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Therefore, to enhance the performance of this estimation, we propose to replace r Δ (n) in Equation 22 by an estimate (hat x(n)) of the transmitted signal x(n) that would be closer to c(n).
Especially large STOs degrade the performance of this estimation technique.
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The performance of this DOA estimation method is significantly improved due to the application of MSNWF for rejecting interference signals.
However, since Cho and Cho [3] evaluated the performance of this complexity estimation conducted through interpolation based on super low-resolution images (e.g., 240 × 128, 192 × 144, 192 × 112) with small differences in complexity between frames, its applicability to the current trend of using high-resolution images is uncertain.
The performance of the suboptimum power estimation is shown in Figure 19; this figure shows that the performance of the estimation becomes better as the number of received vectors increases.
The bootstrap resampling technique was also used to determine the performance of the estimation.
The results state the excellent performance of the estimation algorithm, even under real operation conditions.
Table 4 Performance of the estimation method: Computation time.
Table 3 Performance of the estimation method: Precision.
Therefore, the initial value would affect the performance of the estimation.
When it occurs, the performance of the estimation may significantly degrade.
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