| dc.description.abstract | Direction of Arrival (DOA) estimation is crucial in applications such as wireless communications, radar monitoring, and acoustic localization. However, traditional methods (e.g., MUSIC and ESPRIT) suffer significant performance degradation in the presence of array imperfections, such as gain/phase errors, mutual coupling, and sensor position deviations, as well as in low signal-to-noise ratio (SNR) environments. This paper proposes a DOA estimation framework based on the Inception Encoder (IE), further optimized as IE+, which integrates multi-scale feature extraction and attention mechanisms to achieve superior performance under noisy and imperfect array conditions. The IE architecture leverages multi-scale analysis to extract both local and global features, effectively capturing the spatial and temporal correlations within signals while filtering out noise. Compared to conventional convolutional encoders (CE), IE demonstrates higher accuracy and robustness against complex distortions, while its modular design and depthwise separable convolutions significantly reduce computational demands. IE+ further enhances model adaptability by incorporating attention mechanisms, dynamically focusing on key features to mitigate the impact of array imperfections. Experimental results show that both IE and IE+ outperform CE and traditional methods across various scenarios. Under imperfect conditions, IE+ exhibits significantly lower estimation bias than other approaches, and even in extreme cases where SNR drops to-15 dB, it maintains stable accuracy. Furthermore, IE+ demonstrates excellent scalability in large-scale MIMO systems, with an optimized design that supports low-latency inference, making it suitable for real-time applications. In summary, the Inception-based encoder provides an efficient, robust, and scalable solution for DOA estimation in the presence of array imperfections. This approach establishes a new benchmark for handling real-world distortions and noisy environments, offering reliable technological support for modern communication and sensing systems. | en_US |