Signal Conditioning of Low-Cost Gyroscope Using Kalman Filter and Nonlinear Least Square Method

Abstract

Gyroscopes are important sensors in motion control in equipment such as airplanes, missiles and Segway. Low-cost gyroscopes have problems in signals such as bias, noise and scaling factor that decrease the efficiency of motion control. Therefore this paper is to present signal conditioning of low-cost gyroscopes using a Kalman filter to remove unwanted noise and nonlinear least square method to estimate parameters for compensation errors to the model by comparison with the encoder. The experimental results is shown that Kalman filter and nonlinear least square method can be used in signal conditioning of low-cost gyroscope for a more accurate signal.

An Efficient Hybrid Technique for Noise Reduction in Optical Gyroscope Signals

“…5, removing the noise by using Kalman filtering, we compensate for the errors by computing the parameters using nonlinear least squares method. We compare the encoder with the signal of the gyroscope [25].…”