1 Ocak 2021 Dergi makalesi Açık Erişim

Bahadur, Berkay; Nohutcu, Metin

Citation Style Language JSON

{
  "DOI": "10.1016/j.measurement.2020.108596", 
  "abstract": "Although the emergence of new satellite systems offers considerable opportunities, the integration of Global Navigation Satellite System (GNSS) multi-constellation entails more complicated approaches, especially for stochastic modeling. This study proposes a filtering approach that combines robust Kalman filtering and variance component estimation to specify the weights of multi-GNSS observations in single-frequency positioning. In this approach, robust Kalman filter resists the impact of unexpected outliers by introducing the equivalent covariance matrix, while multi-GNSS observation variances are determined adaptively in each epoch by using variance component estimation. The study demonstrated that the proposed filtering approach determines the variances of multi-GNSS observations more rigorously as a result of the assessment of the observation residuals. The results also showed that the positioning accuracy of single-frequency multi-GNSS positioning that depends on the conventional weighting approaches is improved by 18.5% on average with the employment of the proposed filtering approach and its improvement ratio can exceed 30% in some stations.", 
  "author": [
    {
      "family": "Bahadur", 
      "given": " Berkay"
    }, 
    {
      "family": "Nohutcu", 
      "given": " Metin"
    }
  ], 
  "container_title": "MEASUREMENT", 
  "id": "231342", 
  "issued": {
    "date-parts": [
      [
        2021, 
        1, 
        1
      ]
    ]
  }, 
  "title": "Integration of variance component estimation with robust Kalman filter for single-frequency multi-GNSS positioning", 
  "type": "article-journal", 
  "volume": "173"
}