Interference Source Localization via Frequency Sub-band Segmentation
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Solution Overview
Problem
Current methods for locating interfering sources in signal reception systems, such as satellite radionavigation or digital communications receivers, face challenges in accurately determining the number of sources, their directions of arrival, and frequency localization due to complexity and unreliable results, especially when multiple interfering sources impact the same signal.
Innovation Solution
A method that calculates the spatio-temporal intercorrelation matrix and subdivides the signal band into sub-bands to generate band-pass filters, allowing for improved precision in estimating interfering sources by analyzing eigenvalues and eigenvectors, and determining directions of arrival through orthogonal subspaces.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the MUSIC algorithm is used to locate interfering sources by determining eigenvalues and eigenvectors of the intercorrelation matrix in the spatial domain, then the direction of arrival can be estimated, but the implementation complexity increases significantly for processors with limited resources
Solution Approach 1:
The patent divides the frequency band into multiple sub-bands and processes each sub-band separately. This segmentation reduces the complexity of eigenvalue decomposition by working with smaller, frequency-specific intercorrelation matrices rather than a single large matrix across the entire bandwidth, while maintaining accurate direction of arrival estimation for each interfering source.
2Measurement precision
If the MUSIC algorithm is applied to locate multiple interfering sources, then direction estimation is possible, but the results become unreliable for discriminating several interfering sources impacting the same signal
Solution Approach 1:
By segmenting the frequency spectrum into sub-bands and applying the MUSIC algorithm independently to each sub-band, the patent improves source discrimination reliability. Each sub-band processing yields independent direction estimates, and combining results from multiple sub-bands provides more reliable source identification and discrimination compared to processing the entire spectrum as a single band.
Solution Approach 2:
The patent transitions from purely spatial domain processing to joint spatio-frequency domain processing by introducing frequency sub-band decomposition. This additional frequency dimension enables better separation and discrimination of multiple interfering sources that may overlap in the spatial domain, improving both reliability and precision of source localization.
3Measurement precision
If conventional methods are used to determine the number of sources and their frequency localization, then basic localization is achieved, but precision is insufficient when several interfering sources exist
Solution Approach 1:
The patent segments the frequency spectrum into multiple sub-bands and performs independent analysis in each sub-band. This approach precisely identifies which sub-bands contain interfering sources and determines their frequency localization within those sub-bands, significantly improving frequency localization precision compared to conventional single-band methods.
Solution Approach 2:
The patent replaces complex mechanical or computational source separation techniques with a more elegant spectral decomposition approach. By transforming the problem into the frequency domain and using eigenvalue analysis of sub-band intercorrelation matrices, the method simplifies detection while enhancing precision in determining both the number and frequency localization of interfering sources.
Data Source
Figure 1a
Figure 1b~2
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AI summary
A method and system for locating sources interfering with a signal received by a receiver comprising an antenna array (501) characterized in that it comprises the following steps: ● a step of calculating the spatio-temporal cross-correlation matrix Rxx, ● a step of subdividing the useful bandwidth of said signals into sub-bands (b) ● for each sub-band (b), - a step of calculating the spatial cross-correlation matrix R(b) associated with the sub-band (b) and at least one of its eigenvalues {λ1, λ2,... λM}, - a step of detecting interference using the following detection criterion: log∑m=kMλm/M-k+1-log∏m=kMλm/M-k+1>threshold, - a step of determining the eigenvectors {U1, U2,...UN} of the spatial intercorrelation matrix R(b), - a step of determining the arrival directions of the interfering sources by searching for the relative gain vectors belonging to said interference subspace or which are orthogonal to the noise subspace orthogonal and complementary to the interference subspace.