Frequency Modulation Radar Eigenvalue Estimation
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Solution Overview
Problem
Conventional frequency modulation radar devices require time-series data collection in the absence of observation signals and eigenvalue calculation, making them inefficient and unreliable, especially when responding to temperature-related characteristic changes.
Innovation Solution
A frequency modulation radar device that transmits frequency-modulated signals, receives and mixes them to generate beat signals, analyzes these signals to calculate distance and orientation angles, and estimates the number of incident signals using a covariance matrix, eliminating the need for time-series data without observation signals and eigenvalue calculation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If time series data is collected in the absence of observation signals to obtain second eigenvalues, then eigenvalue analysis can be performed, but data acquisition time increases significantly
Solution Approach 1:
The patent extracts only the necessary first eigenvalues from the covariance matrix calculated during normal observation operations, eliminating the need to collect separate time series data in the absence of signals. This extraction approach allows eigenvalue-based signal discrimination to be performed using existing operational data, significantly reducing data acquisition time while maintaining measurement precision.
2Measurement precision
If separate time series data is collected for first and second eigenvalues, then eigenvalue analysis can be performed, but processing time increases significantly
Solution Approach 1:
The patent merges the calculation of first and second eigenvalues into a single covariance matrix computation performed during normal radar observation operations. By combining these calculations into one unified process rather than performing them separately on different data sets, the patent significantly reduces processing time while maintaining the accuracy of eigenvalue analysis for signal discrimination.
3Measurement precision
If second eigenvalues are obtained from time series data without observation signals, then signal discrimination can be performed, but reliability decreases due to environmental dependencies
Solution Approach 1:
The patent uses the first eigenvalues calculated during normal observation operations as feedback to discriminate between signal and noise components. By continuously monitoring and using the eigenvalue information from actual observation data rather than relying on separate calibration data, the system maintains reliable signal discrimination that adapts to environmental conditions in real-time.
4Measurement precision
If first and second eigenvalues are obtained from separate time series data, then eigenvalue analysis can be performed, but response to temperature characteristic changes is impaired due to time difference
Solution Approach 1:
The patent maintains continuous calculation of the covariance matrix and its eigenvalues during normal radar observation operations, ensuring that eigenvalue-based signal discrimination is always current and responsive to environmental changes. This continuous action eliminates the time delay between data collection and analysis, allowing the system to respond immediately to temperature characteristic changes and other environmental variations.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables accurate estimation of incident signals during temperature-related changes without requiring time-series data in the absence of observation signals, reducing data acquisition and processing time while maintaining reliability.
Implementation Method 1
mixing means for mixing the transmitting signal with the M received signals, respectively, to obtain beat signals for the M channels
Implementation Method 2
transmitting means for transmitting a transmitting signal that has been modulated in frequency so as to change a frequency at a constant change rate with time
Data Source
AI summary
The frequency modulation radar device includes a transmitting unit (5), M receiving units for receiving a reflected signal as M channels, a mixing unit (7) for mixing the transmitting signal with the M received signals to obtain beat signals for the M channels, a frequency analyzing unit (9) for analyzing the beat signals for the M channels in frequency, and a calculating unit (1) for calculating a distance to a target object and an orientation angle based on frequency analysis results. The calculating unit (1) calculates a noise level from the frequency analysis result, extracts a peak signal of a subject target object in each of the channels based on the calculated noise level to generate a covariance matrix, discriminates between a signal eigenvalue and a noise eigenvalue among M eigenvalues of the covariance matrix, and estimates the number of incident signals based on the number of signal eigenvalues.