusion

“…Only the IMU data from the drone is used as the control input for the generic 6DoF rigid body motion equation. Additional sensors under test are the following: 1) Sonar at 50 Hz for height estimation as a cost-effective solution for stable indoor flight height estimation [30] since a barometer cannot be reliably used indoor. These sensors can be sensitive to dampening ground covering such as carpet, but this is less an issue in an industrial context.…”