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Through empirical studies, we find that the spatial-based CFAR widely used in existing works suffers from a severe energy masking issue. This is because these algorithms work well when the target is far away enough to be approximated as a point. In short-range indoor sensing, the human body can not be considered as a point but an extended target, causing the spatial-based CFAR to calculate the noise power wrongly and accordingly a miss-generation of the point cloud. To fundamentally solve the problem, this paper proposes a temporal-based CFAR named ETCM-CFAR. We address multiple issues such as lacking initial noise power and the absence of a closed-form threshold solution to make the proposed algorithm work. Based on ETCM-CFAR, this paper proposes a point cloud generation system named mmPC. mmPC is implemented on three different types of commercial-off-the-shelf mmWave radars and extensive experiments demonstrate that mmPC significantly improves point cloud quality, increasing the number of cloud points by 148.6% compared to the state-of-the-art systems. Two representative sensing applications, i.e., fitness activity recognition and human-pet classification are further employed to demonstrate the effectiveness of mmPC on sensing.<\/jats:p>","DOI":"10.1145\/3729465","type":"journal-article","created":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T21:21:56Z","timestamp":1750281716000},"page":"1-29","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["From Spatial Domain to Temporal Domain: Unleashing the Capability of CFAR for mmWave Point Cloud Generation"],"prefix":"10.1145","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-1589-6567","authenticated-orcid":false,"given":"Hongliu","family":"Yang","sequence":"first","affiliation":[{"name":"Key Laboratory of High Confidence Software Technologies (Ministry of Education), School of Computer Science, Peking University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9977-7244","authenticated-orcid":false,"given":"Duo","family":"Zhang","sequence":"additional","affiliation":[{"name":"Key Laboratory of High Confidence Software Technologies (Ministry of Education), School of Computer Science, Peking University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5786-3331","authenticated-orcid":false,"given":"Xusheng","family":"Zhang","sequence":"additional","affiliation":[{"name":"Key Laboratory of High Confidence Software Technologies (Ministry of Education), School of Computer Science, Peking University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5396-4554","authenticated-orcid":false,"given":"Jie","family":"Xiong","sequence":"additional","affiliation":[{"name":"Nanyang Technological University, Singapore"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-0281-8132","authenticated-orcid":false,"given":"Zizhou","family":"Fan","sequence":"additional","affiliation":[{"name":"Key Laboratory of High Confidence Software Technologies (Ministry of Education), School of Computer Science, Peking University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-4214-630X","authenticated-orcid":false,"given":"Wanru","family":"Ning","sequence":"additional","affiliation":[{"name":"Key Laboratory of High Confidence Software Technologies (Ministry of Education), School of Computer Science, Peking University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2004-1136","authenticated-orcid":false,"given":"Weiyan","family":"Chen","sequence":"additional","affiliation":[{"name":"China Mobile Research Institute, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2529-8021","authenticated-orcid":false,"given":"Fusang","family":"Zhang","sequence":"additional","affiliation":[{"name":"Institute of Software, Chinese Academy of Sciences; University of Chinese Academy of Sciences; Inspur Computing Technology Pty Ltd., Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5626-1654","authenticated-orcid":false,"given":"Zijun","family":"Han","sequence":"additional","affiliation":[{"name":"Key Laboratory of High Confidence Software Technologies (Ministry of Education), School of Computer Science, Peking University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6608-1267","authenticated-orcid":false,"given":"Daqing","family":"Zhang","sequence":"additional","affiliation":[{"name":"Key Laboratory of High Confidence Software Technologies (Ministry of Education), School of Computer Science, Peking University, Beijing, China, Telecom SudParis and Institut Polytechnique de Paris, Evry, France"}]}],"member":"320","published-online":{"date-parts":[[2025,6,18]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/3495243.3560518"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM41043.2020.9155293"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/3349624.3356768"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/2971648.2971665"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/WoWMoM.2016.7523524"},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/2971648.2971744"},{"issue":"2","key":"e_1_2_1_7_1","first-page":"1","article-title":"Exploring lora for long-range through-wall sensing. 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