Spatial Energy Rank Detector for High-Speed Signal Alarm
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Solution Overview
Problem
Current spatial detection systems face challenges in accurately detecting signals of interest in a cluttered RF environment, particularly when co-channel interference is present, as they often rely on single-channel energy detection and do not scale well with increasing input channels, leading to computational bottlenecks and delayed processing.
Innovation Solution
The system employs a spatial energy detector using a General-Purpose Graphics Processing Unit (GPGPU) for parallel processing, computing Eigenvalues and Eigenvectors to identify positive rank changes in covariance matrices, enabling high-speed spatial detection and alarm generation, even in the presence of co-channel interference, by channelizing multiple coherent time domain IQ streams into narrowband streams for further processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple input channels are used to detect signals in cluttered RF environment, then the detection capability and resolution are improved, but the computational complexity and processing time increase significantly
Solution Approach 1:
The patent segments the wideband signal into multiple narrowband frequency channels using FFT-based filtering. Each channel is processed independently through the spatial detection algorithm, dividing the complex multi-channel problem into manageable sub-problems that can be solved in parallel, thereby reducing overall computational complexity while maintaining detection precision
Solution Approach 2:
The patent transforms the spatial detection problem from the time domain to the frequency domain by applying FFT to segment signals into narrowband channels. This dimensional transformation enables parallel processing of multiple frequency bands simultaneously, reducing the computational burden of processing wideband signals in the time domain while improving frequency resolution for signal detection
2Reliability
If traditional single-channel energy detection is used, then the computational complexity is low, but the detection of signals with lower power than dominant interferers is prevented
Solution Approach 1:
The patent introduces spatial dimension by utilizing multiple antenna elements to form a sensor array. By computing the covariance matrix of signals received across multiple antennas and performing Eigenvalue decomposition, the system creates additional degrees of freedom that enable separation of co-channel interferers from signals of interest, improving detection reliability in presence of dominant interferers
Solution Approach 2:
The patent changes the detection parameter from simple energy detection to spatial spectrum analysis using Eigenvalue decomposition of the covariance matrix. This parameter transformation enables the detector to identify signals based on their spatial characteristics rather than just power levels, allowing detection of low-power signals that would be masked by dominant interferers in traditional energy detection
3Adaptability or versatility
If wideband signal acquisition is performed across a wide range of frequencies, then the coverage and detection scope are improved, but the difficulty of discerning signals from background noise and co-channel interferers increases
Solution Approach 1:
The patent segments the wideband frequency spectrum into multiple narrowband channels using FFT-based filtering. Each narrowband channel is processed independently through the spatial detection algorithm, allowing the system to maintain high frequency coverage while reducing the complexity of signal discrimination in each individual channel by limiting the bandwidth
Solution Approach 2:
The patent adds the spatial dimension to the frequency-domain segmentation approach. By combining narrowband frequency filtering with spatial processing using multiple antenna elements, the system achieves both wide frequency coverage and improved signal discrimination capability, as the spatial dimension provides additional parameters for separating co-channel interferers from desired signals
Data Source
AI summary
A method, system, and computer program are described for identifying the presence of narrowband signals within a wide instantaneous bandwidth by exploiting the spatial diversity of the received signals using an array aperture to provide detection capability. For example, the method includes receiving and channelizing digitized signals into signals with a narrow bandwidth of interest. The method further includes estimating covariance matrices associated with the signals, determining a set of Eigenvalues for the covariance matrices, and analyzing each Eigenvalue to determine a rank change estimate. The method further includes identifying one or more of the signals that have a positive rank change estimate, computing a beam forming weight and direction estimate for each signal that has a positive rank change estimate, and outputting an indication of the signals that have a positive rank change estimate including one or more of fine timing information, the beamforming weights, and the direction estimate.