TY - GEN
T1 - An Enhanced Error Correction Algorithm Combined with Directed Density-Based Clustering for Satellite-Based ADS-B Signals
AU - Jian, Xinhui
AU - Zhang, Xuejun
AU - Zhang, Weidong
N1 - Publisher Copyright:
© 2024, Chinese Society of Aeronautics and Astronautics.
PY - 2024
Y1 - 2024
N2 - The minimum Hamming distance of satellite-based Automatic Dependent Surveillance-Broadcast (ADS-B) signals at low signal-to-noise ratios (SNRs) is only 6, which is inadequate to meet airspace surveillance requirements in terms of packet decoding probability (PD). An enhanced error correction algorithm combined with directed density-based clustering for satellite-based ADS-B signals is proposed to address this phenomenon, and its performance is verified by simulation. Firstly, the density-based clustering model will cluster a given signal sequence according to its partial minimum Hamming distance from other sequences, reducing the chance of undetectable errors. Secondly, the proposed error syndrome matrix built offline streamlines the Brute Force correction, preserving on-star resources. Finally, the {a, b} algorithm compensates for low SNR-induced unreliability of confidence arrays through error correction depth a and error correction capability b. The simulation results show that the {20, 10} error correction algorithm can achieve a PD of 86.4% at the minimum SNR of satellite-based ADS-B signals.
AB - The minimum Hamming distance of satellite-based Automatic Dependent Surveillance-Broadcast (ADS-B) signals at low signal-to-noise ratios (SNRs) is only 6, which is inadequate to meet airspace surveillance requirements in terms of packet decoding probability (PD). An enhanced error correction algorithm combined with directed density-based clustering for satellite-based ADS-B signals is proposed to address this phenomenon, and its performance is verified by simulation. Firstly, the density-based clustering model will cluster a given signal sequence according to its partial minimum Hamming distance from other sequences, reducing the chance of undetectable errors. Secondly, the proposed error syndrome matrix built offline streamlines the Brute Force correction, preserving on-star resources. Finally, the {a, b} algorithm compensates for low SNR-induced unreliability of confidence arrays through error correction depth a and error correction capability b. The simulation results show that the {20, 10} error correction algorithm can achieve a PD of 86.4% at the minimum SNR of satellite-based ADS-B signals.
KW - Density-Based Clustering
KW - Partial Minimum Hamming Distance
KW - Satellite-based ADS-B
UR - https://www.scopus.com/pages/publications/85180809549
U2 - 10.1007/978-981-99-8867-9_41
DO - 10.1007/978-981-99-8867-9_41
M3 - 会议稿件
AN - SCOPUS:85180809549
SN - 9789819988662
T3 - Lecture Notes in Mechanical Engineering
SP - 425
EP - 432
BT - Proceedings of the 6th China Aeronautical Science and Technology Conference - Volume 3
PB - Springer Science and Business Media Deutschland GmbH
T2 - 6th China Aeronautical Science and Technology Conference, CASTC 2023
Y2 - 26 September 2023 through 27 September 2023
ER -