JOURNAL ARTICLE

C/N0 Estimator Based on the Adaptive Strong Tracking Kalman Filter for GNSS Vector Receivers

Shiming LiuSihai LiJiangtao ZhengQiangwen FuYanhua Yuan

Year: 2020 Journal:   Sensors Vol: 20 (3)Pages: 739-739   Publisher: Multidisciplinary Digital Publishing Institute

Abstract

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.

Keywords:
Kalman filter GNSS applications Estimator Control theory (sociology) Extended Kalman filter SIGNAL (programming language) Wideband Computer science Mathematics Engineering Electronic engineering Statistics Global Positioning System Telecommunications Artificial intelligence

Metrics

9
Cited By
1.03
FWCI (Field Weighted Citation Impact)
14
Refs
0.80
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Target Tracking and Data Fusion in Sensor Networks
Physical Sciences →  Computer Science →  Artificial Intelligence
GNSS positioning and interference
Physical Sciences →  Engineering →  Aerospace Engineering
Inertial Sensor and Navigation
Physical Sciences →  Engineering →  Aerospace Engineering

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