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The estimated delays suffer from poor time resolution at low sampling frequencies (large sampling period) [5].
However, this approach has ghosting artifacts at low sampling rates.
In this case, accurate TDE requires high time resolution (low sampling time).
So an ideal fusion results can be obtained under a low sampling rate.
To work at extremely low sampling rates to relax the computational and hardware complexity.
In addition, these TDE techniques suffer from a time resolution problem at low sampling frequencies.
Too low sampling rate will, however, make the signal distorted according the Shannon Sampling Theorem.
Nevertheless, the low sampling rate avoids this channel estimation model to properly characterize close-in multipath.
Our approach yields high accuracy despite the low sampling interval and does not require GPS data.
There were also false positives (i.e., wrong "estimated" hotspots), particularly at low sampling frequencies.
In addition, the proposed method works at extremely low sampling rates and hence decreases the computation time and hardware complexity.
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