Separation of Space-based ADS-B Signals with Single Channel for Small Satellite

Yu, Sunquan; Li-hu, Chen; Li, Songting; Lanmin, Li

doi:10.1109/siprocess.2018.8600464

Cited by 10 publications

(6 citation statements)

References 7 publications

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“…To ensure the correct reception probability with no less than 90 %, the space-based ADS-B receiver should be able to separate at least six overlapping signals. However, most of the existing ADS-B signal separation methods (Yu et al, 2018;Zhang et al, 2019) can only effectively separate two or three overlapping signals, only the EPA (Petrochilos et al, 2009) can separate multiple overlapping signals, but it can only separate four overlapping signals with high precision.…”

Section: High Probability Of Multiple Overlapping Signalsmentioning

confidence: 99%

“…However, there may be a few overlapping signals under a single beam, and the DDOA is too small to separate these signals (Bettray et al, 2013;Yu et al, 2019). The second approach is based on a single antenna (Galati et al, 2015;Yu et al, 2018;Zhang, 2018). They utilise time-frequency analysis methods to separate the overlapped signals based on the frequency shifts between them.…”

Section: Introductionmentioning

confidence: 99%

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

Jia

2023

J. Navigation

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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.

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Section: High Probability Of Multiple Overlapping Signalsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

Jia

2023

J. Navigation

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“…Depending on algorithm principle, traditional separation methods can be classified into three categories for single antenna-based ADS-B signal separation. For the first approach Wu et al (2017); Yu et al (2018); Li et al (2021), the power difference between overlapping signals is used to separate ADS-B signals. However, this approach is limited to small power difference between overlapping signals.…”

Section: Introductionmentioning

confidence: 99%

Independently Convolutional Gated Recurrent Neural Unit for Space based ADS-B Signal Separation with Single Antenna

2023

Preprint

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Automatic Dependent Surveillance-Broadcast (ADS-B) is a critical technology to transform aircraft navigate through improving safety, efficiency, and overall effectiveness in the aviation industry. However, ADS-B signal overlapping is a large challenge, especially for space-based ADS-B system. The existing traditional methods cannot effectively separate overlapping signals with small difference such as power difference, carrier frequency difference. To solve this problem, we propose Independently Convolutional Gated Recurrent Neural Unit (Ind-CGRU) to build the encoder-decoder network. And Ind-CGRU explores the more temporal relationship of ADS-B signal to generate effective separation mask and improves the ADS-B signal separation performance. Experimental results on SRADSB dataset, demonstrate that the proposed Ind-CGRU achieves the good performance.

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“…Thus only one message will be received correctly under mild conditions and the surveillance capacity will be reduced [17]. Yu [18] introduced anomaly doubt degree to calculate signal overlap time delay and adopted adaptive threshold technology based on power difference to separate ADS-B signal when the overlap signal is relatively large. Lu [19] proposed a single antenna overlap signal separation method based on empirical mode decomposition and independent component analysis.…”

Section: Introductionmentioning

confidence: 99%

A Reliable Separation Algorithm of ADS-B Signal Based on Time Domain

Li¹,

Kang²,

Ren³

et al. 2021

IEEE Access

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With the development of Aerospace Science and technology, automatic dependent surveillance-broadcast has become a core technique in the field of air surveillance. Installing ADS-B receiver on LEO satellite can solve the problem of small coverage of ground receiver, to realize global coverage and monitoring. However, the satellite ADS-B system is faced with serious collision and overlap problems, which has a serious impact on the signal decoding, leading to the wrong decoding or even loss of important information. In this paper, a time-domain ADS-B blind signal separation algorithm is proposed. When there is a certain power difference between the two source signals, the overlap signals are offset by the high-power signal and low-power signal to get the corresponding cancellation signals. According to the superposition mode of different pulses, different bit decision results are obtained according to the amplitude, to recover the source signal. Simulations demonstrate that the proposed algorithm is feasible and has a lower bit error rate.

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Separation of Space-based ADS-B Signals with Single Channel for Small Satellite

Cited by 10 publications

References 7 publications

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

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

Independently Convolutional Gated Recurrent Neural Unit for Space based ADS-B Signal Separation with Single Antenna

A Reliable Separation Algorithm of ADS-B Signal Based on Time Domain

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