Antenna Array Interference Direction Detection via Beamforming
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods in global navigation satellite systems (GNSS) fail to accurately detect the direction of arrival of interference signals, which hinders the characterization and identification of interference sources amidst the large volume of data received by antenna arrays.
Innovation Solution
A method employing beam forming signal processing techniques, including the calculation of a cross-covariance matrix and application of DOA algorithms like ESPRIT or MUSIC, to identify and evaluate the direction of arrival of interference signals, utilizing a device with an antenna array, signal receivers, and processing subsystems to differentiate between wanted and interference signals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If beam forming signal processing technique is applied to identify interference signals, then measurement precision of direction of arrival is improved, but device complexity increases due to additional processing subsystems and algorithms
Solution Approach 1:
The system segments the signal processing task by separating wanted signal processing from interference signal processing. Beam forming is applied specifically to identified interference signals rather than all received signals, dividing the complex processing into manageable segments that target specific problems.
Solution Approach 2:
The system performs preliminary identification of interference signals before applying beam forming processing. By first identifying which signals are interferences through power level comparison with noise, the system prepares the data in advance, so that the computationally intensive beam forming and DOA algorithms are only applied to relevant signals.
2Measurement precision
If all received data is analyzed to characterize interference, then measurement precision is improved, but loss of time increases due to processing large volume of data
Solution Approach 1:
The system extracts only the interference components from the received signals for detailed analysis. By identifying and separating interference signals from wanted signals, the system takes out only the relevant data portions that need characterization, avoiding unnecessary processing of clean signal segments.
Solution Approach 2:
Instead of applying exhaustive processing to all received data, the system applies partial processing only to identified interference signals. The beam forming and DOA algorithms are executed selectively on subsets of data that contain interferences, rather than processing the entire data stream uniformly.
3Productivity
If automatic detection of interferences is implemented, then productivity is improved by reducing manual analysis, but device complexity increases due to additional processing subsystems
Solution Approach 1:
The system implements self-service automatic detection where the processing subsystems autonomously identify and characterize interference signals without manual intervention. The beam forming and DOA algorithms automatically detect interference sources, their directions, and characteristics, enabling the system to service itself in terms of interference monitoring and characterization.
Data Source
AI summary
A method of detecting a direction of arrival of at least one interference signal interfering a wanted signal in a plurality of received signals involves receiving, by a number of antennas of an antenna array, a number of signals, identifying an interference signal in the received signals, applying a beam forming signal processing technique to the identified interference signal, and detecting the direction of arrival from the results of the beam forming signal processing.