Electromagnetic Signal Power Estimation via Correlation Peak Analysis
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Solution Overview
Problem
Existing systems for passively locating electromagnetic signal sources face challenges in achieving accurate and efficient position estimation due to high computing power consumption, long processing times, and difficulty in determining signal source power without prior knowledge, especially when using multiple receivers such as aircraft, marine vessels, or orbiting spacecraft.
Innovation Solution
A method involving band-pass filtering of signal datasets, determining correlation function peaks, and calculating Effective Signal to Noise Ratio (ESNR) to reduce computing resources and enhance convergence, while also estimating signal component powers and transmitter power to validate location estimates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multilateration techniques are used to estimate signal source location based on TDOA, then location estimation can be achieved, but computing power consumption is high and processing time is long
Solution Approach 1:
The patent applies preliminary action by performing band-pass filtering on signal datasets before correlation analysis. This preprocessing step removes out-of-band noise and interference early in the processing chain, reducing the computational burden on subsequent correlation and multilateration operations while preserving the essential signal characteristics needed for accurate TDOA estimation.
Solution Approach 2:
The patent extracts and utilizes the peak values of correlation functions between signal datasets from different receivers. By identifying and focusing on these peak correlation values, the system extracts the most relevant information for TDOA calculation, eliminating the need to process entire datasets and significantly reducing computational requirements while maintaining location estimation accuracy.
2Measurement precision
If signal processing is performed on multiple datasets from multiple receivers, then location estimation accuracy can be improved, but computing requirements increase
Solution Approach 1:
The patent extracts only the essential information needed for location estimation by computing correlation functions between datasets and identifying peak values. This extraction approach processes multiple receiver datasets to improve accuracy through multilateration, but computes only the necessary correlation peaks rather than performing exhaustive analysis on all data, thereby reducing computing power consumption.
Solution Approach 2:
The patent changes the parameter representation by transforming raw signal datasets into correlation function peak values. This parameter transformation consolidates information from multiple datasets into discrete peak values that capture the essential TDOA information, reducing the dimensionality and computational complexity of subsequent processing while maintaining the accuracy benefits of multi-receiver data.
3Measurement precision
If correlation function peak searching is performed by varying time offset, then signal component power can be determined, but search effort and processing time increase
Solution Approach 1:
The patent applies preliminary action by performing band-pass filtering to confine signals to a predetermined frequency range before correlation analysis. This preprocessing narrows the spectral content of the signals, which concentrates the correlation function energy and allows for more efficient peak searching with reduced time offset variations needed, thereby reducing processing time while maintaining accurate signal component power determination.
4Productivity
If band-pass filtering is applied to confine signals to predetermined frequency range, then processing efficiency is improved, but signal information may be lost if filtering is too aggressive
Solution Approach 1:
The patent changes the frequency domain parameters by applying band-pass filtering with a predetermined frequency range that confines the signals of interest. This parameter change improves processing efficiency by reducing the bandwidth that subsequent processing stages must handle, while the predetermined range is selected to preserve the essential signal characteristics needed for correlation and TDOA estimation, balancing efficiency gains with information preservation.
Data Source
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AI summary
The application relates to a method of determining the power of an electromagnetic signal emission. Also disclosed is a system comprising apparatus for carrying out the method, and a computer-readable medium storing a computer program for carrying out the method. The method includes obtaining a plurality of datasets each comprising a plurality of successive samples of the electromagnetic signal as received at a corresponding receiver, and for each of one of more pairs of the datasets: determining a first received power being that of a first dataset of the respective pair; determining a second received power being that of a dataset of the respective pair; ensuring that the signals represented in the first and second datasets of the respective pair are band-pass filtered according to a predetermined frequency range, thereby obtaining first and second filtered datasets; determining a respective peak of a correlation function between the first and second filtered datasets, wherein determining the respective peak comprises searching for a maximum of the correlation function while varying at least a time offset between samples of the first filtered dataset and samples of the second filtered dataset; and determining, based on the respective peak value of the correlation function, a respective sum of a signal component power of the first filtered dataset and a signal component power of the second filtered dataset.