基于生成模型的三维波束形成图像压缩方法

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关键词：波束形成;数据压缩；深度学习;改进向量量化变分自编码器；三维空间 中图分类号：TP391；TN912 DOI：10.3969/j.issn.1004-132X.2025.07.015 开放科学（资源服务）标识码（OSID）：

3D Beamforming Map Compression Method Based on Generative Model

ZHAO Yunjie HE Yansong*ZHANG Zhifei XU Zhongming College of Mechanical and Vehicle Engineering，Chongqing University，Chongqing，400044

Abstract： To address the significant degradation in localization performance of DenseNet model under high compression ratios caused by channel compression method，a 3D beamforming map compression（3D-BFMC） method was proposed based on VQ-VAE-2 model. The hierarchical encoder of the VQ-VAE-2 model was used to compress 3D beamforming maps into vectorized local feature matrices，and then the matrices were input into the DenseNet model to perform 3D localization. Simulation results show that DenseNet models trained on compressed data by the 3D-BFMC method have better localization accuracy，frequency generalization and noise robustness than those of outperform channel compression approaches.A single-source experiment confirms the effectiveness and feasibility of 3DBFMC in real-world environments.

Key words： beamforming； data compression； deep learning;vector quantized-variational autoencoder-2（VQ-VAE-2）；three-dimensional space

0 引言

波束形成作为一种基于传感器阵列的信号处理技术，被广泛用于无线电波[]、地震波[2]、声波[]领域。（剩余17685字）