Ladar Vibrometry Spectrum Identification via Computational Analysis
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Solution Overview
Problem
Conventional laser vibrometers require coherent micro-Doppler sources and sensors to capture fine frequency measurements, which are not available in systems like LADAR that provide only ranging information, limiting their ability to measure vibrational characteristics of objects.
Innovation Solution
A method and apparatus for identifying vibrometry spectra in imaging applications by obtaining and segmenting image data, analyzing segments to generate images based on vibrational characteristics, using LADAR systems that can provide ranging information to determine vibrational characteristics of objects without the need for coherent micro-Doppler sources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional laser vibrometers use coherent micro-Doppler sources and sensors, then fine frequency measurements can be captured, but the device complexity and cost increase significantly
Solution Approach 1:
The patent replaces the mechanical/optical coherent micro-Doppler sensing system with a computational approach. LADAR range data is processed through signal processing algorithms (FFT, spectral analysis) to extract vibrational characteristics, substituting complex physical sensing infrastructure with computational methods that achieve similar measurement precision without the associated hardware complexity
Solution Approach 2:
The patent introduces an intermediary computational processing layer between the LADAR range measurements and the final vibrational analysis. Signal processing algorithms act as intermediaries that transform raw range data into actionable vibrational spectra, enabling fine frequency measurements without direct coherent micro-Doppler sensing
2Device complexity
If LADAR systems provide only ranging information, then the system simplicity is maintained, but the ability to capture fine frequency measurements and vibrational characteristics is lost
Solution Approach 1:
The patent transforms the measurement parameter from simple range distance to vibrational frequency characteristics through computational analysis. By applying spectral analysis and FFT to the range-time data, the system extracts frequency information that was not directly measurable, effectively changing the measured parameter from spatial to temporal/frequency domain
Solution Approach 2:
The patent transitions from spatial measurement (range/distance) to temporal-frequency measurement by analyzing the time-series nature of LADAR data. Through spectral analysis, the system accesses the frequency dimension that is orthogonal to the original spatial measurement, enabling vibrational characterization without adding physical sensing dimensions
3Measurement precision
If specialized coherent micro-Doppler sensors are used, then vibrational characteristics can be measured, but the ease of operation and accessibility of the system decreases
Solution Approach 1:
The patent makes the LADAR system multi-functional by enabling it to perform both ranging and vibrational analysis with the same hardware platform. The computational processing layer allows a single LADAR system to serve multiple purposes, eliminating the need for specialized sensors and improving system accessibility and ease of operation
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 the identification of vibrational characteristics of objects using existing LADAR systems, allowing for the determination of operating status of vehicles and other equipment, and phenotypic information from range-only measurements, enhancing the capability to analyze vibrational data without the need for specialized sensors.
Implementation Method 1
Laser Detection and Ranging (LADAR) systems...provide only ranging (distance) information to a target's surface
Implementation Method 2
the frequency and amplitude of the surface's vibrations can be identified based on the Doppler shift of the reflected laser beam
Data Source
AI summary
A method includes obtaining image data associated with a specified area having one or more objects. The method also includes segmenting the image data into one or more segments associated with the one or more objects. The method further includes analyzing each of the one or more segments to identify a vibrometry spectrum associated with the corresponding object. In addition, the method includes generating an image of the specified area using the vibrometry spectrum associated with each object. The image of the specified area could illustrate each of the one or more objects with an intensity based on a total power of that target's total vibrational energy. The image of the specified area could also illustrate movement of at least one object over time.