Compressive Sensing Tomographic Imaging Camera for FMCW LIDAR
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Solution Overview
Problem
Current full-field FMCW LIDAR systems face limitations due to the need for high-speed detector arrays, which are expensive and impractical, and require mechanical scanning, limiting their speed and efficiency in acquiring 3-D images.
Innovation Solution
The implementation of a compressive sensing (CS) based tomographic imaging camera (TomICam) that reduces the number of measurements required for 3-D imaging by projecting the unknown optical signal onto an incoherent basis using non-sinusoidal waveforms, allowing low-speed photodetector arrays like CCD or CMOS cameras to capture images in parallel, eliminating the need for high-speed detectors and mechanical scanning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If high-speed detector arrays are used for full-field FMCW LIDAR imaging, then image acquisition capability is improved, but system cost and complexity increase significantly
Solution Approach 1:
The patent applies dynamic frequency modulation of the laser source, varying the chirp rate and sweep frequency over time. This temporal modulation creates a time-varying interference pattern that encodes spatial information, allowing a static low-speed detector array to capture full-field 3-D images dynamically without requiring high-speed detection across all pixels simultaneously
Solution Approach 2:
The patent transforms the detection problem from the spatial domain to the temporal domain by modulating the optical frequency over time. The frequency-domain information is then mapped to spatial positions through the time-varying interference pattern, enabling a 2D detector array to capture 3-D information through temporal encoding rather than requiring high-speed simultaneous detection across all pixels
2Area of stationary object
If mechanical scanning is used to move optical beam across target, then full-field imaging is achieved, but image acquisition speed is limited
Solution Approach 1:
The patent replaces mechanical scanning systems with an electronically controlled frequency-modulated laser source. Instead of physically moving the optical beam across the target using mirrors or scanners, the system uses temporal frequency modulation to encode spatial information, eliminating mechanical moving parts while achieving full-field imaging capability
Solution Approach 2:
The patent performs preliminary frequency modulation of the laser source before the light interacts with the target. By pre-modulating the optical frequency in a controlled temporal pattern, the system encodes spatial information in advance, allowing the detector array to capture complete 3-D image data in a single shot without requiring subsequent mechanical scanning or sequential beam positioning
3Measurement precision
If broadband swept-frequency laser is used for high axial resolution, then range resolution is improved, but system complexity and cost increase
Solution Approach 1:
The patent changes the operational parameters of the laser source by implementing time-varying frequency modulation with varying chirp rates and sweep frequencies. This allows a single-mode laser to achieve broadband coverage and high axial resolution through dynamic parameter adjustment rather than requiring a complex mechanically tuned laser system, as the temporal modulation creates effective bandwidth expansion
Solution Approach 2:
The patent employs periodic frequency sweeping of the laser source with controlled chirp rates. By repeating the frequency sweep cycle multiple times with different temporal patterns, the system builds up spectral coverage and resolution through cumulative measurements, achieving high axial resolution through repeated periodic sampling rather than requiring a single complex broadband source
4Length of moving object
If single-pixel scanning is used to translate measurement laterally, then 3-D image construction is achieved, but data acquisition rate is reduced
Solution Approach 1:
The patent merges the functions of multiple detector pixels into a single low-speed detector array that captures parallel information simultaneously. By using temporal frequency modulation to encode spatial data for all lateral positions in the field of view within a single measurement cycle, the system combines what would traditionally require sequential single-pixel scanning into a parallel full-field capture, dramatically increasing data acquisition rate
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 significantly reduces image acquisition time and optical energy requirements, enabling efficient full-field 3-D imaging with a much smaller number of measurements, particularly for sparse targets, by using CS principles to spread information across a non-sinusoidal waveform basis, thus overcoming the limitations of existing systems.
Implementation Method 1
The output of the laser impinges on a target and the reflected signal is mixed with a part of the laser output in a photodetector (PD)
Implementation Method 2
Frequency modulated continuous wave (FMCW) reflectometry has emerged as a very important technique in a variety of applications including LIDAR
Data Source
AI summary
A detection apparatus and method for FMCW LIDAR employ signals that are modified so that low-cost and low-speed photodetector arrays, such as CCD or CMOS cameras, can be employed for range detection. The LIDAR is designed to measure the range to one or more targets and includes a single mode swept frequency laser (SFL), whose optical frequency is varied with time, as a result of which, a target beam which is reflected back by the one or more targets is shifted in frequency from a reference beam by an amount that is proportional to the relative range to the one or more targets. The reflected target beam(s) is/are combined with the reference beam and detected by the photodetector array. In the case of a sparse number of targets to be detected, Compressive Sensing (CS) techniques can be employed by a processor to reduce the number of measurements necessary to determine the range of each target.