Noise interference and multipath effects in complex marine environments seriously constrain the performance of hydroacoustic positioning systems. Traditional millisecond-level signal application and processing methods are widely used in existing research; however, it is difficult to meet the requirements of centimeter-level positioning accuracy in marine engineering. To address this problem, this study proposes a hydroacoustic positioning method based on a short baseline system for the cooperative reception of multi-channel signals. The method adopts ultra-short pulse signals with microsecond pulse width, and significantly improves the system signal-to-noise ratio and anti-interference capability through multi-channel signal alignment and coherent superposition techniques; meanwhile, a joint energy gradient-phase detection algorithm is designed, which solves the instability problem of the traditional cross-correlation algorithm in the detection of ultra-short pulse signals through the identification of signal stability intervals and accurate phase estimation. Simulation verification shows that the 8-hydrophone × 4-channel configuration can achieve 36.06% signal-to-noise gain under harsh environmental conditions (−10 dB), and the performance of the joint energy gradient-phase detection algorithm is improved by about 19.1% compared with the traditional method in an integrated manner. Marine tests further validate the engineering practicability of the method, with an average SNR gain of 2.27 dB achieved for multi-channel signal reception, and the TDOA estimation stability of the new algorithm is up to 32.0% higher than that of the conventional method, which highlights the significant advantages of the proposed method in complex marine environments. The results show that the proposed method can effectively mitigate the noise interference and multipath effects in complex marine environments, significantly improve the accuracy and stability of hydroacoustic positioning, and provide reliable technical support for centimeter-level accuracy applications in marine engineering.

Detecting ionospheric anomalies constitutes a key research focus in the field of early seismic warnings and responses. This study investigates pre- and post-seismic ionospheric anomalies in relation to strong earthquakes, utilizing Global Ionospheric Map (GIM) data and applying three detection methods: the interquartile range (IQR), first-order and second-order numerical difference (FSND), and butterworth bandpass filter (BBF). The study focuses on two cases of strong earthquakes (inland and offshore earthquakes): the Mw 7.1 earthquake in Aksu, Xinjiang, China (January 23, 2024), and the Mw 7.4 earthquake off the west coast of Honshu, Japan (January 1, 2024). The ionospheric total electron content (TEC) disturbances in these events were detected and analyzed, and the detection performances of the three methods were compared. The results show that all three methods effectively capture ionospheric TEC disturbances and provide valuable insights into earthquake precursors and epicentral anomalies. The IQR method detected pre-seismic disturbances for both inland and offshore earthquakes. The FSND method consistently identifies “N”-type disturbances in the Differential TEC (DTEC) for both events. The FSDN method can process long-term TEC time series, whereas the BBF method is restricted to smaller datasets. In practice, the BBF experiment examined TEC data on a daily basis to identify ionospheric dis-turbances.The BBF method also highlights “N”-type disturbances by employing 30-minute TEC data, unlike the other two methods that used 1-hour sampled data. These findings offer theoretical insights into ionospheric responses to earthquakes and have practical implications for earthquake prediction.