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Frontiers in Signal Processing
FSP > Volume 5, Number 2, April 2021

A Horizontal Tracking Algorithm Suitable for Airborne Collision Avoidance System

Download PDF  (259.1 KB)PP. 27-35,  Pub. Date:May 19, 2021
DOI: 10.22606/fsp.2021.52001

Author(s)
Yuchen Wang, Liangfu Peng
Affiliation(s)
College of Electronic Information, Southwest Minzu University, Chendu, China
College of Electronic Information, Southwest Minzu University, Chendu, China
Abstract
The horizontal tracker is essential for the reliable operation of the Airborne Collision Avoidance System (ACAS). In ACAS target tracking, for the non-linear state estimation problem of using sensor measurement values to track in Cartesian coordinates, this paper proposes a horizontal tracking algorithm based on the Augmented Unscented Kalman Filter (AUKF) to achieve the horizontal of the target. Accurate tracking of direction. Firstly, the tracking model of the relative horizontal state of the target aircraft is established, and then the data is processed by AUKF. In order to verify the effectiveness of the horizontal tracking algorithm, the computer simulation method is used to simulate the track of the local aircraft and the intruder in the horizontal direction, and noise is added to the measured values. The traditional Kalman Filter In Polar Coordinates (KFPC) and AUKF algorithm are used to filter the ACAS horizontal tracking. The simulation results show that AUKF can achieve more accurate target tracking.
Keywords
airborne collision avoidance system (ACAS); horizontal tracker; coordinate transformation; augmented unscented Kalman filter (AUKF)
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