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Figure 5 leads to the observation that act-detect has a better detection performance than the window-sliding methods on the fgnet data set.
The curves highlight that for small-medium SNR values, the KRAO-ASB yields better detection performance than that obtained by performing either the AMF or the KRAO operating alone.
Furthermore, results suggest that some shapes elicit better detection performance than others.
Moreover, it provides better detection performance than the unconstrained ML estimate, particularly, in the case of small sample support.
Experimental results show that the proposed method is effective, and for a given false alarm probability, the DTRN exhibits better detection performance than the single terahertz radar.
For α=1.5 and α=0.8, our proposed detector has a better detection performance than the FLOM detector under all levels of GSNR.
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These methods have better detection performances than the 2D methods (2D BF, 2D Capon and MUSICAL) and than D-BF.
A general conclusion is that D-MUSICAL and D-Capon have better detection performances than all of the existing 2D and 3D methods.
And both CG-PGLRT-NSCM and CG-PGLRT-AML detectors can produce better detection performance with dramatically less training than the GLRT-LQ with Rscm.
The experimental results using raw radar target data and simulated clutter data show that the new detector achieves better detection performance for range-spread maneuvering targets than the existing detectors.
Evaluation with real sEMG analysis also indicated better detection performance compared to existing methods.
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