As a speed feedback element in the servo stabilization system, the noise and random drift of the gyroscope have a direct impact on the accuracy and dynamic performance of the system. This paper proposes a correction method which introduces encoder angle increment into speed closed loop to optimize the drift performance. Combined with the method of least squares forward prediction, it eliminates the dynamic hysteresis caused by Kalman filtering for gyro noise. The engineering verification shows that the drift error is suppressed effectively and the dynamic performance of the servo stabilization system is greatly improved. © 2018 IEEE
In this paper, the performance of two Kalman filter (KF) schemes based on the direct estimated model...
We present an adaptive algorithm for a system integrated with micro-electro-mechanical systems (MEM...
The main disadvantage of an Inertial Navigation System is a low accuracy due to noise, bias, and dri...
A primary cause of degraded performance in pointing and tracking systems is the jitter in the line o...
A new random drift model and the measured angular rate model of MEMS gyro are presented. Based on su...
In this chapter, a low-cost micro electro mechanical systems (MEMS) gyroscope drift is modeled by ti...
A two-axis gimbal system can be used for stabilizing platform equipped with observation system like ...
In this paper, a novel approach for processing the outputs signal of the microelectromechanical syst...
In this paper an improvement in method is proposed for the compensation of the bias drift in microme...
The article refers to the accelerometer sensor and gyro sensor, and the phenomenon of \"drift\" whic...
An improved double-factor adaptive Kalman filter called AMA-RWE-DFAKF is proposed to denoise fiber o...
Motion sensors such as MEMS gyroscopes and accelerometers are characterized by a small size, light w...
In recent years the development of high speed, airborne, digital computers has made possible the app...
The random drift of a micro-electromechanical system (MEMS) gyroscope seriously affects its measurem...
In servo systems, encoders are usually used to measure the position and speed signals of electric ma...
In this paper, the performance of two Kalman filter (KF) schemes based on the direct estimated model...
We present an adaptive algorithm for a system integrated with micro-electro-mechanical systems (MEM...
The main disadvantage of an Inertial Navigation System is a low accuracy due to noise, bias, and dri...
A primary cause of degraded performance in pointing and tracking systems is the jitter in the line o...
A new random drift model and the measured angular rate model of MEMS gyro are presented. Based on su...
In this chapter, a low-cost micro electro mechanical systems (MEMS) gyroscope drift is modeled by ti...
A two-axis gimbal system can be used for stabilizing platform equipped with observation system like ...
In this paper, a novel approach for processing the outputs signal of the microelectromechanical syst...
In this paper an improvement in method is proposed for the compensation of the bias drift in microme...
The article refers to the accelerometer sensor and gyro sensor, and the phenomenon of \"drift\" whic...
An improved double-factor adaptive Kalman filter called AMA-RWE-DFAKF is proposed to denoise fiber o...
Motion sensors such as MEMS gyroscopes and accelerometers are characterized by a small size, light w...
In recent years the development of high speed, airborne, digital computers has made possible the app...
The random drift of a micro-electromechanical system (MEMS) gyroscope seriously affects its measurem...
In servo systems, encoders are usually used to measure the position and speed signals of electric ma...
In this paper, the performance of two Kalman filter (KF) schemes based on the direct estimated model...
We present an adaptive algorithm for a system integrated with micro-electro-mechanical systems (MEM...
The main disadvantage of an Inertial Navigation System is a low accuracy due to noise, bias, and dri...