Generic multisensor multitarget bias estimation architecture

Abstract

Current bias estimation algorithms for air traffic control (ATC) surveillance are focused on radar sensors, but the integration of new sensors (especially automatic dependent surveillance-broadcast and wide area multilateration) demands the extension of traditional procedures. This study describes a generic architecture for bias estimation applicable to multisensor multitarget surveillance systems. It consists on first performing bias estimations using measurements from each target, of a subset of sensors, assumed to be reliable, forming track bias estimations. All track bias estimations are combined to obtain, for each of those sensors, the corresponding sensor bias. Then, sensor bias terms are corrected, to subsequently calculate the target or sensor-target pair specific biases. Once these target-specific biases are corrected, the process is repeated recursively for other sets of less reliable sensors, assuming bias corrected measures from previous iterations are unbiased. This study describes the architecture and outlines the methodology for the estimation and the bias estimation design processes. Then the approach is validated through simulation, and compared with previous methods in the literature. Finally, the study describes the application of the methodology to the design of the bias estimation procedures for a modern ATC surveillance application, specifically for off-line assessment of ATC surveillance performance.

ATC trajectory reconstruction for automated evaluation of sensor and tracker performance

“…C The new opportunity traffic trajectory reconstruction module performs association, sensor bias (systematic error) estimation and correction [19], and trajectory interpolation. This kind of offline action operates on previously recorded target reports and tracks from SCDB and also saves its results (reconstructed reference tra- SASS-C surveillance assessment architecture.…”

“…Additional details on the bias calculation algorithms can be found in [27] and [19]. They were designed in a modular way so that a change in the processing order can be performed for future versions of OTR.…”

Improving Bias Estimation Precision via a More Accuracy Radar Bias Model

“…Great efforts have been made by Besada to establish a more precise bias model for sensor registration. In [10], the errors are divided into three parts, which are sensor-related bias that has the same value independently of the target, target-related bias, which is equal for every sensor of the same type, independent of the sensor, and sensor-target pair-related bias, which is different for each sensor-target pair. Most of the studies above focus on the sensor-related biases and neglect the importance of the target-related biases.…”

Model-based trajectory reconstruction with IMM smoothing and segmentation

“…This permits to take advantage of the adaptability of variable structure IMM filters with respect to uncertainty in the maneuvering state, while exploiting the computed sequence of MoF, and therefore taking advantage of the regularity of maneuvers of commercial aircraft. The reconstruction process also exploits kinematic measurements when available (using ADS-B or Mode S Enhanced Surveillance ADD [1,25]). …”