Precise frame synchronizing method in hydroacoustic communication

Abstract

The present invention relates to a method of the accurate frame synchronization for water sound communication mainly comprising the following steps: 1) digital processing of the received signals, respectively using the copy of Su (t) and Sd (t) to make a relevant processing of the copy of the received signal R (t) and respectively calculating the absolute values of the relevant functions |Cu (t)| and |Cd (t)|; 2) comparing |Cu (t)| & |Cd (t)| with one set threshold; if the result is smaller than the threshold, it will return to step 1) and make a relevant processing; if |Cu (t)| and |Cd (t)| surpasses the threshold, the result is regarded as the arrival of the synchronous pulse and then the calculation can turn to step 3; 3) calculating Tu and Td corresponding to the biggest value of |Cu (t)| and |Cd (t)| and also calculating the interval delta of the two relevant peak positions and then calculating relative Doppler beta; 4) calculating the central point of the two relevant peak positions and take it as the starting point of the time for the synchronous signals. The advantages of the invention are as follows: providing the accurate estimation values of the Doppler and the arrived time, which are very important to the water sound communications under certain conditions and can enhance the communication results. In addition, the invention can greatly reduce the volume of calculation for deciphering.

Description

technical field [0001] The invention relates to the field of underwater acoustic communication, and mainly relates to a precise frame synchronization method in underwater acoustic communication. Background technique [0002] Underwater acoustic communication refers to the related technology of acoustic communication in seawater medium. Compared with radio communication and wired communication, underwater acoustic communication is a more complex communication method, and its complexity is mainly reflected in the time of communication signals. Dimension broadening and frequency dimension divergence. The factors that cause the signal to broaden in the time dimension include multipath propagation effects, the influence of ocean currents, and the propagation of energy on the seabed, etc. The factors that cause the signal to diverge in the frequency dimension include relative motion between transceiver platforms, ocean currents (such as tides, internal wav...

AI Technical Summary

Problems solved by technology

[0003] There are three main methods of frame synchronization in the past: one method is to use a linear frequency modulation pulse signal (abbreviated as LFM signal) or a pseudo-random sequence signal (such as m sequence) as the frame header, and to process the LFM signal or m sequence in the receiving process. The signal is processed by pulse compression, so that the arrival time of the pulse can be extracted, such as figure 1 As shown, this method is simple and effective, but it cannot estimate the relative Doppler value, and it is only suitable for low Doppler occasions, such as when a fixed platform based on the seabed transmits underwater measurement data to moored buoys on the water surface, because the platform If the relative motion rate between them is very small, you can use this frame header and frame synchronization method

[0004] The second method is to transmit an LFM signal first, and then transmit a single-frequency pulse signal (abbreviated as CW pulse). In the receiving process, the pulse arrival time can be extracted by performing pulse compression processing on the LFM signal. For the CW pulse Spectrum analysis can measure the Doppler frequency deviation value, such as figure 2 As shown, the quasi-synchronous estimation of pulse arrival time and Doppler frequency offset is realized in this way. This method is also relatively simple in implementation, but to achieve higher spectral resolution, it is necessary to use a longer pulse width CW Pulse, which actually takes up the communication time and reduces the communication rate

This method has better performance, but there are difficulties in implementation. The main reason is that it is necessary to save a complete subframe signal before estimating the Doppler frequency offset value, which takes up a lot of computer memory, especially This problem is more prominent when the subframe is longer

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