Index Ambiguity Elimination of Overlapped Signals in Multisource Localization

Abstract

Multisource localization (MSL) for overlapped signals has attracted much attention, and the existing methods rely on the combination of multitype measurements, which puts higher requirements on the receiver. Besides, these methods can not avoid the problem of measurement-source association. In view of this, on the basis of broadband signal time-frequency spectrogram detection (TFSD), we propose an MSL scheme for overlapped signals based on index ambiguity elimination, which can avoid the above-mentioned measurement-source association problem by extracting the pure part of each signal component. Specifically, we first conduct the time-frequency transformation of the received signal, and analyze the overlapping types of the time-frequency blocks (TFBs) in two aspects: 1) inter-TFB, i.e., the overlapping types between the TFBs and 2) intra-TFB, i.e., the overlapping types between signal components contained in the TFB. On this basis, the TFB nonoverlapping part extraction algorithm is designed to eliminate the overlap between TFBs. Afterward, the signal segmentation algorithm based on the signal characteristic change mechanism is designed to obtain the pure part of each signal component, that is, eliminating the index ambiguity of each signal component contained in the extracted nonoverlapping TFB. Finally, the angle-of-arrival (AOA) information of multiple receivers for a certain signal can be obtained through the AOA estimation method, as well as the location of source device corresponding to the signal can be estimated by the triangulation method. Simulation and experiment results verify the effectiveness of the designed scheme.