Instantaneous Hybrid Signal Separation Based on CANDECOMP/PARAFAC Decomposition with Accelerated Proximal Gradient Method

In this paper, to solve the anti-interference problem of UAVs in bland source decomposition, a new signal separation method of instantaneous hybrid model based on the classic method named CANDECOMP/PARAFAC Decomposition (CPD) is studied. Firstly, the instantaneous hybrid signal decomposition is analyzed with an instantaneous hybrid model and a regular parallel decomposition method. Secondly, the signal separation problem applied in the instantaneous hybrid model is solved by using a regular parallel decomposition method from tensor decomposition theory. Finally, motivated by the idea of algorithm optimization by adding an operator, a new CPD method with proximal gradient constraint based on the classical CPD separation algorithms is proposed, which can be called as CPD-APG. Compared with the conventional JADE separation method and FastICA separation method, the separation error of the proposed algorithm is generally reduced by about 50% under the SNR range of −20dB~0dB. When the SNR is above 0dB, the separation error of the proposed algorithm is nearly close to zero.