A Nonlinear Tracker Using Attitude Measurements

The subject of this paper involves tracking the present position of a maneuvering aircraft as well as predicting its future position. A tracking filter is developed that uses aircraft attitude angles (yaw, pitch, roll) in addition to the usual radar measurements. Computer simulation of tracker performance when tracking violently maneuvering aircraft indicates that a dramatic improvement is obtained by using attitude information. The approach taken is to develop a 12-or 15-state extended Kalman filter that models both translational and rotational degrees of freedom. By measuring and estimating attitude it is possible to approximately determine the magnitude and direction of the force system acting on the vehicle and therefore determine vehicle linear acceleration. Knowledge of acceleration is then used to improve the estimate of present and future position of the vehicle being tracked. Simulation of a T-38 aircraft performing a 5 g turn indicates that the new tracker produces maximum trajectory prediction errors that are 36 percent of the errors experienced by more conventional trackers.     

Steady state analysis for discrete tracking filters

An analysis of a discrete constant-gain α-β-γ tracking filter is presented. Steady-state tracking filter gains are determined without solving a discrete matrix Ricatti equation. Explicit closed-form gain solutions are found as a function of the roots to a cubic equation. Gain variations as a function of process noise, measurement noise, and sampling time are investigated     

Remote sensing using GNSS signals: Current status and future directions

The refracted, reflected and scattered signals of global navigation satellite systems (GNSS) have been successfully used to remotely sense the Earth’s surface and atmosphere. It has demonstrated its potential to sense the atmosphere and ionosphere, ocean, land surfaces (including soil moisture) and the cryosphere. These new measurements, although in need of refinement and further validation in many cases, can be used to complement existing techniques and sensors, e.g., radiosonde, ionosonde, radar altimetry and synthetic aperture radar (SAR). This paper presents the current status and new developments of remote sensing using GNSS signals as well as its future directions and applications. Some notable emerging applications include monitoring sea ice, dangerous sea states, ocean eddy and storm surges. With the further improvement of the next generation multi-frequency GNSS systems and receivers and new space-based instruments utilizing GNSS reflections and refractions, new scientific applications of GNSS are expected in various environment remote sensing fields in the near future.