The combination of GPS measurements with the dynamic model via a Kalman filter or an extended Kalman filter, also known as GPS based reduced dynamic orbit determination (RDOD) techniques, have been widely used for accurate and real time navigation of satellites in low earth orbit (LEO). In previous studies, the GPS measurement noise variance is empirically taken as a constant, which is not reasonable because of insufficient prior information or dynamic environment. An improper estimate of the measurement noise may lead to poor performance or even divergence of the filter. In this letter, an adaptive extended Kalman filter (AEKF)-based approach using GPS dual-frequency pseudo-range measurements is presented, where the GPS pseudo-range measurement noise variance is adaptively estimated by the Carrier to Noise Ratio (C/N0) from the tracking loop of GPS receiver. The simulation results show that the proposed AEKF approach can achieve apparent improvements of the position accuracy and almost brings no extra computational burdens for satellite borne processor.

A simple robust finite-time convergent observer is presented in the presence of unknown input disturbance and measurement noise. In order to achieve the robust estimation and ensure the finite-time convergence, the proposed observer is constructed by using a multiple integral observer scheme in a hybrid system framework. Comparative computer simulations and laboratory experiments have been performed to test the effectiveness of the proposed observer.

In this letter, we consider the ultimate boundedness of the singularly perturbed system with measurement noise. The composite controller is commonly used to regulate the singularly perturbed system. However, in the presence of measurement noise, the composite controller does not guarantee the ultimate boundedness of the singularly perturbed system. Thus, we propose the modified composite controller to show the ultimate boundedness of the singularly perturbed system with measurement noise.

This paper proposes a robust state observer for multi-input multi-output LTI systems. Unknown inputs of polynomial form and high-frequency measurement noises are considered in the system model. The unknown inputs and the noises are not in the same form. Multiple integrations of both the observer error signal and the measurement output are used for the observer design. The existence condition of the proposed observer is shown to be the same as that of the proportional-integral (PI) observer. Computer simulations show the effectiveness of the proposed observer.