Underdetermined Blind Source Separation of Synchronous Orthogonal Frequency Hopping Signals Based on Single Source...

Area of Science:

• Signal Processing
• Array Signal Processing
• Communications Engineering

Background:

• Underdetermined blind source separation (UBSS) presents challenges in estimating signal parameters when the number of sensors is less than the number of sources.
• Synchronous orthogonal frequency hopping (FH) signals require robust methods for accurate parameter estimation due to their complex time-frequency characteristics.

Purpose of the Study:

• To develop a novel algorithm for complex-valued mixing matrix estimation of synchronous orthogonal FH signals in UBSS.
• To propose a method for direction-of-arrival (DOA) estimation and sorting of these signals under underdetermined conditions.
• To enhance the accuracy of mixing matrix estimation and enable signal sorting.

Main Methods:

• A new algorithm for detecting single source points (SSPs) by comparing normalized time-frequency (TF) point coefficients.
• Hierarchical clustering for estimating the mixing matrix of FH signals.
• A modified subspace projection method for obtaining DOAs of FH signals.

Main Results:

• The proposed SSP detection criteria significantly improve the estimation accuracy of the mixing matrix.
• The developed methods enable the sorting of synchronous orthogonal FH signals even in underdetermined conditions.
• Experimental results validate the efficiency of the proposed mixing matrix estimation and DOA algorithms.

Conclusions:

• The novel SSP detection and hierarchical clustering approach effectively estimates the mixing matrix for FH signals in UBSS.
• The modified subspace projection method successfully determines DOAs and sorts synchronous orthogonal FH signals.
• The presented algorithms offer significant improvements in accuracy and capability for complex signal processing tasks.