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Application of the List Viterbi Algorithm for Satellite-based AIS Detection

Linda Kanaan, Karine Amis, Frédéric Guilloud, Rémi Chauvat

TL;DR

This work tackles the challenge of detecting AIS messages in satellite reception under heavy collision risk by leveraging the CRC in AIS frames. It introduces the Parallel List Viterbi Algorithm (PLVA) to generate multiple candidate sequences and uses CRC-based post-processing, evaluated with both coherent MLSE-CPM and optimized differential MLSE detectors on AWGN and multi-user channels. Results show significant PER reductions and performance approaching the joint MLSE bound, with practical parameter optimizations that balance gains and complexity, and system-level simulations indicating throughput improvements under realistic loads. The findings suggest PLVA can enhance AIS decoding thresholds and strengthen interference cancellation capabilities in satellite AIS systems, enabling more reliable and scalable global maritime tracking.

Abstract

Satellites receiving Automatic Identification System (AIS) packets in dense areas are particularly prone to AIS channel overload due to the extensive number of vessels. Thus a failure of detection might be caused by the collisions among AIS messages. To improve the detection capability, we propose to exploit the presence of the cyclic redundancy check (CRC) in AIS frames by using the parallel list Viterbi algorithm (PLVA) instead of the classical Viterbi algorithm (VA) often used for decoding AIS signals. The performance of combining the PLVA with AIS post processing including the CRC is studied with two detectors, one coherent and the other differential, in two channel models: a single-user AWGN channel and a more realistic multiple-access AIS channel. We also show the impact of the PLVA parameters on the success recovery rate. The simulation results show that the resulting procedure can significantly improve the packet error rate (PER) at the cost of a limited increase of the computational complexity. The proposed technique could be applied to improve the performance of interference cancellation receivers by significantly lowering the AIS decoding threshold.

Application of the List Viterbi Algorithm for Satellite-based AIS Detection

TL;DR

This work tackles the challenge of detecting AIS messages in satellite reception under heavy collision risk by leveraging the CRC in AIS frames. It introduces the Parallel List Viterbi Algorithm (PLVA) to generate multiple candidate sequences and uses CRC-based post-processing, evaluated with both coherent MLSE-CPM and optimized differential MLSE detectors on AWGN and multi-user channels. Results show significant PER reductions and performance approaching the joint MLSE bound, with practical parameter optimizations that balance gains and complexity, and system-level simulations indicating throughput improvements under realistic loads. The findings suggest PLVA can enhance AIS decoding thresholds and strengthen interference cancellation capabilities in satellite AIS systems, enabling more reliable and scalable global maritime tracking.

Abstract

Satellites receiving Automatic Identification System (AIS) packets in dense areas are particularly prone to AIS channel overload due to the extensive number of vessels. Thus a failure of detection might be caused by the collisions among AIS messages. To improve the detection capability, we propose to exploit the presence of the cyclic redundancy check (CRC) in AIS frames by using the parallel list Viterbi algorithm (PLVA) instead of the classical Viterbi algorithm (VA) often used for decoding AIS signals. The performance of combining the PLVA with AIS post processing including the CRC is studied with two detectors, one coherent and the other differential, in two channel models: a single-user AWGN channel and a more realistic multiple-access AIS channel. We also show the impact of the PLVA parameters on the success recovery rate. The simulation results show that the resulting procedure can significantly improve the packet error rate (PER) at the cost of a limited increase of the computational complexity. The proposed technique could be applied to improve the performance of interference cancellation receivers by significantly lowering the AIS decoding threshold.

Paper Structure

This paper contains 18 sections, 13 equations, 4 figures, 1 table.

Table of Contents

  1. Introduction
  2. System Model
  3. AIS access protocol
  4. AIS packet
  5. Transmission Signal Model
  6. Received Signal Model
  7. Detection for Space-based AIS
  8. Maximum Likelihood Sequence Estimation Principle
  9. Coherent MLSE-Detector of CPM
  10. Optimized Differential MLSE-Detector
  11. Parallel List Viterbi Algorithm for AIS Signal Decoding
  12. Principle
  13. Algorithm
  14. Numerical Results
  15. Detection in a single-user AWGN channel
  16. ...and 3 more sections

Figures (4)

  • Figure 1: AIS packet
  • Figure 2: Cumulative Metrics of the PLVA
  • Figure 3: Effect of PLVA application with the coherent and optimized differential detectors on the probability of detection in a single-user AWGN channel with varying $(P,C)$ values compared to two state-of-the-art AIS coherent receivers jointMLSEthreezones2.
  • Figure 4: Throughput as a function of the offered load, considering Coherent detection using the VA and PLVA with $(P,C)=(64,256)$ and usual Differential detection with $K=1$ using the VA taken as a lower bound.