Shanhe Wang

Reliable performance monitoring is indispensable for FM broadcast time service systems, yet systematic evaluation and long-term operational data in practical scenarios remain scarce. This study addresses the gap and verifies the actual service capability of the FM broadcast time service system deployed in 10 key Chinese cities. We established a systematic monitoring model, applied the GUM to evaluate measurement uncertainty, and conducted continuous, multi-site monitoring and statistical analysis over 24 months. Results show the expanded measurement uncertainty of all stations ranges from 62.768 μs to 80.646 μs (k = 2), meeting the 100 μs requirement, and long-term monitoring confirms the system achieves sub-millisecond timing accuracy in practical operation. This work fills the gap in long-term operational data for FM broadcast timing technology, provides a standardized uncertainty evaluation method for the monitoring system, and lays a robust theoretical and data foundation for the technology’s optimization and wide adoption, thereby enhancing user confidence in FM broadcast time services.

To enhance the denoising performance of satellite signals at a low signal-to-noise ratio (SNR), we propose an improved wavelet threshold denoising correlation (IWTDC) method that utilizes wavelet decomposition to analyze the received satellite signals. By dynamically selecting the threshold based on the transformation of the wavelet coefficients of each layer, we reconstruct the signal using processed coefficients for effective denoising. To validate the denoising effect of the proposed IWTDC method, we compare it with methods such as traditional cross-correlation, adaptive filtering correlation, and wavelet threshold correlation. Simulation results indicate that compared to other methods, SNR can be improved by up to 5 dB using the IWTDC method, leading to superior signal correlation and enhanced detection performance for the related peaks. Furthermore, experimental data collected during the study were consistent with the simulation results, confirming the performance of the IWTDC method. Thus, our proposed method can overcome the limitations of using traditional threshold functions through adaptive threshold selection, preserve signal details, and significantly improve the denoising performance.

In the enhanced Loran (eLoran) system, the separation of skywave and groundwave is a crucial step to ensure the accuracy of signal processing, especially when facing challenges such as strong skywave interference and low signal-to-noise ratio (SNR). This paper proposes an upgraded algorithm that introduces the phase dimension based on traditional sky-wave separation technology, enhancing the comprehensiveness and applicability of the algorithm. Firstly, the algorithm utilizes an improved window function and spectral subtraction technique to estimate the characteristic parameters of the signal, and achieves the identification of skywave and groundwave through large number theory. Secondly, this paper proposes an adaptive second-order grid search matching algorithm that combines three dimensions: time delay difference, amplitude ratio, and phase difference, to accurately estimate the parameters of skywave and groundwave, effectively reconstruct and remove the skywave signal. This method not only improves the computational efficiency, but also enhances the comprehensive capture ability of the algorithm for signal characteristics by introducing phase information. Simulation results show that the algorithm can accurately identify and separate sky wave signals under strong sky wave interference. After introducing the phase dimension, the comprehensiveness of the algorithm is improved, and the accurate estimation of sky wave parameters is realized. This study provides a solid technical foundation for the stable realization of cycle identification and system functions in complex environments by improving the signal processing ability of eLoran system in harsh environments, and opens up a new technical path to improve the positioning accuracy and reliability of the system.

The time difference of arrival (TDOA) estimation plays a crucial role in emitter localization and time synchronization applications. When time among multiple sensors is synchronized, the TDOAs between the sensors and the emitter can be measured to achieve hyperbolic positioning of the emitter. Conversely, if the positions of both the sensors and the emitter are known, TDOAs can be utilized to synchronize the clocks across the sensors. Given that compressed sensing (CS) can reduce both the sampling rate and data volume, thereby enhancing the efficiency of TDOA estimation, there has been growing interest among researchers in exploring TDOA estimation within the CS framework. In scenarios such as passive positioning, the signals received by sensors are often non-cooperative, and the underlying signal system is unknown, making it difficult to obtain a sparse representation of the signal. This paper introduces an incomplete reconstruction-based TDOA estimation method along with an improved variant. By selecting a partial Fourier transform matrix as the measurement matrix and a Fourier transform matrix as the projection matrix, the orthogonal matching pursuit (OMP) algorithm is employed to reconstruct the compressed measurement data. Through subsequent processing steps, such as conjugate mirroring, TDOA estimation between two signals can be performed. Although the reconstructed signal may substantially differ from the original, the accuracy of TDOA estimation remains reliable. Simulation results demonstrate that when the signal-to-noise ratio (SNR) of the received signal is at least 0 dB and the compressed sampling length exceeds one-tenth of the original signal length, the TDOA estimation error of the proposed method is nearly identical to that of the cross-correlation method.

Optical clocks have been applied to the generation of time scales since they provide superb uncertainty and instability in recent years. This paper presents the simulations about the impact of the optical clock’s operational strategies on the performance of the generated time scale through two distinct steering algorithms. By post-processing the measured frequency difference between the 87Sr optical lattice clock and the hydrogen maser at the National Time Service Center, we realized an “optically steered” time scale TS(Sr), and the variation of the time difference TT(BIPM22)-TS(Sr) is 0.1 ns during the modified Julian date 59794–59819.

We illustrate the principle of Digital satellite TV differential timing (DSTVDT) and propose an optimal weighting method that reduces the timing error introduced by satellite ephemeris error. A mathematical formula for the timing error introduced by satellite ephemeris error is derived and analyzed. On the basis of the derived formula, the proposed optimal weighting method based on multi-base stations is presented. The results of data simulation and experiments show that when the proposed method is applied, for a satellite ephemeris error of 10km, the ephemeris-introduced timing error is less than 10ns, which is important for improving accuracy and stability of the timing system.