{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T16:53:42Z","timestamp":1774630422218,"version":"3.50.1"},"reference-count":21,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2020,1,29]],"date-time":"2020-01-29T00:00:00Z","timestamp":1580256000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The carrier-to-noise ratio (C\/N0) is an important indicator of the signal quality of global navigation satellite system receivers. In a vector receiver, estimating C\/N0 using a signal amplitude Kalman filter is a typical method. However, the classical Kalman filter (CKF) has a significant estimation delay if the signal power levels change suddenly. In a weak signal environment, it is difficult to estimate the measurement noise for CKF correctly. This article proposes the use of the adaptive strong tracking Kalman filter (ASTKF) to estimate C\/N0. The estimator was evaluated via simulation experiments and a static field test. The results demonstrate that the ASTKF C\/N0 estimator can track abrupt variations in C\/N0 and the method can estimate the weak signal C\/N0 correctly. When C\/N0 jumps, the ASTKF estimation method shows a significant advantage over the adaptive Kalman filter (AKF) method in terms of the time delay. Compared with the popular C\/N0 algorithms, the narrow-to-wideband power ratio (NWPR) method, and the variance summing method (VSM), the ASTKF C\/N0 estimator can adopt a shorter averaging time, which reduces the hysteresis of the estimation results.<\/jats:p>","DOI":"10.3390\/s20030739","type":"journal-article","created":{"date-parts":[[2020,1,29]],"date-time":"2020-01-29T10:51:07Z","timestamp":1580295067000},"page":"739","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["C\/N0 Estimator Based on the Adaptive Strong Tracking Kalman Filter for GNSS Vector Receivers"],"prefix":"10.3390","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5484-0484","authenticated-orcid":false,"given":"Shiming","family":"Liu","sequence":"first","affiliation":[{"name":"School of Automation, Northwestern Polytechnical University, Xi\u2019an 710072, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sihai","family":"Li","sequence":"additional","affiliation":[{"name":"School of Automation, Northwestern Polytechnical University, Xi\u2019an 710072, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiangtao","family":"Zheng","sequence":"additional","affiliation":[{"name":"School of Automation, Northwestern Polytechnical University, Xi\u2019an 710072, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6895-7923","authenticated-orcid":false,"given":"Qiangwen","family":"Fu","sequence":"additional","affiliation":[{"name":"School of Automation, Northwestern Polytechnical University, Xi\u2019an 710072, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yanhua","family":"Yuan","sequence":"additional","affiliation":[{"name":"Beijing Institute of Control and Electronic Technology, Beijing 100032, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,1,29]]},"reference":[{"key":"ref_1","first-page":"16","article-title":"What are vector tracking loops, and what are their benefits and drawbacks?","volume":"4","author":"Lashley","year":"2009","journal-title":"Inside GNSS"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"122","DOI":"10.1007\/s10291-018-0786-y","article-title":"C\/N0 estimators for high-sensitivity snapshot GNSS receivers","volume":"22","year":"2018","journal-title":"GPS Solut."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1002\/navi.221","article-title":"Environmental context detection for adaptive navigation using GNSS measurements from a smartphone","volume":"65","author":"Gao","year":"2018","journal-title":"Navig. 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