Improved ASM-TER Training Sequence Detection and Fine Doppler Frequency Estimation Methods from a Satellite

Peixin Zhang,Jianxin Wang,Shushu Yang,Peng Ren,Haiwei Song

doi:10.1155/2020/3625184

Peixin Zhang, Jianxin Wang + Show 3 more

Open Access

https://doi.org/10.1155/2020/3625184

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Abstract

To detect terrestrial application-specific messages (ASM-TER) signals from a satellite, a novel detection method based on the fast computation of the cross ambiguity function is proposed in this paper. The classic cross ambiguity function’s computational burden is heavy, and we transform the classic cross ambiguity function to a frequency domain version to reduce the computational complexity according to Parseval’s theorem. The computationally efficient sliding discrete Fourier transform (SDFT) is utilized to calculate the frequency spectrum of the windowed received signal, from which the Doppler frequency could be estimated coarsely. Those subbands around the Doppler frequency are selected to calculate the ambiguity function for reducing the computational complexity. Furthermore, two local sequences with half length of the training sequence are utilized to acquire a better Doppler frequency tolerance; thus, the frequency search step is increased and the computational complexity could be further reduced. Once an ASM-TER signal is detected by the proposed algorithm, a fine Doppler frequency estimation could be obtained easily from the correlation peaks of the two local sequences. Simulation results show that the proposed algorithm shares almost the same performance with the classic cross ambiguity function-based method, and the computational complexity is greatly reduced. Simulation results also show that the proposed algorithm is more resistant to cochannel interference (CCI) than the differential correlation (DC) algorithm, and the performance of fine Doppler frequency estimation is close to that of the Cramér–Rao lower bound (CRLB).

Highlights

The automatic identification system (AIS) [1] is well recognized and accepted as an important tool for safety of navigation [2]
The very high frequency (VHF) data exchange system (VDES), which integrates the functions of VHF data exchange (VDE), application-specific messages (ASM) [4], and AIS, is developed to extend the existing AIS standard by the International Telecommunication Union (ITU) [5, 6]
This paper proposes a fast computation of the cross ambiguity function to detect an ASM-TER training sequence from a satellite

Summary

Introduction

The automatic identification system (AIS) [1] is well recognized and accepted as an important tool for safety of navigation [2]. To detect ASM-TER signals from a satellite with excellent performance and acceptable computational complexity, this paper proposes a computational complexity reduced algorithm based on the cross ambiguity function. The idea behind it is to reduce the frequency search range and increase the frequency search step for evaluating the cross ambiguity function. To reduce the frequency search range, the classic cross ambiguity function is transformed to a frequency domain version, in which the frequency spectra of the windowed received signal and the local sequence are used.

Signal Model

Classic Cross Ambiguity Function

The Proposed Algorithm

Simulation and Analysis

Findings

Conclusions