An eLoran Signal Cycle Identification Method Based on Joint Time–Frequency Domain

Abstract

The eLoran system is an international standardized positioning, navigation, and timing service system, which can complement global navigation satellite systems to cope with navigation and timing warfare. The eLoran receiver measures time-of-arrival (TOA) through cycle identification, which is key in determining timing and positioning accuracy. However, noise and skywave interference can cause cycle identification errors, resulting in TOA-measurement errors that are integral multiples of 10 μs. Therefore, this article proposes a cycle identification method in the joint time–frequency domain. Based on the spectrum-division method to determine the cycle identification range, the time–domain peak-to-peak ratio and waveform matching are used for accurate cycle identification. The performance of the method is analyzed via simulation. When the signal-to-noise ratio (SNR) ≥ 0 dB and skywave-to-groundwave ratio (SGR) ≤ 23 dB, the success rate of cycle identification is 100%; when SNR ≥ −13 dB and SGR ≤ 23 dB, the success rate exceeds 75%. To verify its practicability, the method was implemented in the eLoran receiver and tested at three test sites within 1000 km using actual signals emitted by an eLoran system. The results show that the method has a high identification probability and can be used in modern eLoran receivers to improve TOA-measurement accuracy.

Pseudorange reconstruction for high‐dynamic eLoran signal simulators using B‐spline interpolation

“…The signals of the eLoran system are modulated by the Eurofix way [5, 12]. The system time is also synchronised with Coordinated Universal Time (UTC).…”

“…The Global Navigation Satellite System is a crucial infrastructure that users worldwide rely on for Positioning, Navigation and Timing (PNT) [1][2][3][4]. However, the system is vulnerable to threat and interference, with numerous cases of human interference have been reported [5,6]. As a result, there is an urgent need to find a system that is highly resistant to interference [7,8].…”

High‐precision simulation technology for enhanced Loran signal simulators based on Lagrange farrow structure filter

“…[26], a method of noise n(t) simulation was proposed and we advise applying this method in the simulator, our research focuses on doing the time-varying D m (t) generation technique. In PNT applications, the receiver usually completes timing based on TOA, and then calculates the pseudo-range for position and navigation [6,7]. Therefore, TOA is simulated with high accuracy that is a key technology in the signal simulator, which ensures that the equipment is accurately verified.…”

“…Many countries (such as the South Korea [2], China [5]) have upgraded to eLoran system and are using it. In this system, the receiver is the key equipment used by the user segment, and its performance in complex environments is critical [6][7][8]. Therefore, the receiver performance is needed to test in a laboratory environment.…”

Research on an Alpha Navigation Signal Detection Method Based on Multichannel Orthogonal Correlation

“…The weaknesses of Global Navigation Satellite Systems (GNSSs) include weak signals, poor penetration ability, susceptibility to interference, poor anti-interference ability, and an inability to enter water. The sole reliance on a GNSS for navigation and timing carries serious risks [11][12][13]. However, VLF and satellite signals have significant differences in operating frequency (low-and high-frequency), operating mode (land-and satellite-based), and signal strength (high-and low-level).…”