基于GPU的DSSS水声通信多普勒快速估计方法

doi:10.12305/j.issn.1001-506X.2026.06.31

Abstract

Abstract:

The Doppler estimation method based on cross ambiguity function （CAF） in direct sequence spread spectrum （DSSS） underwater acoustic communication has the disadvantages of being computationally intensive and time-consuming to solve. In order to improve the efficiency of Doppler estimation, a fast Doppler estimation method based on graphics processing unit （GPU） is proposed. Firstly, in order to reduce the computational complexity of the CAF Doppler estimation method, an improved two-step Doppler estimation algorithm is proposed. Secondly, the algorithm is realized from three aspects: device memory preloading, parallelization of operation units, and deployment on the GPU platform. Finally, the method is tested using actual sea trial data and compared with the CPU estimation method. The test results show that the GPU fast Doppler estimation method proposed in this paper can achieve accurate estimation of the Doppler factor of DSSS underwater acoustic communication signals. Compared with the CPU estimation method, the maximum speedup ratio is 263.65, which greatly improves the execution efficiency of the Doppler estimation algorithm.

Key words: direct sequence spread spectrum （DSSS）, underwater acoustic communication, graphic processing unit （GPU）, Doppler estimation

CLC Number:

TN 929.3

Haiyuan PENG, Yu LI, Yu’nan ZHU, Zhanqing PU, Wei WANG. GPU-based fast Doppler estimation method for DSSS underwater acoustic communication[J]. Systems Engineering and Electronics, 2026, 48(6): 2105-2112.

Figures/Tables 16

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References 21

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参数	CPU	GPU
型号	12th Gen Intel（R） Core（TM） i9-12900K	NVIDIA GeForce RTX 3060 Ti
时钟频率	3.20 GHz	1410 MHz
CUDA版本	CUDAv11.6

参数	符号	仿真取值
带宽	$B$	—
Q路PN码长	${L_Q}$	4158
单帧信号长度/s	$T$	4.158
采样率/kHz	${f_s}$	48
通信速率/bps	$r$	30.303
粗估计多普勒精度/Hz	$\Delta {\alpha _1}$	1×10⁻⁴
细估计多普勒精度/Hz	$\Delta {\alpha _2}$	3.33×10⁻⁵
基带调制方式	BPSK

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GPU-based fast Doppler estimation method for DSSS underwater acoustic communication

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