Abstract
Automotive spinning FMCW radar provides dense, $360^\circ$ sensing and remains reliable under poor illumination and adverse weather, making it well-suited to autonomous navigation. Place recognition uses these observations to identify previously visited locations for re-localization and long-term navigation. However, heading changes appear as circular shifts in the polar radar representation, and conventional global aggregation can lose relationships among radar responses that are important for distinguishing similar places. We propose SGCA-Net, a spinning radar place recognition framework that combines rotation-robust feature extraction with Spatially Gated Correlation Aggregation (SGCA). SGCA learns spatial weights to reduce the influence of unstable and ambiguous radar regions, while aggregating pairwise correlations among local responses to preserve informative feature relationships. Experiments on the MulRan dataset show that SGCA-Net consistently outperforms SOTA methods across urban, campus, and open-road environments, while remaining robust to substantial heading variation. Evaluation on the HeRCULES dataset further demonstrates that SGCA-Net generalizes to unseen environments and radar sensors without fine-tuning.
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Publication details
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- Open access
- Green open access
Cite this article
APA 7
Rahman, S., Shrestha, S. S., Khamis, A., & Moghadam, P. (2026). Automotive mmWave Spinning Radar Place Recognition with Spatially Gated Feature-Correlation Representation. https://omanscience.com/en/articles/automotive-mmwave-spinning-radar-place-recognition-with-spatially-gated-feature-correlation-representation
MLA 9
Rahman, Saimunur, et al. "Automotive mmWave Spinning Radar Place Recognition with Spatially Gated Feature-Correlation Representation." https://omanscience.com/en/articles/automotive-mmwave-spinning-radar-place-recognition-with-spatially-gated-feature-correlation-representation.
Chicago (author–date)
Rahman, Saimunur, Sagun Singh Shrestha, Abdelwahed Khamis, and Peyman Moghadam. 2026. "Automotive mmWave Spinning Radar Place Recognition with Spatially Gated Feature-Correlation Representation." https://omanscience.com/en/articles/automotive-mmwave-spinning-radar-place-recognition-with-spatially-gated-feature-correlation-representation.
Harvard
Rahman, S., Shrestha, S. S., Khamis, A. and Moghadam, P. (2026) 'Automotive mmWave Spinning Radar Place Recognition with Spatially Gated Feature-Correlation Representation', Available at: https://omanscience.com/en/articles/automotive-mmwave-spinning-radar-place-recognition-with-spatially-gated-feature-correlation-representation.
Vancouver
Rahman S, Shrestha SS, Khamis A, Moghadam P. Automotive mmWave Spinning Radar Place Recognition with Spatially Gated Feature-Correlation Representation. https://omanscience.com/en/articles/automotive-mmwave-spinning-radar-place-recognition-with-spatially-gated-feature-correlation-representation
IEEE
S. Rahman, S. S. Shrestha, A. Khamis, and P. Moghadam, "Automotive mmWave Spinning Radar Place Recognition with Spatially Gated Feature-Correlation Representation," https://omanscience.com/en/articles/automotive-mmwave-spinning-radar-place-recognition-with-spatially-gated-feature-correlation-representation.