{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T03:11:38Z","timestamp":1760238698044,"version":"build-2065373602"},"reference-count":29,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2020,8,21]],"date-time":"2020-08-21T00:00:00Z","timestamp":1597968000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Radar scientists typically define the radar beamwidth as a half-power beamwidth (HPBW) in the main lobe of the antenna pattern. However, the microwave radiations outside radar HPBW might also backscatter into the radar receiver and change the distribution of the received signal. To determine an actual and effective beamwidth illuminated on the measured targets, we first generate the simulated-waveforms derived from coincident lidar points and radar equation and then develop a waveform matching method to seek out an optimal beamwidth based on the 95% threshold of correlation coefficients between radar waveforms and the simulated-waveforms. The 8565 measurements of a Ku-band profiling radar named Tomoradar and coincident lidar data in a widespread heterogeneous forest area of southern Finland are employed for resolving the effective beamwidth. The results reveal that about 97% of the effective beamwidth are larger than Tomoradar HPBW, but the effective beamwidth could be changeable for each measurement due to variations in the scattering properties of vegetation. Thus, a fixed average effective beamwidth (AEBW) with 0.1-degree resolution is introduced to determine Tomoradar cone according to the effective beamwidth and corresponding proportions. We discover that Tomoradar AEBW is approximately approaching to 8\u00b0, which is larger than Tomoradar HPBW of 6\u00b0. If we regard AEBW as the actual Tomoradar beamwidth rather than HPBW, the simulated-waveforms have substantially stronger correlation strength with Tomoradar waveforms, and canopy tops derived from lidar data within Tomoradar AEBW are much closer to those extracted from Tomoradar waveforms. The results demonstrate that radar AEBW is a more appropriate reference for designing radar antenna and selecting the region size of validation data such as lidar points or the ground truth. However, considering that radar AEBW is variable for different radar antenna pattern, we suggest that actual radar beamwidth should be defined with a fraction of total radiation energy within radar AEBW, just like the definition of laser divergence of lidar based on the percentage of transmitted laser energy. In this paper, for a forest inventory research case, the fraction of total radiation energy within the AEBW for radar system is supposed to be 91%.<\/jats:p>","DOI":"10.3390\/rs12172710","type":"journal-article","created":{"date-parts":[[2020,8,21]],"date-time":"2020-08-21T09:21:51Z","timestamp":1598001711000},"page":"2710","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["The Determination of Effective Beamwidth of Ku Band Profiling Radar Based on Waveform Matching Method in the Boreal Forest of Finland"],"prefix":"10.3390","volume":"12","author":[{"given":"Hui","family":"Zhou","sequence":"first","affiliation":[{"name":"Electronic Information School, Wuhan University, Wuhan 430079, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0148-3609","authenticated-orcid":false,"given":"Yuwei","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute, FI-02431 Kirkkonummi, Finland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nan","family":"Hu","sequence":"additional","affiliation":[{"name":"A-INFO Inc., Beijing 100084, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuandan","family":"Dong","sequence":"additional","affiliation":[{"name":"University of Electronic Science and Technology of China, Chengdu 610041, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xinmin","family":"Xu","sequence":"additional","affiliation":[{"name":"College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou 310027, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ziyi","family":"Feng","sequence":"additional","affiliation":[{"name":"Department of Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute, FI-02431 Kirkkonummi, Finland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Teemu","family":"Hakala","sequence":"additional","affiliation":[{"name":"Department of Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute, FI-02431 Kirkkonummi, Finland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Juha","family":"Hyypp\u00e4","sequence":"additional","affiliation":[{"name":"Department of Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute, FI-02431 Kirkkonummi, Finland"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,8,21]]},"reference":[{"key":"ref_1","first-page":"919","article-title":"Improvement of an oak canopy model extracted from digital photogrammetry","volume":"68","author":"Gong","year":"2002","journal-title":"Photogramm. 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