Estimating radar azimuth jitter through analysis of targets of opportunity data

Mayer, Colin; Tzanos, Panos; Thompson, Steven; McCartor, Gerry

doi:10.1109/radar.2011.5960564

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Optimised Non-linear Curve Fitting1

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“…The second method was adapted from a technique previously used to characterise ground-based radar azimuth errors from data [11]. In that study, line segments were fitted to straight and level radar tracks and used as position truth.…”

Section: Optimised Non-linear Curve Fittingmentioning

confidence: 99%

Error model estimation for airborne beacon‐based surveillance

Panken

Kochenderfer

2014

IET Radar, Sonar & Navigation

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A next-generation aircraft collision avoidance system under development is designed to reduce unnecessary alerts while reducing the risk of mid-air collision. Current and future collision avoidance systems rely upon range, bearing and altitude information from airborne, beacon-based surveillance. Realistic models of surveillance error characteristics are needed in order to develop and certify the safety and performance of these systems. Prior models of bearing measurements assumed uncorrelated Gaussian noise. This study explains how hidden Markov models can be used to capture the time-correlated error characteristics exhibited by recorded surveillance data. Simulations show the impact of this higher-fidelity model on predicted collision avoidance performance.

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Section: Optimised Non-linear Curve Fittingmentioning

confidence: 99%