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Since coherent signals scale as the square of the coherence volume, THG signals are expected to be significantly smaller than FWM signals for comparable pulse energy and duration.
Bicoherence analysis is able to detect coherent signals in extremely noisy data, provided that the coherency remains constant for sufficiently long times, since the noise contribution falls off rapidly with increasing N. The auto- and cross-bispectrum of a nonlinear system is presented by Pezeshki [62, 63].
Here, these two sources can be seen the coherent signals.
In this paper, a novel FOC-ITMR method for coherent signals estimation is proposed.
The method not only is suitable for non-coherent signals but also can process coherent signals directly without any decoherent operations; in addition, the number of signals is not necessarily known a priori.
Notice that if the narrowband far-field signals are the coexistence of the uncorrelated and coherent signals, which means there are K coherent signals, the remaining are M − K statistically independent signals.
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To extract each coherent signal, a cross spectral matrix is decomposed into eigenmodes.
These filters adjust the phases of the microphone signals to guarantee coherent signal combining.
The estimated total received power PS (coherent signal power) can be derived from Equation 3.
To overcome this drawback, Wang and Kaveh [8] proposed a coherent signal-subspace method.
The proposed focusing scheme can perform coherent signal subspace transformation in the beamspace domain without preliminary DOA estimation or iteration.
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