According to the results, the location accuracy of the KF-based and FOSB-based tracking schemes is better than the non-tracking schemes.
As the sampling time set to 1 s, the results demonstrate that more than 9060percentcent of the non-tracking, KF-based tracking, and FOSB-based tracking schemes have error distances of less than 4.63 (2.87), 3.04 (1.90), and 3.03 (1.90) m, respectively.
For the third path, Figures 9 and 10 present the comparisons among the non-tracking, the KF-based tracking, and the FOSB-based tracking schemes.
Figure 9 Comparison of the non-tracking (observed), the KF-based tracking, and the FOSB-based tracking schemes in the third path.
Figure 5 Comparison of the non-tracking (observed), the KF-based tracking, and the FOSB-based tracking schemes for different sampling times in terms of the CDF of the error distances in the first path.
Therefore, compared to previous matrix-based subspace tracking schemes, the subspace estimation accuracy is improved.
Wang et al. [16] and Chen et al. [17] propose cluster-based tracking schemes.
All the tracking schemes mentioned above adopt the maximum-likelihood (ML) estimation (MLE) technique.
Consequently, the sampling time has a considerable effect on the performance of the tracking schemes.
TeTraKron allows to extend arbitrary existing matrix-based subspace tracking schemes to the tracking of the HOSVD-based subspace estimate.
