Radar Target Recognition Using Inverse Transform Signatures
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Solution Overview
Problem
Conventional radar systems require substantial and costly processing capability to identify targets through time-frequency analysis of return signals, which can be inefficient and prone to false recognitions due to the complexity of signal processing and the dependency on aspect angles.
Innovation Solution
The system employs an inverse transform library to modulate RF signals with unique waveform patterns that, when reflected from targets, produce autocorrelation functions with detectable correlation peaks, allowing for improved target recognition by averaging multiple reflections and using polarization to enhance signal-to-noise ratio and reduce false recognitions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional radar systems use time-frequency analysis to identify targets, then target recognition capability is improved, but processing complexity and cost increase substantially
Solution Approach 1:
The patent pre-calculates and stores mirror image signatures for multiple target types and aspect angles before actual target detection. This preliminary preparation eliminates the need for complex real-time processing during target identification, as the system only needs to compare received signals against pre-computed reference signatures.
Solution Approach 2:
The patent creates simplified mirror image copies of target signatures through pre-computed reference data instead of performing full time-frequency analysis on each detected target. These copied signatures serve as templates for rapid comparison, dramatically reducing processing requirements while maintaining recognition accuracy.
2Measurement precision
If conventional radar systems perform complex signal processing to recognize targets, then target identification capability is improved, but false recognitions increase due to processing complexity
Solution Approach 1:
By pre-calculating mirror image signatures for various target types and aspect angles under controlled conditions, the system establishes accurate reference templates before actual detection. This preliminary characterization of targets reduces false recognitions during operational use by providing reliable comparison standards.
Solution Approach 2:
The system uses the comparison between received signals and pre-computed mirror image signatures as a feedback mechanism to verify target identity. This structured feedback approach with multiple aspect angle comparisons helps eliminate false recognitions by requiring consistent matches across different viewing angles.
3Productivity
If radar systems use standard RF signals for target detection, then detection capability is maintained, but target recognition accuracy decreases due to lack of unique waveform patterns
Solution Approach 1:
The patent applies different modulated waveform patterns corresponding to specific target types and aspect angles to the transmitted RF signal. This local differentiation of signal characteristics enables the system to elicit distinctive mirror image responses from different target types, improving recognition accuracy while maintaining overall detection capability.
Solution Approach 2:
The system changes the waveform parameters (amplitude, frequency, phase) of the transmitted RF signal based on the specific target type and aspect angle being detected. By modulating the signal with inverse transform data sets tailored to different targets, the system creates unique signal-target interactions that produce distinguishable mirror image signatures.
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
This approach enables efficient and accurate target identification with reduced processing requirements and improved accuracy by utilizing inverse transform data sets tailored to specific targets and aspect angles, enhancing the radar system's capability to distinguish between different targets while minimizing false recognitions.
Implementation Method 1
a radar system to transmit a radio-frequency signal and receive a return signal reflected from a scene
Implementation Method 2
The radar system may include an inverse transform library to provide an inverse transform data set corresponding to a target at an aspect angle. The inverse transform data set may be used to modulate a waveform transmitted from the radar system
Implementation Method 3
The modulated waveform and the return signal may be averaged and evaluated by a detector to determine if a target corresponding to the inverse transform data set has been detected within the scene
Data Source
AI summary
There is disclosed a system and method for detecting targets. A transmitter may transmit a first inverse transform signal, the first inverse transform signal derived from a reference image of a first reference target at a first aspect angle. A receiver may receive a return signal reflected from a scene. A detector may determine, based on the return signal, if an object similar to the first target at the first aspect angle is detected within the scene.