PHS:基于双曲线频率调制的脉冲序列速度测量法

IF 1.9 4区 计算机科学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS International Journal of Distributed Sensor Networks Pub Date : 2024-01-12 DOI:10.1155/2024/6670576
Tao Ping, Caixia Song, Zhiguo Qi, Pengmin Xu
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引用次数: 0

摘要

海洋环境中的信道是一个时变和空间变化的信道。声纳中经常使用脉冲截断连续波(PCW)测速,但 PCW 信号在信道中的不稳定效应限制了测速的有效性。双曲频率调制(HFM)信号对多普勒不敏感,因此被广泛用于声纳和雷达的测距和测速。然而,由于海洋环境的滤波效应,单一频段的高频调制信号可能会导致传输损耗过大,回波能量过弱而无法探测到目标。在分析速度对高频调频信号测距影响的基础上,提出了一种基于高频调频的脉冲序列测速方法(PHS),在脉冲序列中使用不同频段和脉宽的高频调频信号进行测速。大量仿真结果表明,PHS 方法不仅能保证速度测量,还能充分利用高频序列的能量,提高距离测量的精度。PHS 方法在实际工程应用中具有重要价值。
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PHS: A Pulse Sequence Method Based on Hyperbolic Frequency Modulation for Speed Measurement
The channel in the marine environment is a time-varying and space-varying channel. Pulse-truncated continuous wave (PCW) speed measurement is often used in sonar, but the instability effect of PCW signal in the channel limits the effectiveness of speed measurement. Hyperbolic frequency modulation (HFM) signal is insensitive to Doppler; therefore, HFM signals are widely used in ranging and velocity measurement of sonar and radar. However, due to the filtering effect of the marine environment, the HFM signal of a single frequency band may cause excessive transmission loss, and the echo energy may be too weak to detect the target. Based on the analysis of the influence of speed on the distance measurement of HFM signal, a pulse sequence method based on HFM for speed measurement (PHS) is proposed, which uses HFM signals of different frequency bands and pulse widths in the pulse sequence to perform speed measurement. Extensive simulation results show that PHS method not only guarantees the speed measurement but also makes full use of the energy of the HFM sequence to improve the accuracy of the distance measurement. And PHS method is valuable to the practical application of engineering.
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来源期刊
CiteScore
6.50
自引率
4.30%
发文量
94
审稿时长
3.6 months
期刊介绍: International Journal of Distributed Sensor Networks (IJDSN) is a JCR ranked, peer-reviewed, open access journal that focuses on applied research and applications of sensor networks. The goal of this journal is to provide a forum for the publication of important research contributions in developing high performance computing solutions to problems arising from the complexities of these sensor network systems. Articles highlight advances in uses of sensor network systems for solving computational tasks in manufacturing, engineering and environmental systems.
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