Fault diagnosis is a critical task for autonomous operation of systems such as spacecraft and planetary rovers, and must often be performed on-board. Unfortunately, these systems frequently also have relatively little computational power to devote to diagnosis. For this reason, algorithms for these applications must be extremely efficient, and preferably anytime. In this paper we introduce the ...

In this work, the problem of detecting and tracking targets with synthetic aperture radars is considered. A novel approach in which prior knowledge on target motion is assumed to be known for small patches within the field of view. Probability densities are derived as priors on the moving target signature within backprojected SAR images, based on the work of Jao. Furthermore, detection and trac...

Under high dynamic situation, the typical GPS carrier tracking loop cannot guarantee a reliable tracking. In this paper an improved high dynamic carrier tracking method based on unscented Kalman filter is presented, a rapid frequency traction method is adopted to ensure that the filter can convergence quickly, and joining a carrier amplitude estimation method. The U.S Jet Propulsion Laboratory ...

This paper describes how a constrained nonlinear least-squares optimization approach can be used to recover the configuration of the segments in an arbitrary mechanical system from motion capture data. By appending the difference between markers in the model and the measured marker trajectories to the set of kinematic constraint equations, a set of over-determinate nonlinear equations will be o...

this paper studies the use of unscented kalman filters (ukf) to estimate nonlinear dynamics and, specifically, adaptive determination of scaling parameters in these filters. due to lack of analytic solution and use of numerical methods instead, the computational load of these filters increases drastically. in this paper, a new method is proposed based on interactive multiple models (imm) which ...

MOTIVATION Traditional models of systems biology describe dynamic biological phenomena as solutions to ordinary differential equations, which, when parameters in them are set to correct values, faithfully mimic observations. Often parameter values are tweaked by hand until desired results are achieved, or computed from biochemical experiments carried out in vitro. Of interest in this article, i...

Recurrent neural networks, in contrast to the classical feedforward neural networks, better handle inputs that have spacetime structure, e.g. symbolic time series. Since the classic gradient methods for recurrent neural network training on longer input sequences converge very poorly and slowly, the alternative approaches are needed. We describe the principles of the training method with the Ext...

In the normal operation conditions of a pico satellite, conventional Unscented Kalman Filter (UKF) gives sufficiently good estimation results. However, if the measurements are not reliable because of any kind of malfunction in the estimation system, UKF gives inaccurate results and diverges by time. This study, introduces Robust Unscented Kalman Filter (RUKF) algorithms with the filter gain cor...