Airport based bias estimation of surface movement radars

Abstract

In this proposal, a real time bias estimation system for an airport surveillance data fusion system is presented. This bias estimation system is divided in two main parts. The first part estimates SMR bias terms, taking advantage of the knowledge of the airport map, which is useful because aircraft usually follow the axis of airport taxiways. The other part makes use of SMR corrected measures, which can be assumed to be unbiased. Using them, bias estimators for other important surface surveillance sensors are defined. These estimators are based on processing differences of measurement taken from each sensor and from the SMR. As simulation results show, if the sensor error models are precise enough, both estimations converge to the real bias values, and therefore unbiased measures may be obtained. These unbiased measurements should be provided to the fusion system, in order to enhance tracking performance. These estimation processes do not represent an important computer load increase for the data fusion system. The performance improvement in tracking is also presented.

Measurement Bias Estimation in the Problem of Target Tracking

“…There are mainly two directions for dealing with the bias. First, the bias is corrected and then the unbiased measurements are fused to deduce target trajectory, e.g., in the application of the airport surveillance data fusion system [3,4]. Second, the biased measurements are directly fused into tracking system and the bias is estimated together with target trajectory.…”

Piezoelectric sensors for taxiway airport traffic control system

“…With the popularity in flying, there is a big demand for new and more safety requirements over the taxiway airport traffic control system [6][7][8].…”