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A high-precision and efficient algorithm for space-based ADS-B signal separation

Published online by Cambridge University Press:  16 June 2023

Yan Bi ,
Renbiao Wu  and
Qiongqiong Jia
Yan Bi
Affiliation:
School of Electrical and Information Engineering, Tianjin University, Tianjin, China Tianjin Key Lab for Advanced Signal Processing, Civil Aviation University of China, Tianjin, China
Renbiao Wu*
Affiliation:
Tianjin Key Lab for Advanced Signal Processing, Civil Aviation University of China, Tianjin, China
Qiongqiong Jia
Affiliation:
Tianjin Key Lab for Advanced Signal Processing, Civil Aviation University of China, Tianjin, China
*
Corresponding author: Renbiao Wu; Email: rbwu@cauc.edu.cn
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Abstract

Space-based automatic dependent surveillance-broadcast (ADS-B) receivers can cover thousands of aircraft, each transmitting 6 ⋅ 2 signals per second. As a result, ADS-B signals are very prone to overlap. When the number of aircraft covered by a receiver reaches 3,000, about 90 % of the signals will be overlapping. Overlapped signals can reduce the decoding accuracy of receivers, so that aircraft information cannot be accurately transmitted to the air traffic control (ATC) surveillance system, hence threatening aviation flight safety. It is necessary to propose signal separation algorithms for space-based ADS-B systems. An orthogonal projection linear constrained minimum variance (OPLCMV) algorithm is proposed, which can separate two signals simultaneously based on the linearly constrained minimum variance algorithm by exploiting the characteristics of overlapped signals. Compared with the state-of-the-art extended projection algorithm and the fast independent component analysis algorithm, the OPLCMV method has a higher decoding accuracy for multiple overlapping signals with a small direction difference of arrival or frequency shift. Moreover, the OPLCMV algorithm has a low computational complexity when the number of overlapped signal sources is less than seven.

Keywords

ADS-Bspace-based ADS-B systemarray antennasignal separation
Type
Research Article
Information
The Journal of Navigation , Volume 76 , Issue 4-5 , July 2023 , pp. 562 - 576
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Copyright
Copyright © The Author(s), 2023. Published by Cambridge University Press on behalf of The Royal Institute of Navigation

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